PCA-tSNE-AE.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PCA-tSNE-AE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "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": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "iris_dataset = datasets.load_iris()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "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": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
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       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
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       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
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       "\n",
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       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
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       "\n",
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       "    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",
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       "    if (!this.waiting) {\n",
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       "        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",
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       "        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",
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       "    x0 = Math.floor(x0) + 0.5;\n",
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       "    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",
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       "        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",
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       "        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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "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)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## TSNE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "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": 23,
   "metadata": {},
   "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": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 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)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "TensorFlow-GPU",
   "language": "python",
   "name": "tf-gpu"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}