thermo_debugging.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cantera as ct\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['figure.constrained_layout.use'] = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Thermo Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When loading a CTI file, sometimes you will encounter warnings about discontinuities in the thermodynamic data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species HCNH, discontinuity in cp/R detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  14.1403\n",
      "\tValue computed using high-temperature polynomial: 8.62009\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species HCNH, discontinuity in h/RT detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  31.9298\n",
      "\tValue computed using high-temperature polynomial: 31.3834\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species HCNH, discontinuity in s/R detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  38.9438\n",
      "\tValue computed using high-temperature polynomial: 38.3468\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species H2CNO, discontinuity in cp/R detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  22.7915\n",
      "\tValue computed using high-temperature polynomial: 11.3588\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species H2CNO, discontinuity in h/RT detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  26.491\n",
      "\tValue computed using high-temperature polynomial: 25.3684\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species H2CNO, discontinuity in s/R detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  44.2383\n",
      "\tValue computed using high-temperature polynomial: 43.0124\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species CH3NO, discontinuity in cp/R detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  20.4504\n",
      "\tValue computed using high-temperature polynomial: 13.1991\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species CH3NO, discontinuity in h/RT detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  15.491\n",
      "\tValue computed using high-temperature polynomial: 14.7826\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species CH3NO, discontinuity in s/R detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  47.6023\n",
      "\tValue computed using high-temperature polynomial: 46.8286\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species C2H5CHO, discontinuity in cp/R detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  33.8166\n",
      "\tValue computed using high-temperature polynomial: 25.3773\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species C2H5CHO, discontinuity in h/RT detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  0.697319\n",
      "\tValue computed using high-temperature polynomial: -0.0929274\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species C2H5CHO, discontinuity in s/R detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  64.855\n",
      "\tValue computed using high-temperature polynomial: 63.995\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species C2H5CO, discontinuity in cp/R detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  22.1895\n",
      "\tValue computed using high-temperature polynomial: 22.9822\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species C2H5CO, discontinuity in h/RT detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  10.7708\n",
      "\tValue computed using high-temperature polynomial: 11.0295\n",
      "\n",
      "\n",
      "**** WARNING ****\n",
      "For species C2H5CO, discontinuity in s/R detected at Tmid = 1500\n",
      "\tValue computed using low-temperature polynomial:  61.774\n",
      "\tValue computed using high-temperature polynomial: 62.0741\n"
     ]
    }
   ],
   "source": [
    "gas = ct.Solution('input-files/mech_debug/mech.cti')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These warnings are part of a validation check that Cantera does to make sure the thermodynamics data are consistent. In the standard NASA 14-coefficient polynomial form, the thermodynamics data are defined as two five coefficient polynomials (plus two other constants) over two temperature ranges. This is the form used for CHEMKIN files. The discontinuities occur when either the slope or the value of the thermodynamic functions ($c_p/R$, $h/(RT)$, or $s/R$) has a discontinuity at the mid-point temperature. Most commonly, one or more the discontinuities are due to incorrectly fit parameters, but they can also be caused by other means. Let's investigate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ct.suppress_thermo_warnings()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"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=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sp = gas.species('H2CNO')\n",
    "T = np.linspace(600, 2000, 200)\n",
    "f,ax = plt.subplots(1,3, figsize=(8,3.5))\n",
    "\n",
    "def plot_thermo(thermo):\n",
    "    h = [thermo.h(tt)/(ct.gas_constant * tt) for tt in T]\n",
    "    cp = [thermo.cp(tt)/ct.gas_constant for tt in T]\n",
    "    s = [thermo.s(tt)/ct.gas_constant for tt in T]\n",
    "    ax[0].plot(T,cp)\n",
    "    ax[0].set_title('$c_p/R$')\n",
    "    ax[1].plot(T,h)\n",
    "    ax[1].set_title('$h/RT$')\n",
    "    ax[2].plot(T,s)\n",
    "    ax[2].set_title('$s/R$')\n",
    "plot_thermo(sp.thermo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.5000000e+03,  5.4028152e+00,  6.9057001e-03, -2.5162977e-06,\n",
       "        4.1014066e-10, -2.4718300e-14,  2.4528690e+04, -4.4574262e+00,\n",
       "        3.8781858e+00, -6.6530886e-03,  5.3947610e-05, -6.8176813e-08,\n",
       "        2.7181746e-11,  2.5716857e+04,  7.4618774e+00])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c0 = sp.thermo.coeffs\n",
    "c0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "c0[0] = 1200\n",
    "test = ct.NasaPoly2(sp.thermo.min_temp, sp.thermo.max_temp, sp.thermo.reference_pressure, c0)\n",
    "plot_thermo(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "c0[0] = 1000\n",
    "test = ct.NasaPoly2(sp.thermo.min_temp, sp.thermo.max_temp, sp.thermo.reference_pressure, c0)\n",
    "plot_thermo(test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In many cases, when the change is on the order of a few percent, these discontinuities won't cause problems. However, if you notice a simulation failing at a consistent temperature for several conditions, this is one possible cause."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reaction Rates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another common issue with mechanisms are unphysical reaction rates (particularly reverse reaction rates). These unphysical reaction rates often exceed the collision limit for a given reaction. A recent study by [Chen et al.](https://www.sciencedirect.com/science/article/pii/S0010218017303024) found that\n",
    "\n",
    "> among.. 20 [recent] models tested, 15 of them contain either considerable numbers of rate coefficients that exceed their respective collision limits or reactions exceeding the collision limit in a considerable manner. In the worst case, the rate coefficient exceeds the collision limit by 73 orders of magnitude.\n",
    "\n",
    "The authors continue\n",
    "\n",
    "> It is proposed that computational tools should be made available for authors to conduct the same rate coefficient screening.\n",
    "\n",
    "Let's take a look at how Cantera can fill this need."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "  gas:\n",
      "\n",
      "       temperature             300  K\n",
      "          pressure          101325  Pa\n",
      "           density         0.71061  kg/m^3\n",
      "  mean mol. weight         17.4932  amu\n",
      "\n",
      "                          1 kg            1 kmol\n",
      "                       -----------      ------------\n",
      "          enthalpy     -5.9584e+06       -1.042e+08     J\n",
      "   internal energy      -6.101e+06       -1.067e+08     J\n",
      "           entropy           10981        1.921e+05     J/K\n",
      "    Gibbs function     -9.2527e+06       -1.619e+08     J\n",
      " heat capacity c_p          2036.8        3.563e+04     J/K\n",
      " heat capacity c_v          1561.5        2.732e+04     J/K\n",
      "\n",
      "                           X                 Y          Chem. Pot. / RT\n",
      "                     -------------     ------------     ------------\n",
      "                H2    7.59247e-06      8.74939e-07         -27.5055\n",
      "               H2O       0.090905        0.0936178         -122.058\n",
      "                CO    4.06301e-11      6.50574e-11         -92.0113\n",
      "               CO2      0.0454563          0.11436         -186.564\n",
      "               CH4       0.863631         0.792022         -52.4694\n",
      "              C2H6    8.67456e-08       1.4911e-07         -77.4334\n",
      "              C3H8    5.29756e-13       1.3354e-12         -102.397\n",
      "     [ +122 minor]    4.59535e-17      8.42281e-17\n",
      "\n"
     ]
    }
   ],
   "source": [
    "gas.TPX = 300, 101325, 'CH4:1.0, O2:0.1'\n",
    "gas.equilibrate('TP')\n",
    "gas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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": [
    "f, ax = plt.subplots()\n",
    "ax.semilogy(gas.forward_rate_constants, '.', label='forward')\n",
    "ax.semilogy(gas.reverse_rate_constants, '.', label='reverse')\n",
    "ax.axis(ymin=1e-30)\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are clearly several reverse rates with very high magnitudes. Let's print the reactions with reverse rate constants higher than $10^{20}$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   6  2.0744e+28  HNCN + M <=> H + NCN + M\n",
      " 109  2.2720e+21  N2H2 + M <=> 2 NH + M\n",
      " 126  2.1338e+20  N2H4 + M <=> H + N2H3 + M\n",
      " 295  4.2657e+23  CH3 + M <=> CH + H2 + M\n",
      " 737  5.8053e+23  C3H6 + O2 <=> HO2 + SC3H5\n",
      " 803  6.7117e+29  C3H3 + H <=> C3H2 + H2\n",
      " 806  7.6172e+20  C3H3 + OH <=> C3H2 + H2O\n",
      " 812  7.2188e+23  C2H2 + CH <=> C3H2 + H\n",
      " 900  2.1231e+25  C4H2 (+M) <=> C4H + H (+M)\n",
      " 939  2.1370e+25  PC3H4 <=> C2H + CH3\n",
      "1026  3.3031e+37  C2N2 + M <=> 2 CN + M\n"
     ]
    }
   ],
   "source": [
    "kr = gas.reverse_rate_constants\n",
    "for i, k in enumerate(kr):\n",
    "    if k > 1e20:\n",
    "        print(f'{i:4d}  {k:.4e}  {gas.reaction_equation(i)}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Among these is the reaction \n",
    "\n",
    "$$\\text{CH}_3 + \\text{M} <=> \\text{CH} + \\text{H}_2 + \\text{M}$$\n",
    "\n",
    "with reverse rate constant of `4.2656e+23`. This is a pretty common reaction, so we can compare to the same reaction from, for example, GRI 3.0:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "288 CH + H2 (+M) <=> CH3 (+M)\n"
     ]
    }
   ],
   "source": [
    "gri = ct.Solution('gri30.cti')\n",
    "for i, r in enumerate(gri.reactions()):\n",
    "    if 'CH3' in r and 'H2' in r and 'CH' in r:\n",
    "        print(i, r)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The reaction is #295 from the first mechanism and #288 from GRI-30, so we can calculate the rate of each reaction over a range of temperatures from 300 K to 3000 K and plot them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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": [
    "gasN = ct.SolutionArray(gas, shape=200)\n",
    "griN = ct.SolutionArray(gri, shape=200)\n",
    "T = np.linspace(300, 3000, 200)\n",
    "gasN.TPY = T, ct.one_atm, 'N2:1.0'\n",
    "griN.TPY = T, ct.one_atm, 'N2:1.0'\n",
    "\n",
    "f,ax = plt.subplots()\n",
    "ax.semilogy(1000/T, gasN.forward_rate_constants[:,295], label='mech, forward')\n",
    "ax.semilogy(1000/T, gasN.reverse_rate_constants[:,295], label='mech, reverse')\n",
    "ax.semilogy(1000/T, griN.forward_rate_constants[:,288], '--', label='GRI3.0, forward')\n",
    "ax.semilogy(1000/T, griN.reverse_rate_constants[:,288], '--', label='GRI3.0, reverse')\n",
    "T_label = np.array([300, 400, 500, 700, 1000, 2000])\n",
    "ax.set(xticks=1000/T_label, xticklabels=T_label, xlabel='Temperature (K)')\n",
    "ax.legend()\n",
    "ax.grid(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, we see that the rate of the reactions is close-ish at high temperature (>1000 K), but as the temperature decreases, they rapidly diverge and differ by 11 orders of magnitude at 300 K. This can cause problems in the integrator for both 0-D and 1-D problems, often accompanied by error messages about \"Repeated recoverable right-hand side errors\""
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}