REopt API CHP Benchmarking Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# REopt API Benchmarking of CHP+ Additions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import copy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Read in benchmarking data to Pandas DataFrams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "bench_5 = pd.read_csv(\"results_FivePercentGap.csv\", index_col=\"file\")\n",
    "bench_8 = pd.read_csv(\"results_EightPercentGap.csv\", index_col=\"file\")\n",
    "bench_const = pd.read_csv(\"results_FivePctGapConst.csv\", index_col=\"file\")\n",
    "bench_max = pd.read_csv(\"results_FivePctGap400maxkw.csv\", index_col=\"file\")\n",
    "bench_gap = pd.read_csv(\"results_FivePctGapBothTESReportGap.csv\", index_col=\"file\")\n",
    "bench_const4 = pd.read_csv(\"results_FivePctFourItersConstFull.csv\", index_col=\"file\")\n",
    "# Fixed ColdTES evaluation because above runs did not have a cooling load\n",
    "bench_const3pctfixcool = pd.read_csv(\"results_ThreePctConstFullOneIterFixedCool.csv\", index_col=\"file\")\n",
    "bench_monoconst3pct = pd.read_csv(\"results_ThreePctMonolithConstFullOneIter.csv\", index_col=\"file\")\n",
    "bench_monoconstHalfpct = pd.read_csv(\"results_HalfPctMonolithConstFullOneIter.csv\", index_col=\"file\")\n",
    "bench_minsizes3Pct1PctSub = pd.read_csv(\"results_ThreePctMinSizes1PctSubGapConst.csv\", index_col=\"file\")\n",
    "bench_const1pct900secs = pd.read_csv(\"results_OnePct900SecsConst.csv\", index_col=\"file\")\n",
    "bench_mono1pct900secsconst = pd.read_csv(\"results_MonoOnePct900SecsConst.csv\", index_col=\"file\")\n",
    "bench_mono5pct900secs = pd.read_csv(\"results_MonoFivePct900Secs.csv\", index_col=\"file\")\n",
    "bench_minsizes3pctconst = pd.read_csv(\"results_DecompMinSizesThreePct900SecsConst.csv\", index_col=\"file\")\n",
    "bench_monocostcurve1pctconst = pd.read_csv(\"results_MonoOnePctCostCurve900SecsConst.csv\", index_col=\"file\")\n",
    "bench_decompcostcurve3pctconst = pd.read_csv(\"results_DecompThreePctCostCurve900SecsConst.csv\", index_col=\"file\")\n",
    "bench_private5pctconstc110p = pd.read_csv(\"results_PrivateFivePct420SecsC110PConst.csv\", index_col=\"file\")\n",
    "bench_minsizesupdated3pctconst = pd.read_csv(\"results_DecompUpdated2MinSizesThreePct900SecsConst.csv\", index_col=\"file\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "/* 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",
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       "    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",
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       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
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       "\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",
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       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
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       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
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       "\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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scenario = \"mono5pct900secs\"\n",
    "for s in [scenario]:\n",
    "    bench = copy.deepcopy(eval(\"bench_\"+s))\n",
    "    tech_configs = ['chp', 'chp_pv_bess', 'chp_pv_bess_coldtes', 'chp_pv_bess_hottes', \n",
    "                'chp_hottes', 'chp_coldtes', 'chp_pv_bess_coldtes_hottes']\n",
    "    if 'pv_bess' in list(bench[\"tech_choice\"]):\n",
    "        tech_configs = ['pv_bess'] + tech_configs\n",
    "    by_tech = {t: bench[bench[\"tech_choice\"] == t] for t in tech_configs}\n",
    "    num_cases = len(bench)\n",
    "    avg_time = {t: np.sum(by_tech[t]['reopt_seconds'].dropna()) / len(by_tech[t]['lcc'].dropna()) for t in tech_configs}\n",
    "    if 'gap' in list(bench.columns):\n",
    "        avg_gap = {t: np.sum(by_tech[t]['gap'].dropna()) / len(by_tech[t]['lcc'].dropna()) for t in tech_configs}\n",
    "    else:\n",
    "        avg_gap = {t: 0.0 for t in tech_configs}\n",
    "    avg_chp_kw = {t: np.sum(by_tech[t]['chp_kw'].dropna()) / len(by_tech[t]['lcc'].dropna()) for t in tech_configs}\n",
    "    avg_npv = {t: np.sum(by_tech[t]['npv'].dropna()) / len(by_tech[t]['lcc'].dropna()) for t in tech_configs}\n",
    "    plt.bar(by_tech.keys(), [len(by_tech[t]['lcc'].dropna())/len(by_tech[t]['lcc']) for t in by_tech.keys()])\n",
    "    # Show average time for the ones that solved\n",
    "    for t in tech_configs:\n",
    "        plt.text(t, len(by_tech[t]['lcc'].dropna())/len(by_tech[t]['lcc']), str(int(avg_time[t])) + \"sec\", fontdict=None)\n",
    "        plt.text(t, len(by_tech[t]['lcc'].dropna())/len(by_tech[t]['lcc'])-0.05, str(round(avg_gap[t],3)) + \"gap\", fontdict=None)\n",
    "        plt.text(t, len(by_tech[t]['lcc'].dropna())/len(by_tech[t]['lcc'])-0.1, str(round(avg_chp_kw[t],0)) + \"kw_CHP\", fontdict=None)\n",
    "        plt.text(t, len(by_tech[t]['lcc'].dropna())/len(by_tech[t]['lcc'])-0.15, \"$\" + str(round(avg_npv[t],0)) + \"npv\", fontdict=None)\n",
    "    plt.title(scenario + \" Fraction of scenarios converged by tech config\")\n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of negative NPV solutions =  19\n"
     ]
    }
   ],
   "source": [
    "neg_npv = bench[bench[\"npv\"] < -0.01]\n",
    "plt.scatter(range(len(bench[\"npv\"].index)), bench[\"npv\"])\n",
    "plt.title(scenario + \" NPV for all scenarios\")\n",
    "plt.ylabel(\"NPV ($)\")\n",
    "plt.xlabel(\"Benchmark scenario/run\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "#print(\"Calc'd gap for negative NPV chp_pv_bess = \", neg_npv[neg_npv[\"tech_choice\"]==\"chp_pv_bess\"][\"npv\"]/neg_npv[neg_npv[\"tech_choice\"]==\"chp_pv_bess\"][\"lcc\"])\n",
    "#print(\"Model gap output from decomp [LCC_objval - LCC_lb] = \", neg_npv[neg_npv[\"tech_choice\"]==\"chp_pv_bess\"][\"gap\"])\n",
    "print(\"Number of negative NPV solutions = \", len(neg_npv))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compare results across API versions and settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load in all API results into a dictionary of dataframes\n",
    "bench_names = ['monoconst3pct', 'mono1pct900secsconst', 'monoconstHalfpct', 'monocostcurve1pctconst',  # Constant CHP efficiencies\n",
    "               'gap', 'mono5pct900secs',  # Variable CHP efficiencies\n",
    "               'const3pctfixcool', 'const1pct900secs', 'decompcostcurve3pctconst',  # Decomposition, const effic\n",
    "               'private5pctconstc110p'] # Private, const effic\n",
    "bench_var_const = ['mono1pct900secsconst', 'mono5pct900secs']\n",
    "bench_all = {api: copy.deepcopy(eval(\"bench_\"+api)) for api in bench_names}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pick the metrics to extract from each API for all scenarios\n",
    "# Format --> e.g. {\"npv\": df of NPV for all APIs for all scenarios, \"chp_kw\": def of chp_kw for all API's for all scenarios}\n",
    "# TODO check if this is doing some unintended filtering of the data (e.g. no pv_bess)\n",
    "metric_list = [\"npv\", \"chp_kw\", \"pv_kw\"]\n",
    "agg_data = {metric: pd.DataFrame(index=bench_all['mono1pct900secsconst'].index) for metric in metric_list}\n",
    "for metric in metric_list:\n",
    "    for bench_name, bench_data_df in bench_all.items():\n",
    "        agg_data[metric] = agg_data[metric].join(pd.Series(bench_data_df[metric], name=bench_name))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Further filter on API's to compare against (values expected to be same if life was perfect), e.g. same set of inputs but different API settings or versions\n",
    "tech_config = \"chp_pv_bess\"\n",
    "chp_effic = \"variable\"\n",
    "bench_const = [name for name in bench_names if \"const\" in name if \"curve\" not in name]\n",
    "bench_var = [name for name in bench_names if \"const\" not in name if \"curve\" not in name]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# NPV\n",
    "const_npv = copy.deepcopy(agg_data[\"npv\"].loc[:,bench_const])\n",
    "const_npv = const_npv.filter(regex=tech_config+\"_San\", axis='index')\n",
    "const_npv_positive = const_npv[const_npv > 0]#.dropna(how='all')\n",
    "var_const_npv = copy.deepcopy(agg_data[\"npv\"].loc[:,bench_var_const])\n",
    "# var_const_npv_chp = var_const_npv.filter(regex=\"chp_San\", axis='index')\n",
    "# var_const_npv_chp_pv_bess = var_const_npv.filter(regex=\"chp_pv_bess_San\", axis='index')\n",
    "# var_const_npv = pd.concat([var_const_npv_chp, var_const_npv_chp_pv_bess]) \n",
    "var_const_npv_positive = var_const_npv[var_const_npv > 0].dropna(how='all')\n",
    "var_effic_fixed_chp_size_1pct_npv = copy.deepcopy(var_effic_fixed_chp_size_1pct_summary_df[\"npv\"])\n",
    "\n",
    "# CHP size\n",
    "const_chp_kw = copy.deepcopy(agg_data[\"chp_kw\"].loc[:,bench_const])\n",
    "const_chp_kw = const_chp_kw.filter(regex=tech_config+\"_San\", axis='index')\n",
    "#const_chp_kw = const_chp_kw[const_chp_kw > 50000].dropna(how='all')\n",
    "var_const_chp_kw = copy.deepcopy(agg_data[\"chp_kw\"].loc[:,bench_var_const])\n",
    "var_const_chp_kw = var_const_chp_kw.filter(regex=tech_config+\"_San\", axis='index')\n",
    "\n",
    "# PV size\n",
    "const_pv_kw = copy.deepcopy(agg_data[\"pv_kw\"].loc[:,bench_const])\n",
    "const_pv_kw = const_pv_kw.filter(regex=tech_config+\"_San\", axis='index')\n",
    "var_const_pv_kw = copy.deepcopy(agg_data[\"pv_kw\"].loc[:,bench_var_const])\n",
    "var_const_pv_kw = var_const_pv_kw.filter(regex=tech_config+\"_San\", axis='index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mono1pct900secsconst</th>\n",
       "      <th>mono5pct900secs</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>file</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_9_0.json</th>\n",
       "      <td>2187026.0</td>\n",
       "      <td>1883752.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_13_0.json</th>\n",
       "      <td>6271728.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_5e7cc9135457a338417d5622_13_0.json</th>\n",
       "      <td>111236.0</td>\n",
       "      <td>111236.0</td>\n",
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       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5ec2a6945457a3e60d81625c_13_0.json</th>\n",
       "      <td>23121.0</td>\n",
       "      <td>23121.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pv_bess_SanFrancisco_Hospital_539f74f4ec4f024411ed0e5b__0.json</th>\n",
       "      <td>6116.0</td>\n",
       "      <td>6116.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_SanFrancisco_Hospital_539f6b62ec4f024411ec9bcb_13_0.json</th>\n",
       "      <td>14421.0</td>\n",
       "      <td>19742.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_539f6b62ec4f024411ec9bcb_9_0.json</th>\n",
       "      <td>166856.0</td>\n",
       "      <td>163655.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_9_0.json</th>\n",
       "      <td>3655662.0</td>\n",
       "      <td>3346203.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pv_bess_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0__0.json</th>\n",
       "      <td>2437043.0</td>\n",
       "      <td>2437043.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>7048228.0</td>\n",
       "      <td>6706279.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_13_0.json</th>\n",
       "      <td>3175583.0</td>\n",
       "      <td>2967001.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_SanFrancisco_Hospital_5e7cc9135457a338417d5622_13_0.json</th>\n",
       "      <td>24620.0</td>\n",
       "      <td>24620.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_539f74f4ec4f024411ed0e5b_9_0.json</th>\n",
       "      <td>103600.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5e7cc9135457a338417d5622_13_0.json</th>\n",
       "      <td>111236.0</td>\n",
       "      <td>111236.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_9_0.json</th>\n",
       "      <td>2035058.0</td>\n",
       "      <td>1503338.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5d094abf5457a3ba43474943_9_0.json</th>\n",
       "      <td>2365.0</td>\n",
       "      <td>2365.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_hottes_SanFrancisco_Hospital_539f6b62ec4f024411ec9bcb_9_0.json</th>\n",
       "      <td>2577.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5e7cc9135457a338417d5622_13_0.json</th>\n",
       "      <td>12936.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5e7cc9135457a338417d5622_9_0.json</th>\n",
       "      <td>111236.0</td>\n",
       "      <td>111236.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5ec2a6945457a3e60d81625c_9_0.json</th>\n",
       "      <td>23122.0</td>\n",
       "      <td>23122.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>7332864.0</td>\n",
       "      <td>6924114.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_hottes_SanFrancisco_Hospital_5ec2a6945457a3e60d81625c_13_0.json</th>\n",
       "      <td>184.0</td>\n",
       "      <td>184.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_539f74f4ec4f024411ed0e5b_13_0.json</th>\n",
       "      <td>120009.0</td>\n",
       "      <td>120009.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_539f6b62ec4f024411ec9bcb_13_0.json</th>\n",
       "      <td>143591.0</td>\n",
       "      <td>163654.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_5ec2a6945457a3e60d81625c_9_0.json</th>\n",
       "      <td>23122.0</td>\n",
       "      <td>23122.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5d094abf5457a3ba43474943_13_0.json</th>\n",
       "      <td>2365.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_5d094abf5457a3ba43474943_9_0.json</th>\n",
       "      <td>2365.0</td>\n",
       "      <td>2365.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>7418835.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_SanFrancisco_Hospital_5e7cc9135457a338417d5622_9_0.json</th>\n",
       "      <td>24620.0</td>\n",
       "      <td>24620.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pv_bess_SanFrancisco_Hospital_5cb742345457a31e119b6ec3__0.json</th>\n",
       "      <td>4763890.0</td>\n",
       "      <td>4763890.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_hottes_SanFrancisco_Hospital_539f6b62ec4f024411ec9bcb_9_0.json</th>\n",
       "      <td>24327.0</td>\n",
       "      <td>19743.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_539f6b62ec4f024411ec9bcb_9_0.json</th>\n",
       "      <td>97873.0</td>\n",
       "      <td>15354.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5ec2a6945457a3e60d81625c_9_0.json</th>\n",
       "      <td>23022.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_539f74f4ec4f024411ed0e5b_13_0.json</th>\n",
       "      <td>120009.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_hottes_SanFrancisco_Hospital_5e7cc9135457a338417d5622_9_0.json</th>\n",
       "      <td>24620.0</td>\n",
       "      <td>24620.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5ec2a6945457a3e60d81625c_13_0.json</th>\n",
       "      <td>23021.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_SanFrancisco_Hospital_5ec2a6945457a3e60d81625c_13_0.json</th>\n",
       "      <td>184.0</td>\n",
       "      <td>184.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pv_bess_SanFrancisco_Hospital_539f6b62ec4f024411ec9bcb__0.json</th>\n",
       "      <td>19742.0</td>\n",
       "      <td>19742.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_13_0.json</th>\n",
       "      <td>6577275.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>7165152.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_9_0.json</th>\n",
       "      <td>3931150.0</td>\n",
       "      <td>3661395.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_hottes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>5537600.0</td>\n",
       "      <td>5210780.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_13_0.json</th>\n",
       "      <td>3565447.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>5567413.0</td>\n",
       "      <td>5316669.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5d094abf5457a3ba43474943_13_0.json</th>\n",
       "      <td>2365.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5e7cc9135457a338417d5622_9_0.json</th>\n",
       "      <td>12936.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_hottes_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_13_0.json</th>\n",
       "      <td>3284902.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_SanFrancisco_Hospital_5ec2a6945457a3e60d81625c_9_0.json</th>\n",
       "      <td>185.0</td>\n",
       "      <td>185.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_539f74f4ec4f024411ed0e5b_9_0.json</th>\n",
       "      <td>119157.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_13_0.json</th>\n",
       "      <td>6393437.0</td>\n",
       "      <td>6166605.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_13_0.json</th>\n",
       "      <td>3487034.0</td>\n",
       "      <td>3241469.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_539f6b62ec4f024411ec9bcb_13_0.json</th>\n",
       "      <td>70345.0</td>\n",
       "      <td>14433.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pv_bess_SanFrancisco_Hospital_5ec2a6945457a3e60d81625c__0.json</th>\n",
       "      <td>184.0</td>\n",
       "      <td>184.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_13_0.json</th>\n",
       "      <td>933054.0</td>\n",
       "      <td>813684.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>5537600.0</td>\n",
       "      <td>4987776.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_9_0.json</th>\n",
       "      <td>4050378.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_hottes_SanFrancisco_Hospital_5e7cc9135457a338417d5622_13_0.json</th>\n",
       "      <td>24620.0</td>\n",
       "      <td>24620.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5d094abf5457a3ba43474943_9_0.json</th>\n",
       "      <td>2365.0</td>\n",
       "      <td>2365.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_5d094abf5457a3ba43474943_13_0.json</th>\n",
       "      <td>2365.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_hottes_SanFrancisco_Hospital_539f6b62ec4f024411ec9bcb_13_0.json</th>\n",
       "      <td>14411.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>72 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    mono1pct900secsconst  \\\n",
       "file                                                                       \n",
       "chp_coldtes_SanFrancisco_Hospital_5e1676e95457a...             2187026.0   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742...             6271728.0   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5e7cc...              111236.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...               23121.0   \n",
       "pv_bess_SanFrancisco_Hospital_539f74f4ec4f02441...                6116.0   \n",
       "chp_pv_bess_SanFrancisco_Hospital_539f6b62ec4f0...               14421.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...              166856.0   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a...             3655662.0   \n",
       "pv_bess_SanFrancisco_Hospital_5e1676e95457a3f87...             2437043.0   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5cb742345457a...             7048228.0   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a...             3175583.0   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e7cc9135457a...               24620.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...              103600.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...              111236.0   \n",
       "chp_SanFrancisco_Hospital_5e1676e95457a3f87673e...             2035058.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...                2365.0   \n",
       "chp_hottes_SanFrancisco_Hospital_539f6b62ec4f02...                2577.0   \n",
       "chp_coldtes_SanFrancisco_Hospital_5e7cc9135457a...               12936.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...              111236.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...               23122.0   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb74...             7332864.0   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5ec2a6...                 184.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...              120009.0   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_539f6...              143591.0   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5ec2a...               23122.0   \n",
       "chp_coldtes_SanFrancisco_Hospital_5d094abf5457a...                2365.0   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5d094...                2365.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...             7418835.0   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e7cc9135457a...               24620.0   \n",
       "pv_bess_SanFrancisco_Hospital_5cb742345457a31e1...             4763890.0   \n",
       "...                                                                  ...   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_539f6b...               24327.0   \n",
       "chp_coldtes_SanFrancisco_Hospital_539f6b62ec4f0...               97873.0   \n",
       "chp_coldtes_SanFrancisco_Hospital_5ec2a6945457a...               23022.0   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_539f7...              120009.0   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5e7cc9...               24620.0   \n",
       "chp_coldtes_SanFrancisco_Hospital_5ec2a6945457a...               23021.0   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5ec2a6945457a...                 184.0   \n",
       "pv_bess_SanFrancisco_Hospital_539f6b62ec4f02441...               19742.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...             6577275.0   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742...             7165152.0   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5e167...             3931150.0   \n",
       "chp_hottes_SanFrancisco_Hospital_5cb742345457a3...             5537600.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...             3565447.0   \n",
       "chp_coldtes_SanFrancisco_Hospital_5cb742345457a...             5567413.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...                2365.0   \n",
       "chp_coldtes_SanFrancisco_Hospital_5e7cc9135457a...               12936.0   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5e1676...             3284902.0   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5ec2a6945457a...                 185.0   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_539f7...              119157.0   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb74...             6393437.0   \n",
       "chp_coldtes_SanFrancisco_Hospital_5cb742345457a...             3487034.0   \n",
       "chp_coldtes_SanFrancisco_Hospital_539f6b62ec4f0...               70345.0   \n",
       "pv_bess_SanFrancisco_Hospital_5ec2a6945457a3e60...                 184.0   \n",
       "chp_SanFrancisco_Hospital_5e1676e95457a3f87673e...              933054.0   \n",
       "chp_SanFrancisco_Hospital_5cb742345457a31e119b6...             5537600.0   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...             4050378.0   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5e7cc9...               24620.0   \n",
       "chp_coldtes_SanFrancisco_Hospital_5d094abf5457a...                2365.0   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5d094...                2365.0   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_539f6b...               14411.0   \n",
       "\n",
       "                                                    mono5pct900secs  \n",
       "file                                                                 \n",
       "chp_coldtes_SanFrancisco_Hospital_5e1676e95457a...        1883752.0  \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742...              NaN  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5e7cc...         111236.0  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...          23121.0  \n",
       "pv_bess_SanFrancisco_Hospital_539f74f4ec4f02441...           6116.0  \n",
       "chp_pv_bess_SanFrancisco_Hospital_539f6b62ec4f0...          19742.0  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...         163655.0  \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a...        3346203.0  \n",
       "pv_bess_SanFrancisco_Hospital_5e1676e95457a3f87...        2437043.0  \n",
       "chp_pv_bess_SanFrancisco_Hospital_5cb742345457a...        6706279.0  \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a...        2967001.0  \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e7cc9135457a...          24620.0  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...              NaN  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...         111236.0  \n",
       "chp_SanFrancisco_Hospital_5e1676e95457a3f87673e...        1503338.0  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...           2365.0  \n",
       "chp_hottes_SanFrancisco_Hospital_539f6b62ec4f02...              NaN  \n",
       "chp_coldtes_SanFrancisco_Hospital_5e7cc9135457a...              NaN  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...         111236.0  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...          23122.0  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb74...        6924114.0  \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5ec2a6...            184.0  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...         120009.0  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_539f6...         163654.0  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5ec2a...          23122.0  \n",
       "chp_coldtes_SanFrancisco_Hospital_5d094abf5457a...              NaN  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5d094...           2365.0  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...              NaN  \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e7cc9135457a...          24620.0  \n",
       "pv_bess_SanFrancisco_Hospital_5cb742345457a31e1...        4763890.0  \n",
       "...                                                             ...  \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_539f6b...          19743.0  \n",
       "chp_coldtes_SanFrancisco_Hospital_539f6b62ec4f0...          15354.0  \n",
       "chp_coldtes_SanFrancisco_Hospital_5ec2a6945457a...              NaN  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_539f7...              NaN  \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5e7cc9...          24620.0  \n",
       "chp_coldtes_SanFrancisco_Hospital_5ec2a6945457a...              NaN  \n",
       "chp_pv_bess_SanFrancisco_Hospital_5ec2a6945457a...            184.0  \n",
       "pv_bess_SanFrancisco_Hospital_539f6b62ec4f02441...          19742.0  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...              NaN  \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742...              NaN  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5e167...        3661395.0  \n",
       "chp_hottes_SanFrancisco_Hospital_5cb742345457a3...        5210780.0  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...              NaN  \n",
       "chp_coldtes_SanFrancisco_Hospital_5cb742345457a...        5316669.0  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...              NaN  \n",
       "chp_coldtes_SanFrancisco_Hospital_5e7cc9135457a...              NaN  \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5e1676...              NaN  \n",
       "chp_pv_bess_SanFrancisco_Hospital_5ec2a6945457a...            185.0  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_539f7...              NaN  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb74...        6166605.0  \n",
       "chp_coldtes_SanFrancisco_Hospital_5cb742345457a...        3241469.0  \n",
       "chp_coldtes_SanFrancisco_Hospital_539f6b62ec4f0...          14433.0  \n",
       "pv_bess_SanFrancisco_Hospital_5ec2a6945457a3e60...            184.0  \n",
       "chp_SanFrancisco_Hospital_5e1676e95457a3f87673e...         813684.0  \n",
       "chp_SanFrancisco_Hospital_5cb742345457a31e119b6...        4987776.0  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...              NaN  \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5e7cc9...          24620.0  \n",
       "chp_coldtes_SanFrancisco_Hospital_5d094abf5457a...           2365.0  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5d094...              NaN  \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_539f6b...              NaN  \n",
       "\n",
       "[72 rows x 2 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "var_const_npv_positive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'chp_pv_bess_coldtes_5d094abf5457a3ba43474943_9_0'"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:8: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
      "of pandas will change to not sort by default.\n",
      "\n",
      "To accept the future behavior, pass 'sort=False'.\n",
      "\n",
      "To retain the current behavior and silence the warning, pass 'sort=True'.\n",
      "\n",
      "  \n"
     ]
    },
    {
     "data": {
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       "/* 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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1187\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:21: UserWarning: Tight layout not applied. The bottom and top margins cannot be made large enough to accommodate all axes decorations. \n"
     ]
    }
   ],
   "source": [
    "# Remove redundant text in scenario name to clean up the labels to compare differences\n",
    "rm_list = [\"SanFrancisco_Hospital_\", \".json\"]\n",
    "for rm in rm_list:\n",
    "    var_const_npv_positive.index = [name.replace(rm,\"\") for name in var_const_npv_positive.index.values]\n",
    "    # Fixed CHP size for var effic case with constant efficiency size\n",
    "    var_effic_fixed_chp_size_1pct_npv.index = [name.replace(rm,\"\") for name in var_effic_fixed_chp_size_1pct_npv.index.values]\n",
    "\n",
    "all_data_plot = pd.concat([var_const_npv_positive, var_effic_fixed_chp_size_1pct_npv], axis=1).dropna(how=\"all\")\n",
    "    \n",
    "markers = [\"o\",\"x\",\"*\",\"1\",\"^\",\"+\",\"*\"]\n",
    "legend_label = [\"ConstEfficMono1%GapTol\", \"VariableEfficMono5%GapTol\", \"FixedSizeVarEffic1%GapTol\"]\n",
    "for i, col in enumerate(all_data_plot.columns):\n",
    "    plt.plot(all_data_plot[col], label=legend_label[i], linewidth=0, marker=markers[i])\n",
    "# plt.plot(var_effic_fixed_chp_size_1pct_npv, label=legend_label[i+1], linewidth=0, marker=markers[i+1])\n",
    "plt.grid()\n",
    "plt.legend(loc=\"upper left\")\n",
    "plt.ylabel(\"NPV ($)\")\n",
    "plt.xlabel(\"Scenario\")\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.title(\"NPV for Constant Vs Variable CHP Efficiencies\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"898\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Remove redundant text in scenario name to clean up the labels to compare differences\n",
    "rm_list = [tech_config + \"_SanFrancisco_Hospital_\", \".json\"]\n",
    "for rm in rm_list:\n",
    "    const_npv_positive.index = [name.replace(rm,\"\") for name in const_npv_positive.index.values]\n",
    "\n",
    "markers = [\"o\",\"x\",\"1\",\"^\",\"+\",\"*\"]    \n",
    "for i, col in enumerate(const_npv_positive.columns):\n",
    "    plt.plot(const_npv_positive[col], label=col, linewidth=0, marker=markers[i])\n",
    "plt.grid()\n",
    "plt.legend(const_npv_positive.columns)\n",
    "plt.ylabel(\"NPV ($)\")\n",
    "plt.xlabel(\"Scenario\")\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.title(\"NPV for \" + tech_config + \" techs and \" + chp_effic + \" CHP effic\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / 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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"975\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for rm in rm_list:\n",
    "    const_chp_kw.index = [name.replace(rm,\"\") for name in const_chp_kw.index.values]\n",
    "\n",
    "#fig, ax = plt.subplots()\n",
    "for i, col in enumerate(const_chp_kw.columns):\n",
    "    plt.plot(const_chp_kw[col], label=col, linewidth=0, marker=markers[i])\n",
    "plt.grid()\n",
    "plt.legend(loc=\"center right\")\n",
    "plt.ylabel(\"Size (kW))\")\n",
    "plt.xlabel(\"Scenario\")\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.title(\"CHP size (kW) for \" + tech_config + \" techs and \" + chp_effic + \" CHP effic\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"958\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for rm in rm_list:\n",
    "    const_pv_kw.index = [name.replace(rm,\"\") for name in const_pv_kw.index.values]\n",
    "\n",
    "#fig, ax = plt.subplots()\n",
    "for i, col in enumerate(const_pv_kw.columns):\n",
    "    plt.plot(const_pv_kw[col], label=col, linewidth=0, marker=markers[i])\n",
    "plt.grid()\n",
    "plt.legend(loc=\"center right\")\n",
    "plt.ylabel(\"Size (kW))\")\n",
    "plt.xlabel(\"Scenario\")\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.title(\"pv size (kW) for \" + tech_config + \" techs\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import json\n",
    "file_dir = r\"C:\\Bill\\AMO_Local\\API Benchmarking\\Variable Vs Constant CHP Efficiencies\\All run data\"\n",
    "all_data = {}\n",
    "subfolders = [f.name for f in os.scandir(file_dir) if f.is_dir()]\n",
    "subfolders_path = [f.path for f in os.scandir(file_dir) if f.is_dir()]\n",
    "for i, sub_path in enumerate(subfolders_path):\n",
    "    all_data[subfolders[i]] = {}\n",
    "    for filename in os.listdir(sub_path):\n",
    "        if filename.endswith(\".csv\"):\n",
    "            all_data[subfolders[i]][\"summary\"] = pd.read_csv(os.path.join(sub_path, filename))\n",
    "        elif filename.endswith(\".json\"): \n",
    "            all_data[subfolders[i]][filename] = json.loads(eval(open(os.path.join(sub_path, filename)).read()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "chp_sized_data = {}\n",
    "chp_size_threshold = 101.0\n",
    "for i, case in enumerate(subfolders):\n",
    "    chp_sized_data[case] = {}\n",
    "    chp_sized_data[case][\"chp_sized\"] = all_data[case][\"summary\"][all_data[case][\"summary\"][\"chp_kw\"] >= chp_size_threshold] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['MonoFivePct900Secs', 'MonoOnePct900SecsConst'])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chp_sized_data.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# DONE ALREADY, DON'T REDO\n",
    "response_dict = {}\n",
    "for file in chp_sized_data['MonoOnePct900SecsConst'][\"chp_sized\"][\"file\"]:\n",
    "    response_dict[file] = all_data['MonoOnePct900SecsConst'][file]\n",
    "    with open(os.path.join(file_dir,\"mono_chp_sized_posts\", file), \"w\") as outfile:\n",
    "        json.dump(response_dict[file], outfile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# DON'T RUN, JUST FOR INFORMATION OF POST USED TO DO ANALYSIS\n",
    "chp_fixed_size_post = {}\n",
    "for name, post in chp_sized_response.items():\n",
    "    chp_fixed_size_post[name] = post['inputs'].copy()\n",
    "    chp_fixed_size_post[name][\"Scenario\"][\"timeout_seconds\"] = 300\n",
    "    chp_fixed_size_post[name][\"Scenario\"][\"optimality_tolerance_techs\"] = 0.01\n",
    "    chp_size = post[\"outputs\"][\"Scenario\"][\"Site\"][\"CHP\"][\"size_kw\"]\n",
    "    chp_fixed_size_post[name][\"Scenario\"][\"Site\"][\"CHP\"][\"min_kw\"] = chp_size\n",
    "    chp_fixed_size_post[name][\"Scenario\"][\"Site\"][\"CHP\"][\"max_kw\"] = chp_size\n",
    "    chp_fixed_size_post[name][\"Scenario\"][\"Site\"][\"CHP\"][\"elec_effic_full_load\"] = 0.32\n",
    "    chp_fixed_size_post[name][\"Scenario\"][\"Site\"][\"CHP\"][\"elec_effic_half_load\"] = 0.28845\n",
    "    chp_fixed_size_post[name][\"Scenario\"][\"Site\"][\"CHP\"][\"thermal_effic_full_load\"] = 0.4925\n",
    "    chp_fixed_size_post[name][\"Scenario\"][\"Site\"][\"CHP\"][\"thermal_effic_half_load\"] = 0.51573"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "results_dir = r\"C:\\Bill\\AMO_Local\\API Benchmarking\\Variable Vs Constant CHP Efficiencies\\var_effic_fixed_size_response\"\n",
    "var_effic_fixed_chp_size_1pct = {}\n",
    "for filename in os.listdir(results_dir):\n",
    "    var_effic_fixed_chp_size_1pct[filename] = json.loads(open(os.path.join(results_dir, filename)).read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "var_effic_fixed_chp_size_1pct_summary = {\"npv\": {},\"chp_fuel_mmbtu\": {}, \"chp_elec_kwh\": {}, \"chp_thermal_mmbtu\": {}}\n",
    "for case, data, in var_effic_fixed_chp_size_1pct.items():\n",
    "    var_effic_fixed_chp_size_1pct_summary[\"npv\"][case] = data[\"outputs\"][\"Scenario\"][\"Site\"][\"Financial\"][\"npv_us_dollars\"]\n",
    "    var_effic_fixed_chp_size_1pct_summary[\"chp_fuel_mmbtu\"][case] = data[\"outputs\"][\"Scenario\"][\"Site\"][\"CHP\"][\"year_one_fuel_used_mmbtu\"]\n",
    "    var_effic_fixed_chp_size_1pct_summary[\"chp_elec_kwh\"][case] = data[\"outputs\"][\"Scenario\"][\"Site\"][\"CHP\"][\"year_one_electric_energy_produced_kwh\"]\n",
    "    var_effic_fixed_chp_size_1pct_summary[\"chp_thermal_mmbtu\"][case] = data[\"outputs\"][\"Scenario\"][\"Site\"][\"CHP\"][\"year_one_thermal_energy_produced_mmbtu\"]\n",
    "list_cases = list(var_effic_fixed_chp_size_1pct_summary.keys())\n",
    "\n",
    "var_effic_fixed_chp_size_1pct_summary_df = pd.DataFrame(var_effic_fixed_chp_size_1pct_summary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>npv</th>\n",
       "      <th>chp_fuel_mmbtu</th>\n",
       "      <th>chp_elec_kwh</th>\n",
       "      <th>chp_thermal_mmbtu</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>chp_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_13_0.json</th>\n",
       "      <td>2996437.0</td>\n",
       "      <td>47536.750</td>\n",
       "      <td>4267237.903</td>\n",
       "      <td>6904.880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>5197150.0</td>\n",
       "      <td>80554.595</td>\n",
       "      <td>7223583.894</td>\n",
       "      <td>9793.853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_13_0.json</th>\n",
       "      <td>833119.0</td>\n",
       "      <td>20589.144</td>\n",
       "      <td>1813014.792</td>\n",
       "      <td>7855.591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_9_0.json</th>\n",
       "      <td>1649192.0</td>\n",
       "      <td>76460.429</td>\n",
       "      <td>6795391.949</td>\n",
       "      <td>9793.853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_13_0.json</th>\n",
       "      <td>3286880.0</td>\n",
       "      <td>40302.253</td>\n",
       "      <td>3651551.820</td>\n",
       "      <td>6902.103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>5334824.0</td>\n",
       "      <td>78976.462</td>\n",
       "      <td>7118239.177</td>\n",
       "      <td>9793.853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_13_0.json</th>\n",
       "      <td>1121928.0</td>\n",
       "      <td>23059.925</td>\n",
       "      <td>2050138.684</td>\n",
       "      <td>9451.746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_coldtes_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_9_0.json</th>\n",
       "      <td>1853625.0</td>\n",
       "      <td>77288.314</td>\n",
       "      <td>6931916.235</td>\n",
       "      <td>9793.853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_hottes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>5510471.0</td>\n",
       "      <td>77303.206</td>\n",
       "      <td>7223553.698</td>\n",
       "      <td>9793.853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_13_0.json</th>\n",
       "      <td>5985293.0</td>\n",
       "      <td>27252.674</td>\n",
       "      <td>2468072.728</td>\n",
       "      <td>8781.580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>6890852.0</td>\n",
       "      <td>44954.973</td>\n",
       "      <td>4047527.325</td>\n",
       "      <td>8793.470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_13_0.json</th>\n",
       "      <td>3058038.0</td>\n",
       "      <td>20051.578</td>\n",
       "      <td>1753679.565</td>\n",
       "      <td>8785.744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_9_0.json</th>\n",
       "      <td>3438110.0</td>\n",
       "      <td>33186.617</td>\n",
       "      <td>2922932.969</td>\n",
       "      <td>8969.664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_13_0.json</th>\n",
       "      <td>6294480.0</td>\n",
       "      <td>27037.475</td>\n",
       "      <td>2448951.777</td>\n",
       "      <td>8782.389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_13_0.json</th>\n",
       "      <td>3383485.0</td>\n",
       "      <td>19892.029</td>\n",
       "      <td>1757552.082</td>\n",
       "      <td>8809.510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_9_0.json</th>\n",
       "      <td>3766303.0</td>\n",
       "      <td>30246.654</td>\n",
       "      <td>2672388.795</td>\n",
       "      <td>8994.707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_13_0.json</th>\n",
       "      <td>6739542.0</td>\n",
       "      <td>20476.296</td>\n",
       "      <td>1940487.587</td>\n",
       "      <td>9823.420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_13_0.json</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_9_0.json</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_13_0.json</th>\n",
       "      <td>6202443.0</td>\n",
       "      <td>23773.125</td>\n",
       "      <td>2208052.146</td>\n",
       "      <td>9588.474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0.json</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chp_pv_bess_hottes_SanFrancisco_Hospital_5e1676e95457a3f87673e3b0_13_0.json</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                          npv  chp_fuel_mmbtu  \\\n",
       "chp_SanFrancisco_Hospital_5cb742345457a31e119b6...  2996437.0       47536.750   \n",
       "chp_SanFrancisco_Hospital_5cb742345457a31e119b6...  5197150.0       80554.595   \n",
       "chp_SanFrancisco_Hospital_5e1676e95457a3f87673e...   833119.0       20589.144   \n",
       "chp_SanFrancisco_Hospital_5e1676e95457a3f87673e...  1649192.0       76460.429   \n",
       "chp_coldtes_SanFrancisco_Hospital_5cb742345457a...  3286880.0       40302.253   \n",
       "chp_coldtes_SanFrancisco_Hospital_5cb742345457a...  5334824.0       78976.462   \n",
       "chp_coldtes_SanFrancisco_Hospital_5e1676e95457a...  1121928.0       23059.925   \n",
       "chp_coldtes_SanFrancisco_Hospital_5e1676e95457a...  1853625.0       77288.314   \n",
       "chp_hottes_SanFrancisco_Hospital_5cb742345457a3...  5510471.0       77303.206   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5cb742345457a...  5985293.0       27252.674   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5cb742345457a...  6890852.0       44954.973   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a...  3058038.0       20051.578   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a...  3438110.0       33186.617   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb74...  6294480.0       27037.475   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb74...        NaN             NaN   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5e167...  3383485.0       19892.029   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5e167...  3766303.0       30246.654   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...  6739542.0       20476.296   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...        NaN             NaN   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...        NaN             NaN   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...        NaN             NaN   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742...  6202443.0       23773.125   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742...        NaN             NaN   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5e1676...        NaN             NaN   \n",
       "\n",
       "                                                    chp_elec_kwh  \\\n",
       "chp_SanFrancisco_Hospital_5cb742345457a31e119b6...   4267237.903   \n",
       "chp_SanFrancisco_Hospital_5cb742345457a31e119b6...   7223583.894   \n",
       "chp_SanFrancisco_Hospital_5e1676e95457a3f87673e...   1813014.792   \n",
       "chp_SanFrancisco_Hospital_5e1676e95457a3f87673e...   6795391.949   \n",
       "chp_coldtes_SanFrancisco_Hospital_5cb742345457a...   3651551.820   \n",
       "chp_coldtes_SanFrancisco_Hospital_5cb742345457a...   7118239.177   \n",
       "chp_coldtes_SanFrancisco_Hospital_5e1676e95457a...   2050138.684   \n",
       "chp_coldtes_SanFrancisco_Hospital_5e1676e95457a...   6931916.235   \n",
       "chp_hottes_SanFrancisco_Hospital_5cb742345457a3...   7223553.698   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5cb742345457a...   2468072.728   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5cb742345457a...   4047527.325   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a...   1753679.565   \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a...   2922932.969   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb74...   2448951.777   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb74...           NaN   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5e167...   1757552.082   \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5e167...   2672388.795   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...   1940487.587   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...           NaN   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...           NaN   \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...           NaN   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742...   2208052.146   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742...           NaN   \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5e1676...           NaN   \n",
       "\n",
       "                                                    chp_thermal_mmbtu  \n",
       "chp_SanFrancisco_Hospital_5cb742345457a31e119b6...           6904.880  \n",
       "chp_SanFrancisco_Hospital_5cb742345457a31e119b6...           9793.853  \n",
       "chp_SanFrancisco_Hospital_5e1676e95457a3f87673e...           7855.591  \n",
       "chp_SanFrancisco_Hospital_5e1676e95457a3f87673e...           9793.853  \n",
       "chp_coldtes_SanFrancisco_Hospital_5cb742345457a...           6902.103  \n",
       "chp_coldtes_SanFrancisco_Hospital_5cb742345457a...           9793.853  \n",
       "chp_coldtes_SanFrancisco_Hospital_5e1676e95457a...           9451.746  \n",
       "chp_coldtes_SanFrancisco_Hospital_5e1676e95457a...           9793.853  \n",
       "chp_hottes_SanFrancisco_Hospital_5cb742345457a3...           9793.853  \n",
       "chp_pv_bess_SanFrancisco_Hospital_5cb742345457a...           8781.580  \n",
       "chp_pv_bess_SanFrancisco_Hospital_5cb742345457a...           8793.470  \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a...           8785.744  \n",
       "chp_pv_bess_SanFrancisco_Hospital_5e1676e95457a...           8969.664  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb74...           8782.389  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5cb74...                NaN  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5e167...           8809.510  \n",
       "chp_pv_bess_coldtes_SanFrancisco_Hospital_5e167...           8994.707  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...           9823.420  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...                NaN  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...                NaN  \n",
       "chp_pv_bess_coldtes_hottes_SanFrancisco_Hospita...                NaN  \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742...           9588.474  \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5cb742...                NaN  \n",
       "chp_pv_bess_hottes_SanFrancisco_Hospital_5e1676...                NaN  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "var_effic_fixed_chp_size_1pct_summary_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compare the inputs of two models/files/dictionaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load in .json files for two different models\n",
    "root_dir = r\"C:\\Bill\\Projects\\AMO\"\n",
    "compare = [\"PrivateFivePct420SecsC110PConst\", \"MonoOnePct900SecsConst\"]\n",
    "case = \"chp_pv_bess_coldtes_hottes_SanFrancisco_Hospital_5cb742345457a31e119b6ec3_9_0\"\n",
    "files = [os.path.join(root_dir, model, case) + \".json\" for model in compare]\n",
    "data = {}\n",
    "for i, file in enumerate(files):\n",
    "    try:\n",
    "        data[compare[i]] = json.loads(eval(open(file).read()))\n",
    "    except:\n",
    "        data[compare[i]] = json.loads(open(file).read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Must pip install deepdiff which recursively checks nested dictionary differences\n",
    "import deepdiff\n",
    "diff = {}\n",
    "for check in [\"CHP\", \"Financial\", \"HotTES\",\"ColdTES\",\"PV\",\"Storage\"]:\n",
    "    pre = \"['inputs']['Scenario']['Site']\"\n",
    "#     diff[check] = deepdiff.DeepDiff(eval(\"data[compare[0]]\"+pre+\"[\"+check+\"]\"), \n",
    "#                                     eval(\"data[compare[1]]\"+pre+\"[\"+check+\"]\"))\n",
    "    diff[check] = deepdiff.DeepDiff(data[compare[0]]['inputs']['Scenario']['Site'][check], \n",
    "                                    data[compare[1]]['inputs']['Scenario']['Site'][check])\n",
    "    print(check+ \" diff = \", diff[check])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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