Cantera_Tools_Tutorial.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cantera Tools Tutorial"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## USER INPUT: File Paths"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "chemkin_file_path = './chem.inp'\n",
    "species_dicionary_path = './species_dictionary.txt'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Next, we load the data from the chemkin files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from rmgpy.chemkin import loadChemkinFile\n",
    "\n",
    "species_list, reaction_list = loadChemkinFile(chemkin_file_path, species_dicionary_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## USER INPUT: Associate Common Names with Smile Strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from CanteraTools import *\n",
    "from rmgpy.species import Species\n",
    "\n",
    "smiles_dictionary = {'PDD':'CCCCCCCCCCCCc1ccccc1',\n",
    "                     'toluene':'Cc1ccccc1',\n",
    "                     'ethylbenzene':'CCc1ccccc1', \n",
    "                     'propylbenzene':'CCCc1ccccc1',\n",
    "                     'butylbenzene':'CCCCc1ccccc1', \n",
    "                     'pentylbenzene':'CCCCCc1ccccc1',\n",
    "                     'undecane':'CCCCCCCCCCC',\n",
    "                     'decane':'CCCCCCCCCC',\n",
    "                     'ethane':'CC',\n",
    "                     'methane':'C',\n",
    "                     'hexane':'CCCCCC',\n",
    "                     'heptane':'CCCCCCC',\n",
    "                     'octane':'CCCCCCCC',\n",
    "                     'nonane':'CCCCCCCCC',\n",
    "                     'styrene':'C=CC1C=CC=CC=1',\n",
    "                     'butane': 'CCCC',\n",
    "                     'pentane': 'CCCCC',\n",
    "                     'methylcyclopentane': 'CC1CCCC1',\n",
    "                     'benzene': 'C1=CC=CC=C1',\n",
    "                     'methyl-cyclohexane': 'CC1CCCCC1',\n",
    "                     'ethyl-cyclohexane': 'CCC1CCCCC1',\n",
    "                     '2-methylpropylbenzene': 'CC(C)CC1C=CC=CC=1',\n",
    "                     'napthalene': 'C1=CC=C2C=CC=CC2=C1',\n",
    "                     'hexylbenzene': 'CCCCCCC1C=CC=CC=1',\n",
    "                     'heptylbenzene': 'CCCCCCCC1C=CC=CC=1',\n",
    "                     'octylbenzene': 'CCCCCCCCC1C=CC=CC=1',\n",
    "                     'nonylbenzene': 'CCCCCCCCCC1C=CC=CC=1',\n",
    "                     '1,3-diphenylpropane': 'C1=CC=C(C=C1)CCCC1C=CC=CC=1',\n",
    "                     'decylbenzene': 'CCCCCCCCCCC1C=CC=CC=1',\n",
    "                     '1-butyloctylbenzene': 'CCCCCCCC(CCCC)C1C=CC=CC=1',\n",
    "                     '1-propylnonylbenzene': 'CCCCCCCCC(CCC)C1C=CC=CC=1',\n",
    "                     '1-ethyldecylbenzene': 'CCCCCCCCCC(CC)C1C=CC=CC=1',\n",
    "                     'undecylbenzene': 'CCCCCCCCCCCC1C=CC=CC=1',\n",
    "                     '1-methylundecylbenzene': 'CCCCCCCCCCC(C)C1C=CC=CC=1',\n",
    "                     '2,3-dimethyldecylbenzene': 'CCCCCCCC(C)C(C)CC1C=CC=CC=1'\n",
    "                     }"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## USER INPUT: Initial Mole Fractions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mol_fracs = {'PDD': 0.254956, 'toluene': 0.232564, 'undecane': 0.51248}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## USER INPUT: Conditions for Cantera Job"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wrote CTI mechanism file to '/home/mark/Documents/Cantera_Tools/chem.cti'.\n",
      "Mechanism contains 260 species and 10554 reactions.\n",
      "WARNING: 'ReactorNet::step(t)' is deprecated. The argument to this function is deprecated and will be removed after Cantera 2.3.\n"
     ]
    }
   ],
   "source": [
    "all_data = run_cantera_job(smiles_dictionary, \n",
    "                           mol_fracs,\n",
    "                           239, # Time\n",
    "                           350.0, # Temperature\n",
    "                           300.0, # Pressure\n",
    "                           p_units='bar',\n",
    "                           temp_units='C',\n",
    "                           time_units='h',\n",
    "                           chemkin_file=chemkin_file_path,\n",
    "                           species_dictionary_file=species_dicionary_path,\n",
    "                           species_list = species_list,\n",
    "                           reaction_list = reaction_list,\n",
    "                           )\n",
    "all_data = change_cantera_data_units(all_data, comp_units='moles_per_mass', time_units='h') # Changes the units in the returned 'all_data' object\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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       "             * 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 overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "concentration_profile_plot(all_data, ['PDD','toluene','undecane'], logscale=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "concentration_conversion_plot(all_data, ['hexane','heptane','octane','decane','ethylbenzene', 'butylbenzene'],\n",
    "                              'PDD',\n",
    "                              logscale=True,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}