Construct the f0 - Sed Thickness Powerlaw Relation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Notebook to construct the resonance frequency - Sediment thickness Powerlaw Relation\n",
    "\n",
    "#### Loads Supplementary data tables and plots the figures of the paper in below\n",
    "Van Noten, K., Lecocq, T., Goffin, C., Meyvis, B., Molron, J., Debacker, T. & Devleeschouwer, X. accepted. Brussels’ bedrock paleorelief from borehole-controlled powerlaws linking polarised H/V resonance frequencies and sediment thickness. Journal of Seismology."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-03-30T11:56:29.403640Z",
     "start_time": "2018-03-30T11:56:29.390606Z"
    }
   },
   "outputs": [],
   "source": [
    "import traceback\n",
    "import matplotlib\n",
    "matplotlib.use(\"nbagg\")\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.cm as cm\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from scipy.optimize import curve_fit\n",
    "from matplotlib.ticker import FormatStrFormatter\n",
    "from matplotlib.ticker import ScalarFormatter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-03-30T11:56:29.544444Z",
     "start_time": "2018-03-30T11:56:29.527397Z"
    }
   },
   "outputs": [],
   "source": [
    "## only set borehole = 0 to create figure 6B\n",
    "borehole = 1\n",
    "\n",
    "if borehole:\n",
    "    df = pd.read_csv('VanNotenetal_JOSE_S1 - Borehole HVSR analysis.csv', delimiter=',', skiprows=33, engine = 'python')\n",
    "else:\n",
    "    #df = pd.read_csv(\"HVSR Brussels survey.csv\", delimiter=',', skiprows=0, engine = 'python')\n",
    "    df = pd.read_csv('VanNotenetal_JOSE_S2 - Survey HVSR analysis.csv', delimiter=',', skiprows=33, engine = 'python')\n",
    "    print(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define regions for which you want to compute the powerlaw relations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-03-30T11:56:31.668906Z",
     "start_time": "2018-03-30T11:56:31.612749Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "88 88\n",
      "   Nr             Location     ID    Easting   Northing        lat       lon  \\\n",
      "0   1  Watermaal-Bosvoorde    C05  152808.74  166177.22  50.806039  4.408599   \n",
      "1   2            Uccle ROB  Ukkel  149305.00  165170.00  50.796991  4.358893   \n",
      "2   3            Uccle ROB  Ukkel  149305.00  165170.00  50.796991  4.358893   \n",
      "3   4               Elsene    C08  150997.92  168012.92  50.822547  4.382914   \n",
      "4   5  Sint-Stevens-Woluwe    C12  153217.39  172254.37  50.860668  4.414451   \n",
      "\n",
      "   Z (DEM)                     Geology Region  ...          Vs  a_R1_R2_R3_R4  \\\n",
      "0    88.70  ['Mal', 'Ld', 'Br', 'Shh']     R3  ...  379.749884         90.422   \n",
      "1   101.01  ['Mal', 'Ld', 'Br', 'Shh']     R3  ...  421.015856         90.422   \n",
      "2   101.01  ['Mal', 'Ld', 'Br', 'Shh']     R3  ...  421.832749         90.422   \n",
      "3    84.75  ['Mal', 'Ld', 'Br', 'Shh']     R3  ...  405.530579         90.422   \n",
      "4    76.88  ['Mal', 'Ld', 'Br', 'Shh']     R3  ...  488.968204         90.422   \n",
      "\n",
      "   b_R1_R2_R3_R4 h_Indiv  h-h_indiv    a_R'   b_R'   h_all  h-h_all  diff  \n",
      "0         -1.641  125.98     -10.48  88.631 -1.683  124.54    -9.04 -1.44  \n",
      "1         -1.641  113.64       2.76  88.631 -1.683  112.04     4.36  1.60  \n",
      "2         -1.641  113.64       4.06  88.631 -1.683  112.04     5.66  1.60  \n",
      "3         -1.641  122.04      -0.04  88.631 -1.683  120.54     1.46  1.42  \n",
      "4         -1.641  139.74      16.76  88.631 -1.683  138.51    17.99  1.23  \n",
      "\n",
      "[5 rows x 32 columns]\n",
      "88\n"
     ]
    }
   ],
   "source": [
    "# define the groups (named R1 --> R4 in the paper)\n",
    "colors = ['lightblue', 'grey', 'yellow', 'lightpink']\n",
    "labels = ['R1', 'R2','R3', 'R4']\n",
    "\n",
    "PW_sand = ['Mal', 'Ld', 'Br', 'Shh']\n",
    "#PW_al_sand = ['Br_Al'] #modification 20190326: Br_AL included in the Aluvium algorithm\n",
    "PW_clay = ['KoMo', 'KoSm']\n",
    "PW_al_clay = ['KoMo_Al', 'KoSm_Al', 'Br_Al']\n",
    "PW_pal = ['Pal_Al', 'Hn_Al']\n",
    "\n",
    "geol_group = []\n",
    "geol_color = []\n",
    "error = []\n",
    "for id, row in df.iterrows():\n",
    "    for j, g in enumerate([PW_sand, PW_clay, PW_al_clay, PW_pal]):\n",
    "        if row[\"Geology\"] in g:\n",
    "            geol_group.append(str(g))\n",
    "            break\n",
    "print(len(df), len(geol_group))\n",
    "df[\"Geology\"] = geol_group\n",
    "print(df.head())\n",
    "print(len(df))\n",
    "\n",
    "\n",
    "#We deliberately delete alluvial deposits on top of Paleozoicum and Hannut out of the equation (R4)\n",
    "#These alluvial deposits have completely different characteristics which cannot be linked to a general powerlaw.\n",
    "PW_pal = ['Pal_Al', 'Hn_Al']\n",
    "df2 = df[df[\"Geology\"] != str(PW_pal) ] "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fig. 5: Powerlaw regression for Brussels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-03-30T12:15:31.983184Z",
     "start_time": "2018-03-30T12:15:31.425456Z"
    },
    "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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "************************************************** ['KoMo', 'KoSm']\n",
      "n =  23\n",
      "a and b parameters= [87.57623187 -1.66259419]\n",
      "R2 0.9740473045045851\n",
      "************************************************** ['KoMo_Al', 'KoSm_Al', 'Br_Al']\n",
      "n =  26\n",
      "a and b parameters= [88.48609208 -1.73496473]\n",
      "R2 0.851177619395151\n",
      "************************************************** ['Mal', 'Ld', 'Br', 'Shh']\n",
      "n =  27\n",
      "a and b parameters= [90.42167141 -1.64075696]\n",
      "R2 0.9011440611436456\n",
      "************************************************** ['Pal_Al', 'Hn_Al']\n",
      "n =  12\n",
      "a and b parameters= [200.          -2.02784251]\n",
      "R2 0.48259273283433535\n",
      "************************************************** All data\n",
      "n =  88\n",
      "a and b parameters= [91.45262511 -1.63273091]\n",
      "R2 0.9138429029548205\n",
      "************************************************** All data - R4\n",
      "n =  76\n",
      "a and b parameters= [88.63111939 -1.68309326]\n",
      "R2 0.9750791972529225\n"
     ]
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "#defining the shape of the powerlaw function that needs to be fit (note: this is the inverse of the relation h = a.f0.exp(b))\n",
    "def func(x, a, b):\n",
    "    return (x/a)**(1.0/b)\n",
    "\n",
    "def powerlaw(x,y,z, label_group, color, ls, linewidth):\n",
    "    print(\"n = \", len(x))\n",
    "    popt, pcov = curve_fit(func, x, y, p0=(100, -1.5),bounds=([0,-5], [200, 0.0]),\n",
    "                       sigma= z, absolute_sigma=True)\n",
    "    print(\"a and b parameters=\", popt)\n",
    "    a,b = popt\n",
    "    xx = np.linspace(np.min(x), np.max(x), 1000)\n",
    "    yy = func(xx, *popt)\n",
    "    plt.plot(xx, yy, c=color, ls=ls, label='%s: %s*$f_0$$^{%s}$'%(label_group, round(popt[0],3), round(popt[1],3)), \n",
    "             linewidth = linewidth)\n",
    "    yy = func(x, *popt)\n",
    "    residuals = y - yy\n",
    "    ss_res = np.sum(residuals**2)\n",
    "    ss_tot = np.sum((y-np.mean(y))**2)\n",
    "    r_squared = 1 - (ss_res / ss_tot)\n",
    "    print(\"R2\", r_squared)\n",
    "    return a,b\n",
    "\n",
    "plt.figure(figsize=(8,6))\n",
    "ax = plt.subplot(111)\n",
    "\n",
    "i = 0\n",
    "#gather a and b values for later\n",
    "a_values = []\n",
    "b_values = []\n",
    "f0_range_min = []\n",
    "f0_range_max = []\n",
    "groups = df.groupby(\"Geology\")\n",
    "for id, group in groups:       \n",
    "    print(\"*\"*50, id)\n",
    "    Name = group[\"ID\"]\n",
    "    x = group[\"h\"]\n",
    "    y = group[\"f0_ip\"]\n",
    "    z = group[\"error\"]\n",
    "    \n",
    "    # x array to interpolate values on, after curve fitting, but limited to the array data\n",
    "    xx = np.linspace(np.min(x), np.max(x), 1000)\n",
    "\n",
    "    try:\n",
    "        f0_range_min.append(np.min(y))\n",
    "        f0_range_max.append(np.max(y))\n",
    "        \n",
    "        ## perform the regression: curve fitting with scipy; bounds give you the range of the a and b values\n",
    "        a,b = powerlaw(x,y,z,labels[i], colors[i], ls = '-', linewidth = 3)\n",
    "        a_values.append(a)\n",
    "        b_values.append(b)\n",
    "    except:\n",
    "        traceback.print_exc()\n",
    "\n",
    "    plt.scatter(x, y, s=30, label = \"%s (%s)\"%(labels[i], len(x)), edgecolor='black', c=colors[i], zorder=4)\n",
    "    #plt.scatter(x, y, s=30, edgecolor='black', label  ='', c=colors[i], zorder=4)\n",
    "    \n",
    "    plt.errorbar(x, y, xerr = None, yerr=z, c='black', label=\"\", ls=\"none\", zorder = 3, capsize=2)\n",
    "        \n",
    "    i+=1\n",
    "    \n",
    "# ************************************************** Compute powerlaw regression through all data (no group)\n",
    "print(\"*\"*50, \"All data\")\n",
    "## for all data; check if you wanna use all data (=df) \n",
    "## or only those data without the sediments on top of the paleozoicum (other velocities) = df2\n",
    "x = df[\"h\"]\n",
    "y = df[\"f0_ip\"]\n",
    "z = df[\"error\"]\n",
    "a,b = powerlaw(x,y,z,'R','grey', ls = \":\", linewidth = 2)\n",
    "\n",
    "# ************************************************** Compute powerlaw regression through all data - Region 4\n",
    "print(\"*\"*50, \"All data - R4\")\n",
    "## for all data; check if you wanna use all data (=df) \n",
    "## or only those data without the sediments on top of the paleozoicum (other velocities) = df2\n",
    "x = df2[\"h\"]\n",
    "y = df2[\"f0_ip\"]\n",
    "z = df2[\"error\"]\n",
    "a,b = powerlaw(x,y,z,\"R'\", 'k', ls=\"--\", linewidth = 2)\n",
    "a_values.append(a)\n",
    "b_values.append(b)\n",
    "\n",
    "##### adjust the plot and save\n",
    "plt.legend(title=\"Powerlaw eqs\", frameon=True, ncol=1)\n",
    "plt.xlabel(\"Sediment Thickness (m)\")\n",
    "plt.ylabel('$f_{0}$ (Hz)')\n",
    "\n",
    "plt.xlim(2.8,200)\n",
    "plt.ylim(0.6,8)\n",
    "plt.xticks(rotation='vertical')\n",
    "ax.set_xscale('log')\n",
    "ax.set_yscale('log')\n",
    "\n",
    "plt.setp(ax.xaxis.get_minorticklabels(), rotation=90)\n",
    "ax.xaxis.set_major_formatter(FormatStrFormatter('%.f'))\n",
    "ax.yaxis.set_major_formatter(FormatStrFormatter('%.f'))\n",
    "ax.xaxis.set_minor_formatter(FormatStrFormatter('%.f'))\n",
    "ax.yaxis.set_minor_formatter(FormatStrFormatter('%.1f'))\n",
    "plt.grid(which='minor', zorder = -3) # horizontal lines\n",
    "plt.savefig(\"Fig. 5 - Powerlaw derivation.png\", dpi=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 8: Compare amplitudes and resonance frequencies of borehole measurements and survey measurements\n",
    "Make an amplitude and resonance frequency histogram of borehole measurements and survey measurements.\n",
    "At the top of the notebook: Set boreholes = 1 for Fig. 8A; Set boreholes = 0 for Fig. 8B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "23\n",
      "26\n",
      "27\n",
      "12\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "import pylab as P\n",
    "import matplotlib.gridspec as gridspec\n",
    "plt.close('all')\n",
    "\n",
    "i = 0\n",
    "if borehole:\n",
    "    labels = ['R1 (23)', 'R2 (26)','R3 (27)', 'R4 (12)']\n",
    "else:\n",
    "    labels = ['R1 (32)', 'R2 (24)','R3 (343)', 'R4 (5)']\n",
    "    \n",
    "\n",
    "A0s = []\n",
    "ids = []\n",
    "f0s = []\n",
    "\n",
    "for id, group in groups:\n",
    "    f0 = group[\"f0_ip\"]\n",
    "    A0 = group[\"A0\"]\n",
    "    A0s.append(A0)\n",
    "    ids.append(id)\n",
    "    f0s.append(f0)\n",
    "    print(len(group))\n",
    "    \n",
    "#create figure\n",
    "gs = gridspec.GridSpec(1, 2, width_ratios= (1,1))\n",
    "if borehole:\n",
    "    plt.figure(figsize=(9, 3))\n",
    "else:\n",
    "    plt.figure(figsize=(9, 5))\n",
    "\n",
    "\n",
    "#histogram plotter\n",
    "ax0 = plt.subplot(gs[0])\n",
    "bins = np.arange(0,26, 1)\n",
    "n, bins, patches = P.hist(A0s, bins,orientation='vertical', color = colors, \n",
    "                          edgecolor = 'black', zorder = 5, stacked = 1, label = labels)\n",
    "plt.grid(zorder = -5, ls = '--')\n",
    "plt.ylabel(\"Nr\")\n",
    "if borehole:\n",
    "    plt.ylim(20,0)\n",
    "    plt.yticks(np.arange(0, 20, step=2))\n",
    "    plt.text(15.5,6,'Boreholes', bbox=dict(facecolor='white', alpha=1))\n",
    "else:\n",
    "    plt.title(\"Amplitude\")\n",
    "    plt.ylim(0,70)\n",
    "    plt.text(15.5,43,'Survey', bbox=dict(facecolor='white', alpha=1))\n",
    "    ax0.xaxis.set_ticklabels([])\n",
    "plt.legend()\n",
    "\n",
    "ax1 = plt.subplot(gs[1])\n",
    "bins=np.logspace(np.log10(0.5),np.log10(5), 50)\n",
    "n, bins, patches = P.hist(f0s, bins,orientation='vertical', color = colors, edgecolor = 'black', \n",
    "                          zorder = 5, stacked = 1, label = labels)\n",
    "plt.ylabel(\"Nr\")\n",
    "ax1.set_xscale(\"log\")\n",
    "plt.grid(b=True, which='major', linestyle='--')\n",
    "plt.grid(b=True, which='minor', linestyle='--')\n",
    "\n",
    "\n",
    "plt.setp(ax1.xaxis.get_minorticklabels(), rotation=90)\n",
    "plt.xlim(0.5,6)\n",
    "\n",
    "if borehole:\n",
    "    ax1.invert_yaxis()\n",
    "    plt.ylim(20,0)\n",
    "    plt.yticks(np.arange(0, 20, step=2))\n",
    "    plt.legend(loc=4)\n",
    "    plt.xlabel(\"Frequency (Hz)\")\n",
    "    plt.xticks(rotation='vertical')\n",
    "    plt.text(2.1,6,'Boreholes', bbox=dict(facecolor='white', alpha=1))\n",
    "    plt.gca().xaxis.set_major_formatter(FormatStrFormatter('%.1f'))\n",
    "    plt.gca().xaxis.set_minor_formatter(FormatStrFormatter('%.1f'))\n",
    "    plt.savefig(\"Fig 6B - Amplitude - f0 histogram - boreholes.png\", dpi=600) \n",
    "    \n",
    "else:\n",
    "    plt.title(\"Resonance frequency (Hz)\")\n",
    "    plt.ylim(0,70)\n",
    "    plt.text(2.1,43,'Survey', bbox=dict(facecolor='white', alpha=1))\n",
    "    ax1.xaxis.set_ticklabels([])\n",
    "    plt.legend()\n",
    "    plt.savefig(\"Fig 6A - Amplitude - f0 histogram - survey.png\", dpi=600)\n",
    "    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fig. 6A: Computation of residuals between predicted bedrock depth and true bedrock depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "************************************************** ['KoMo', 'KoSm']\n",
      "n =  23\n",
      "************************************************** ['KoMo_Al', 'KoSm_Al', 'Br_Al']\n",
      "n =  26\n",
      "************************************************** ['Mal', 'Ld', 'Br', 'Shh']\n",
      "n =  27\n",
      "************************************************** ['Pal_Al', 'Hn_Al']\n",
      "n =  12\n"
     ]
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "# change percentage to False if you want to plot the absolute values\n",
    "Percentage = True\n",
    "plt.close('all')\n",
    "plt.figure()\n",
    "ax = plt.axes()  \n",
    "\n",
    "groups = df.groupby(\"Geology\")\n",
    "\n",
    "diff_indivs = []\n",
    "Th_cali_1PWs = []\n",
    "diff_1PWs = []\n",
    "\n",
    "labels = ['R1 (23)', 'R2 (26)','R3 (27)', 'R4 (12)']\n",
    "markers = ['>', '+', (5,1), 'o']\n",
    "\n",
    "## first plot the residuals of the individual groups\n",
    "i = 0\n",
    "for label, (id, group), marker in zip(labels, groups, markers):\n",
    "    print(\"*\"*50, id)\n",
    "    print('n = ', len(group))\n",
    "    x = group[\"h\"]\n",
    "    y = group[\"f0_ip\"]\n",
    "    z = group[\"error\"]\n",
    "\n",
    "    Th_cali_indiv = a_values[i]*np.power(y,b_values[i])\n",
    "    \n",
    "    #Thickness for several PW\n",
    "    diff_indiv = x - Th_cali_indiv\n",
    "    diff_indivs.append(diff_indiv)\n",
    "    \n",
    "    #Thickness for 1 PW\n",
    "    diff_1PWs.append(x - (a*np.power(y,b)))\n",
    "    \n",
    "    #PLOT THE DIFFERENCE in %\n",
    "    if Percentage:\n",
    "        plt.scatter(diff_indiv/x*100,x, label=label, color = colors[i], edgecolor = 'black', zorder = 3, marker = marker, s = 60) \n",
    "    #PLOT THE ABSOLUTE DIFFERENCE\n",
    "    else:\n",
    "        plt.scatter(x,diff_indiv, label=label, color = colors[i],edgecolor = 'black', zorder = 3)\n",
    "\n",
    "    i+=1\n",
    "\n",
    "## plot residuals of the regional regression R'\n",
    "a_Rprime = a_values[4]\n",
    "b_Rprime = b_values[4]\n",
    "Th_cali_1PW = a_Rprime*np.power(df[\"f0_ip\"],b_Rprime)\n",
    "diff_1PW = df[\"h\"] - Th_cali_1PW\n",
    "\n",
    "if Percentage:\n",
    "    plt.scatter(diff_1PW/df[\"h\"]*100, df[\"h\"], c='white',edgecolor = 'black', \n",
    "                label=\"all, n = %s\"%len(diff_1PW),zorder = 3)\n",
    "    plt.xlabel('% difference of predicted h with true h') #PLOT THE DIFFERENCE in %\n",
    "else:\n",
    "    plt.scatter(df[\"h\"],diff_1PW, c='red',edgecolor = 'black',label=\"all, n = %s\"%len(diff_all), zorder = 3)\n",
    "    plt.xlabel('$h_{ True}$ - $h_{ modelled}$', fontsize = 11) #PLOT THE ABSOLUTE DIFFERENCE\n",
    "\n",
    "## adjust plot\n",
    "plt.legend(loc='upper left',fontsize=9, ncol = 1)\n",
    "plt.ylim(0,200)\n",
    "plt.ylabel(\"Sediment Thickness (m)\")\n",
    "plt.axvline(0,500,0, ls='--', c='black')\n",
    "plt.xlim(-60,60)\n",
    "t = plt.text(40, 105.5, 'Thickness \\n underestimation', fontsize = 11, ha = 'center')\n",
    "t2 = plt.text(-40,105.5, 'Thickness \\n overestimation', fontsize = 11, ha = 'center')\n",
    "t.set_bbox(dict(facecolor='white', edgecolor='white'))\n",
    "t2.set_bbox(dict(facecolor='white', edgecolor='white'))\n",
    "\n",
    "plt.grid(zorder = -200)\n",
    "plt.savefig(\"Fig. 7A - residual computation.png\", dpi=300)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fig. 6B residual histogram: compare if 1 powerlaw relation or several powerlaws are better"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 PR better: 39\n",
      "Geological PR better: 49\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Program Files (x86)\\Anaconda\\lib\\site-packages\\matplotlib\\axes\\_axes.py:6521: MatplotlibDeprecationWarning: \n",
      "The 'normed' kwarg was deprecated in Matplotlib 2.1 and will be removed in 3.1. Use 'density' instead.\n",
      "  alternative=\"'density'\", removal=\"3.1\")\n",
      "C:\\Program Files (x86)\\Anaconda\\lib\\site-packages\\matplotlib\\figure.py:98: MatplotlibDeprecationWarning: \n",
      "Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
      "  \"Adding an axes using the same arguments as a previous axes \"\n"
     ]
    }
   ],
   "source": [
    "import pylab as P\n",
    "\n",
    "plt.close('all')\n",
    "## difference between 1 PW residuals or geologically-dependant residuals\n",
    "all_indiv =  np.absolute(np.array(diff_1PWs)) - np.absolute(np.array(diff_indivs))\n",
    "onePW = []\n",
    "allPW = []\n",
    "onePW_id = []\n",
    "allPW_id = []\n",
    "\n",
    "p = 0\n",
    "for i,(id, group),label in zip(all_indiv, groups,labels):\n",
    "    for j in i:\n",
    "        if j < 0:\n",
    "            onePW_id.append(j)\n",
    "            onePW.append(j)\n",
    "        else:\n",
    "            allPW_id.append(j)\n",
    "            allPW.append(j)\n",
    "    ########1 PW better\n",
    "    t = plt.text(-9,15-p/1.2,\"%s (%s)\"%(labels[p], len(onePW_id)))\n",
    "    t.set_bbox(dict(facecolor='white', edgecolor='white'))\n",
    "    ########Geol PW better\n",
    "    t = plt.text(6,15-p/1.2,\"%s (%s)\"%(labels[p], len(allPW_id)))\n",
    "    t.set_bbox(dict(facecolor='white', edgecolor='white'))\n",
    "    onePW_id = []\n",
    "    allPW_id = []\n",
    "\n",
    "    p = p+1\n",
    "\n",
    "print('1 PR better:', len(onePW))\n",
    "print('Geological PR better:',len(allPW))\n",
    "bins = np.arange(-16,16,0.5)      #define the bin width of the histogram\n",
    "\n",
    "n, bins, patches = P.hist(all_indiv, bins, normed=0, histtype='bar', \n",
    "                          edgecolor = 'black', color = ['lightblue', 'grey', 'yellow','lightpink'], \n",
    "                          rwidth=1, orientation = 'vertical', zorder = 2, stacked=1)\n",
    "\n",
    "plt.xlabel('ABS($h_{True}$ - $h_{1 eq.})$  -  ABS($h_{ True}$ - $h_{geol. eqs.})$')\n",
    "plt.ylabel('nr')\n",
    "plt.axvline(0,0,100, c='black', zorder = 2)\n",
    "\n",
    "ax = plt.axes() \n",
    "ax.yaxis.grid(ls = '--',zorder = -3)\n",
    "plt.xticks(np.arange(-14, 16, 2))\n",
    "plt.ylim(0,16)\n",
    "plt.xlim(-14,14)\n",
    "plt.title(\"   1 PR better                     Geological PR better\")\n",
    "\n",
    "plt.savefig(\"Fig 7B - comparing residuals.png\", dpi=300)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fig. 7: Shear wave velocity versus Sediment thickness plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "************************************************** ['KoMo', 'KoSm']\n",
      "************************************************** ['KoMo_Al', 'KoSm_Al', 'Br_Al']\n",
      "************************************************** ['Mal', 'Ld', 'Br', 'Shh']\n",
      "************************************************** ['Pal_Al', 'Hn_Al']\n"
     ]
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "i = 0\n",
    "plt.figure()\n",
    "plt.grid(zorder = -5)\n",
    "labels = ['R1', 'R2','R3', 'R4']\n",
    "for label,(id, group) in zip(labels,groups):\n",
    "    print(\"*\"*50, id)\n",
    "    f0 = group[\"f0_ip\"]\n",
    "    h = group[\"h\"]\n",
    "    Vs = 4*f0*h\n",
    "    plt.scatter(h,Vs, label = \"%s (%s)\"%(labels[i], len(h)), s=30, edgecolor = 'black', linewidth='1', c=colors[i], zorder = 3)\n",
    "    y_errmax = 4*group[\"f0 min\"]*h - Vs\n",
    "    y_errmin = Vs - (4*group[\"f0 max\"]*h)\n",
    "    plt.errorbar(h,Vs,xerr=None,yerr=[y_errmin, y_errmax], ls='none', capsize=2, c = 'black',zorder = 2)\n",
    "    i+=1\n",
    "\n",
    "def PW(a,b,color, f0_range_min,f0_range_max, lw):\n",
    "    f0_int = np.arange(f0_range_min,f0_range_max,0.1)  \n",
    "    h_int = a*np.power(f0_int,b)\n",
    "    Vs_int = h_int * f0_int * 4  \n",
    "    plt.plot(h_int, Vs_int, c = color, ls='--', zorder = 2, linewidth=lw)\n",
    "\n",
    "#For all individual regressions\n",
    "for i in np.arange(0,4,1):\n",
    "    PW(a_values[i],b_values[i],colors[i], f0_range_min[i],f0_range_max[i], lw = 3)\n",
    "\n",
    "#For one regression\n",
    "a_Rprime = a_values[4]\n",
    "b_Rprime = b_values[4]\n",
    "PW(a_Rprime,b_Rprime,'black',np.min(f0_range_min),np.max(f0_range_max), lw = 2)\n",
    "    \n",
    "plt.legend(frameon=True, ncol=1)\n",
    "plt.annotate(\"n = %s\"%len(df2),(1.1,5))\n",
    "plt.ylabel(\"Vs (m/s)\")\n",
    "plt.xlabel(\"Sediment Thickness (m)\")\n",
    "plt.xlim(0,180)\n",
    "plt.ylim(50,550)\n",
    "plt.yticks(np.arange(100, 600, 50))\n",
    "plt.savefig('Fig 8 - Vs versus thickness.jpg')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fig. 10A - H/V polarisation histogram: Plot the distribution of azimuthal directions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nr</th>\n",
       "      <th>Date</th>\n",
       "      <th>Name</th>\n",
       "      <th>Easting</th>\n",
       "      <th>Northing</th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "      <th>Z (DEM)</th>\n",
       "      <th>Gain</th>\n",
       "      <th>Ovmx</th>\n",
       "      <th>...</th>\n",
       "      <th>Th_all</th>\n",
       "      <th>Top_all</th>\n",
       "      <th>diff</th>\n",
       "      <th>borehole</th>\n",
       "      <th>A_max</th>\n",
       "      <th>max_freq</th>\n",
       "      <th>max_Azi</th>\n",
       "      <th>A_min</th>\n",
       "      <th>min_freq</th>\n",
       "      <th>min_Azi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>26/06/2017</td>\n",
       "      <td>A201</td>\n",
       "      <td>151025.0847</td>\n",
       "      <td>162193.0678</td>\n",
       "      <td>50.770229</td>\n",
       "      <td>4.383283</td>\n",
       "      <td>124.00</td>\n",
       "      <td>128</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>116.51</td>\n",
       "      <td>7.49</td>\n",
       "      <td>-0.79</td>\n",
       "      <td>124.0</td>\n",
       "      <td>9.94885</td>\n",
       "      <td>0.833221</td>\n",
       "      <td>30</td>\n",
       "      <td>9.28274</td>\n",
       "      <td>0.865017</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>26/06/2017</td>\n",
       "      <td>A202</td>\n",
       "      <td>151117.5959</td>\n",
       "      <td>162679.6450</td>\n",
       "      <td>50.774603</td>\n",
       "      <td>4.384596</td>\n",
       "      <td>119.23</td>\n",
       "      <td>512</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>122.02</td>\n",
       "      <td>-2.79</td>\n",
       "      <td>-0.97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.38320</td>\n",
       "      <td>0.816373</td>\n",
       "      <td>10</td>\n",
       "      <td>9.58308</td>\n",
       "      <td>0.847526</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>26/06/2017</td>\n",
       "      <td>A203</td>\n",
       "      <td>151635.6421</td>\n",
       "      <td>162976.4595</td>\n",
       "      <td>50.777270</td>\n",
       "      <td>4.391942</td>\n",
       "      <td>126.87</td>\n",
       "      <td>512</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>130.67</td>\n",
       "      <td>-3.80</td>\n",
       "      <td>-1.26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.55490</td>\n",
       "      <td>0.783692</td>\n",
       "      <td>20</td>\n",
       "      <td>15.35570</td>\n",
       "      <td>0.799865</td>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>26/06/2017</td>\n",
       "      <td>A204</td>\n",
       "      <td>151303.5648</td>\n",
       "      <td>162518.1713</td>\n",
       "      <td>50.773151</td>\n",
       "      <td>4.387232</td>\n",
       "      <td>122.58</td>\n",
       "      <td>256</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>119.57</td>\n",
       "      <td>3.01</td>\n",
       "      <td>-0.89</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.43310</td>\n",
       "      <td>0.816373</td>\n",
       "      <td>20</td>\n",
       "      <td>10.44390</td>\n",
       "      <td>0.862077</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>26/06/2017</td>\n",
       "      <td>A205</td>\n",
       "      <td>150878.9403</td>\n",
       "      <td>162106.6076</td>\n",
       "      <td>50.769452</td>\n",
       "      <td>4.381211</td>\n",
       "      <td>127.53</td>\n",
       "      <td>512</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>114.92</td>\n",
       "      <td>12.61</td>\n",
       "      <td>-0.74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.56450</td>\n",
       "      <td>0.850416</td>\n",
       "      <td>30</td>\n",
       "      <td>9.84464</td>\n",
       "      <td>0.865017</td>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   nr        Date  Name      Easting     Northing        lat       lon  \\\n",
       "0   0  26/06/2017  A201  151025.0847  162193.0678  50.770229  4.383283   \n",
       "1   1  26/06/2017  A202  151117.5959  162679.6450  50.774603  4.384596   \n",
       "2   2  26/06/2017  A203  151635.6421  162976.4595  50.777270  4.391942   \n",
       "3   3  26/06/2017  A204  151303.5648  162518.1713  50.773151  4.387232   \n",
       "4   4  26/06/2017  A205  150878.9403  162106.6076  50.769452  4.381211   \n",
       "\n",
       "   Z (DEM)  Gain  Ovmx  ...  Th_all  Top_all  diff borehole     A_max  \\\n",
       "0   124.00   128     5  ...  116.51     7.49 -0.79    124.0   9.94885   \n",
       "1   119.23   512     5  ...  122.02    -2.79 -0.97      NaN  11.38320   \n",
       "2   126.87   512     5  ...  130.67    -3.80 -1.26      NaN  18.55490   \n",
       "3   122.58   256     5  ...  119.57     3.01 -0.89      NaN  11.43310   \n",
       "4   127.53   512     5  ...  114.92    12.61 -0.74      NaN  10.56450   \n",
       "\n",
       "   max_freq  max_Azi     A_min  min_freq  min_Azi  \n",
       "0  0.833221       30   9.28274  0.865017       90  \n",
       "1  0.816373       10   9.58308  0.847526      100  \n",
       "2  0.783692       20  15.35570  0.799865      110  \n",
       "3  0.816373       20  10.44390  0.862077      140  \n",
       "4  0.850416       30   9.84464  0.865017      150  \n",
       "\n",
       "[5 rows x 39 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df = pd.read_csv('HVSR rotation.csv', delimiter=',', skiprows=0, engine = 'python')\n",
    "df = pd.read_csv('VanNotenetal_JOSE_S2 - Survey HVSR analysis.csv', delimiter=',', skiprows=33, engine = 'python')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "az = df['max_Azi']\n",
    "az360=az+180\n",
    "azs = []\n",
    "azs.append(az)\n",
    "azs.append(az360)\n",
    "\n",
    "radians = np.deg2rad(azs)\n",
    "\n",
    "bin_size = 10\n",
    "a , b = np.histogram(azs, bins=np.arange(0, 360+bin_size, bin_size))\n",
    "centers = np.deg2rad(np.ediff1d(b)//2 + b[:-1])\n",
    "\n",
    "fig = plt.figure(figsize=(8,6))\n",
    "ax = fig.add_subplot(111, projection='polar')\n",
    "ax.set_rlabel_position(90)\n",
    "ax.bar(centers, a, width=np.deg2rad(bin_size), bottom=0.0, color='grey', edgecolor='black', zorder = 3)\n",
    "ax.set_theta_zero_location(\"N\")\n",
    "ax.set_theta_direction(-1)\n",
    "ax.set_xticks(np.pi/180. * np.linspace(0,  360, 18, endpoint=False))\n",
    "ax.tick_params(axis='both', which='major', labelsize=14)\n",
    "\n",
    "plt.title(\"H/V Polarisation histogram\", fontsize=14)\n",
    "plt.savefig('Polarisation histogram.png', DPI=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}