Plots.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Make various plots that I am gonna need\n",
    "\n",
    "These are plots for talks and demos, and also just debugging and validation. \n",
    "\n",
    "There might also be some random plots in here as I work out things."
   ]
  },
  {
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"pdf\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "db731bc74ed44757bf4a279e042e6199",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=0.0, max=49.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.animation as animation\n",
    "import matplotlib.cm as cm\n",
    "import pandas as pd\n",
    "from utils.utilities import mk_heatmap\n",
    "from utils.strings import DATE\n",
    "from tqdm.autonotebook import tqdm\n",
    "\n",
    "inspecs = pd.read_csv('./data/inspecs_heat_scores.csv', parse_dates=[DATE])\n",
    "\n",
    "# break out the month and year so we can group on them\n",
    "inspecs['wk'] = inspecs[DATE].dt.week\n",
    "inspecs['mon'] = inspecs[DATE].dt.month\n",
    "inspecs['yr'] = inspecs[DATE].dt.year\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(10,10))\n",
    "\n",
    "grouped = inspecs.groupby(['yr', 'mon'])\n",
    "\n",
    "# work out the extent for all the data\n",
    "img, extent_big, xedges, yedges = mk_heatmap(inspecs.longitude.values,\n",
    "                                         inspecs.latitude.values, s=2, bins=1000)\n",
    "\n",
    "\n",
    "# # ims is a list of lists, each row is a list of artists to draw in the\n",
    "# # current frame; here we are just animating one artist, the image, in\n",
    "# # each frame\n",
    "ims = []\n",
    "i=0\n",
    "for (yr, mon), group in tqdm(grouped, total=len(grouped)):\n",
    "    x = group.longitude.values\n",
    "    y = group.latitude.values\n",
    "    img, _, _, _ = mk_heatmap(x, y, s=2, bins=[xedges, yedges])\n",
    "    im = plt.imshow(img, extent=extent_big, origin='lower', cmap=cm.PuRd, animated=True)\n",
    "    plt.axis('off')\n",
    "    ims.append([im])\n",
    " \n",
    "    \n",
    "ani = animation.ArtistAnimation(fig, ims, interval=500, blit=True,\n",
    "                                repeat_delay=10)\n",
    "\n",
    "ani.save('animation.gif', writer='imagemagick')\n",
    "# ani.save('dynamic_images.gif')\n",
    "\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
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    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
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