analysis_demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis of a bias-free network\n",
    "\n",
    "A bias-free network operates on its input by applying an adaptive linear transform (adaptive, because the transform is dependent on the input image). In this notebook, we analyze the properties of this transform using singular value decomposition.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pylab as plt\n",
    "import matplotlib.patches as patches\n",
    "import os\n",
    "import torch\n",
    "from skimage import io\n",
    "from skimage.measure.simple_metrics import compare_psnr, compare_mse\n",
    "import sys  \n",
    "from utils import *\n",
    "import time \n",
    "\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Paths for data, pretrained models, and precomputed performance measures\n",
    "pretrained_base = './pretrained/'\n",
    "precomputed_base = './precomputed/'\n",
    "data_base = 'data/'\n",
    "\n",
    "# Datasets available in the data folder\n",
    "train_folder_path = os.path.join(data_base, 'Train400/')\n",
    "test_folder_path = os.path.join(data_base, 'Test/Set68/')\n",
    "set12_path = os.path.join(data_base, 'Test/Set12/')\n",
    "kodak_path = os.path.join(data_base, 'Test/Kodak23/') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Choose a model \n",
    "\n",
    "Note: we provide four pre-trained models. You can train and analyze any other model (and its bias-free counterpart) using the train script provided in the repository. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Choose a model (pre-trained options: 'dncnn', 'unet', 'rcnn', 'sdensenet')\n",
    "model = 'dncnn' \n",
    "\n",
    "# Select the range of noise levels (stdev, relative to intensities in range [0,255]) \n",
    "# used during training (options are 0-10, 0-30, 0-55, 0-100).\n",
    "l = 0   # lower bound of training range \n",
    "h = 100 # upper bound of training range\n",
    "\n",
    "BF_CNN = load_model(os.path.join(pretrained_base, model, 'bias_free', str(l)+'-'+str(h)+'.pt'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Choose a clean image\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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=\"300\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# choose a clean image (figure 4 in paper uses image_num=15)\n",
    "image_num = 15\n",
    "clean_im = single_image_loader(test_folder_path, image_num)\n",
    "\n",
    "# Crop out a 40x40 patch (optional, helps for visibility.  Same values used for Figure 4 in paper).\n",
    "clean_im = clean_im[100:140, 100:140]\n",
    "dim1, dim2 = clean_im.shape\n",
    "f , axs = plt.subplots(1,1 , figsize=(3,3))    \n",
    "axs.imshow(clean_im, 'gray', vmin=0, vmax = 1)\n",
    "axs.axis('off');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interpretation: Nonlinear adaptive filtering\n",
    "\n",
    "Since the BF-CNN can be interpreted as applying an adaptive linear transform, each pixel in the denoised image is a weighted sum of input pixels. The weighting function is one row of the Jacobian, evaluated at the input image. Here, we examine this weighting function for selected output pixels, as shown in Figure 4 of the paper."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interactive visualization of adaptive filters\n",
    "\n",
    "Note that all weighting functions sum to approximately one, and thus compute a local average. Their shapes vary substantially, and are adapted to the underlying image content. As the noise level increases, the spatial extent of the weight functions increases in order to average out the noise, while respecting boundaries between different regions in the image, which results in dramatically different functions for each pixel (i.e., non-convolutional)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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>"
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     "output_type": "display_data"
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Choose some noise levels to examine, relative to image intensities in range (0,255)\n",
    "# Note: Figure 4 of paper uses [10, 30, 100].\n",
    "noise_levels = [10, 30, 90] \n",
    "\n",
    "global residual_imgs, input_imgs\n",
    "input_imgs = []\n",
    "residual_imgs = []\n",
    "\n",
    "%matplotlib notebook\n",
    "\n",
    "fig = plt.figure(figsize = (8,9))\n",
    "fig.suptitle('click on a pixel on any of the noisy images to see filters')\n",
    "plt.axis('off')\n",
    "ax_names=[]\n",
    "\n",
    "for j in range(len(noise_levels)):\n",
    "    # add noise\n",
    "    noisy_im, _ = add_noise2(clean_im.reshape(1,dim1,dim2), noise_levels[j], 'S') \n",
    "    # plot noisy\n",
    "    ax = fig.add_subplot(3,len(noise_levels),j+1)\n",
    "    ax.imshow(noisy_im[0], 'gray', vmin = 0, vmax = 1)\n",
    "    ax.tick_params(bottom=False,left=False,labelleft=False,labelbottom=False)\n",
    "    ax.set_title(r'$\\sigma = $ ' + str(noise_levels[j]) + '\\n noisy image')\n",
    "    ax_names.append(ax)  \n",
    "\n",
    "    # denoise\n",
    "    inp_test = torch.tensor(noisy_im.astype('float32'),requires_grad=True).unsqueeze(1)\n",
    "    input_imgs.append(inp_test)\n",
    "    residual= BF_CNN(inp_test)\n",
    "    residual_imgs.append(residual)\n",
    "    denoised = residual.squeeze(0).squeeze(0).data.numpy()\n",
    "    \n",
    "    # plot denoised\n",
    "    ax = fig.add_subplot(3,len(noise_levels),j+len(noise_levels)+1)\n",
    "    ax.imshow(denoised, 'gray', vmin = 0, vmax = 1)\n",
    "    ax.tick_params(bottom=False,left=False,labelleft=False,labelbottom=False)\n",
    "    ax.set_title( 'denoised image')    \n",
    "    \n",
    "global last_pa \n",
    "last_pa = []\n",
    "\n",
    "ix, iy = 0, 0\n",
    "def onclick(event):\n",
    "\n",
    "    global ix, iy\n",
    "    ix, iy = int(event.xdata), int(event.ydata)\n",
    "    \n",
    "    # remove previous pixel marker\n",
    "    if len(last_pa) != 0:       \n",
    "        for i in range(len(last_pa)):\n",
    "            last_pa[i].set_visible(False)         \n",
    "    \n",
    "    for j in range(len(noise_levels)):\n",
    "        ax = fig.add_subplot(fig.add_subplot(3,len(noise_levels),j+len(noise_levels)*2+1))\n",
    "        filt = torch.autograd.grad(residual_imgs[j][0,0,iy,ix], input_imgs[j], retain_graph=True)[0][0,0].data.numpy() \n",
    "        limit =  max(np.abs(np.min( filt)), np.abs(np.max( filt)))\n",
    "        ax.imshow(filt, 'RdGy', vmin= -limit, vmax = limit)\n",
    "        ax.set_title('adaptive filter \\n sum = ' + str( np.round(np.sum(filt),2)))\n",
    "        ax.tick_params(bottom=False,left=False,labelleft=False,labelbottom=False)\n",
    "        pa = patches.Rectangle((ix-.5,iy-.5), width=1, height=1,edgecolor = [1,0,0], angle=0.0, facecolor='red', lw=1)\n",
    "        ax_names[j].add_patch(pa)\n",
    "        last_pa.append(pa)\n",
    "        \n",
    "cid = fig.canvas.mpl_connect('button_press_event', onclick);\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# exit the interactive mode\n",
    "f.canvas.mpl_disconnect(cid)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interpretation: Projection onto an adaptive signal subspace\n",
    "\n",
    "We can study the effect of the linear transformation, A, by looking into its column space. A singular value decomposition of A, reveals that 1) most singular values are  close to zero, implying that the network is discarding all but a very low-dimensional portion of the input image, and 2) left and right singular vectors of the signal subspace are nearly identical. This means that we can interpret the action of the network as projecting the noisy signal onto a low-dimensional subspace.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compute SVD of Jacobian (adaptive linear transform) of denoiser\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---- Jacobian computation time --- 52.0781512260437 seconds ---\n"
     ]
    }
   ],
   "source": [
    "# Compute the Jacobian, evaluated at a noisy version of the clean image selected above. \n",
    "# WARNING: slow computation! For a 40x40 patch, it can take between 1 and 2 minutes. \n",
    "\n",
    "noisy_im = add_noise2(clean_im.reshape(1,dim1,dim2), 90, 'S')[0][0] \n",
    "\n",
    "start_time_total = time.time()\n",
    "A = calc_jacobian(noisy_im,BF_CNN)\n",
    "print(\"---- Jacobian computation time --- %s seconds ---\" % (time.time() - start_time_total))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compute SVD of Jacobian\n",
    "U , S, V = np.linalg.svd( A)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot singular values\n",
    "\n",
    "Note that most singular values are close to zero, suggesting\n",
    "the denoiser is eliminating many dimensions.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>"
      ]
     },
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     "output_type": "display_data"
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the singular values against the axis number. \n",
    "f, ax = plt.subplots(1,1,figsize = (8,4))\n",
    "\n",
    "ax.set_xlabel('axis number ', fontsize = 12, fontname= 'Times New Roman')\n",
    "ax.set_ylabel('singular values', fontsize = 12, fontname= 'Times New Roman')   \n",
    "\n",
    "for tick in ax.xaxis.get_major_ticks():\n",
    "    tick.label.set_fontsize(10) \n",
    "    tick.label.set_fontname(\"Times New Roman\")\n",
    "\n",
    "for tick in ax.yaxis.get_major_ticks():\n",
    "    tick.label.set_fontsize(10) \n",
    "    tick.label.set_fontname(\"Times New Roman\")\n",
    "    \n",
    "ax.plot(S, '-o', alpha = 1, markersize = 2,linewidth=1);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize some example singular vectors with large singular values\n",
    "\n",
    "These are 'features' of the input image that are preserved by the denoiser."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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"
    },
    {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show some example singular vectors with large singular values\n",
    "sing_vect_n = [10,11,12,13] # indices of the singular vectors for visualization \n",
    "\n",
    "N = dim1*dim2 # dimensionality of the space\n",
    "\n",
    "limit =  max(np.abs(np.min( U[:,sing_vect_n])), np.abs(np.max(U[:,sing_vect_n])))\n",
    "f , axs = plt.subplots(1,len(sing_vect_n) , figsize=(8,3))    \n",
    "plt.subplots_adjust()\n",
    "for i in range(len(sing_vect_n)):\n",
    "    u = U[:,sing_vect_n[i]]\n",
    "    v = V[sing_vect_n[i],:]\n",
    "    axs[i].imshow(u.reshape(dim1,dim2), 'gray', vmin=-limit/2, vmax = limit/2)\n",
    "    axs[i].set_title('singular vector '+str(sing_vect_n[i]), fontsize = 10, fontname= 'Times New Roman')\n",
    "    axs[i].tick_params(bottom=False,left=False,labelleft=False,labelbottom=False)\n",
    "    axs[i].set_xlabel(r'$v^Tu$ =  '+str(np.round( np.dot(u,v) ,2))+ '\\n $s =$ '+str(np.round(S[sing_vect_n[i]],1)),\n",
    "                      fontsize = 10, fontname= 'Times New Roman');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize some example singular vectors with small singular values\n",
    "\n",
    "These are 'features' of the input image that are discarded by the denoiser."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "scrolled": true
   },
   "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"
    },
    {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show some example singular vectors with small singular values\n",
    "sing_vect_n = [N-10,N-11,N-12,N-13] # indices of the singular vectors for visualization \n",
    "\n",
    "limit =  max(np.abs(np.min( U[:,sing_vect_n])), np.abs(np.max(U[:,sing_vect_n])))\n",
    "f , axs = plt.subplots(1,len(sing_vect_n) , figsize=(8,3))    \n",
    "plt.subplots_adjust()\n",
    "for i in range(len(sing_vect_n)):\n",
    "    u = U[:,sing_vect_n[i]]\n",
    "    v = V[sing_vect_n[i],:]\n",
    "    axs[i].imshow(u.reshape(dim1,dim2), 'gray', vmin=-limit/2, vmax = limit/2)\n",
    "    axs[i].set_title('singular vector '+str(sing_vect_n[i]), fontsize = 10, fontname= 'Times New Roman')\n",
    "    axs[i].tick_params(bottom=False,left=False,labelleft=False,labelbottom=False)\n",
    "    axs[i].set_xlabel(r'$v^Tu$ =  '+str(np.round( np.dot(u,v) ,2))+ '\\n $s =$ '+str(np.round(S[sing_vect_n[i]],1)),\n",
    "                      fontsize = 10, fontname= 'Times New Roman');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Left and right singular vectors with significant singular values are nearly identical\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "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"
    },
    {
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\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute dot products of left and right singular vectors (u.v=1). \n",
    "subspace_dim = int(np.sum((S)**2))\n",
    "uvdots = []\n",
    "for j in range(N):\n",
    "    v = V[j,:]\n",
    "    u = U[:,j]\n",
    "    uvdots.append(abs(np.dot(v,u)))\n",
    "\n",
    "# Plot dot products as a function of associated singular value\n",
    "f, ax = plt.subplots(1,1,figsize = (6,4))\n",
    "ax.plot(S, uvdots, '.', color = 'lightgray', markersize=2 , label='discarded axes')       \n",
    "ax.plot(S[0:subspace_dim], uvdots[0:subspace_dim], '.',markersize=3,color='green',alpha=1, label = 'preserved axes')     \n",
    "ax.set_ylabel(r'${v}^T{u} $', fontsize = 12, fontname= 'Times New Roman')\n",
    "ax.set_xlabel('singular values', fontsize = 12, fontname= 'Times New Roman')   \n",
    "plt.legend()\n",
    "for tick in ax.xaxis.get_major_ticks():\n",
    "    tick.label.set_fontsize(10) \n",
    "    tick.label.set_fontname(\"Times New Roman\")\n",
    "for tick in ax.yaxis.get_major_ticks():\n",
    "    tick.label.set_fontsize(10) \n",
    "    tick.label.set_fontname(\"Times New Roman\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}