dedalus_timevarying_1d_adv_diff.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Solve 1D advection diffusion problem\n",
    "\n",
    "$$\n",
    "\\frac{\\partial c}{\\partial t} + w_s \\frac{\\partial c}{\\partial z} - \\frac{\\partial}{\\partial z}\\left( F\\right) =0\n",
    "$$\n",
    "\n",
    "where\n",
    "\n",
    "$$\n",
    "F=K_v \\frac{\\partial c}{\\partial z}\n",
    "$$\n",
    "\n",
    "with boundary conditions\n",
    "\n",
    "$$\n",
    "F = f(t),\\ z =0\n",
    "$$\n",
    "\n",
    "$$\n",
    "F = 0,\\ z=H\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Gotta find my FFTW_PATH\n",
    "!export FFTW_PATH=/path/to/your/fftw_prefix "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[sudo] password for suntans: \n"
     ]
    }
   ],
   "source": [
    "!sudo pip install dedalus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "import numpy as np\n",
    "import dedalus.public as de\n",
    "from dedalus.tools  import post\n",
    "\n",
    "from dedalus.extras.plot_tools import quad_mesh, pad_limits\n",
    "\n",
    "\n",
    "import logging\n",
    "import matplotlib.pyplot as plt\n",
    "logger = logging.getLogger(__name__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Constants\n",
    "\n",
    "H = 5. # Depth\n",
    "\n",
    "nz = 64\n",
    "\n",
    "K_0 = 1e-1 # Diffusivity - had to boost this to actually get the sediment into the water column\n",
    "ws = 1e-3 # settling velocity\n",
    "\n",
    "E = -1e-3 # constant erosion rate [c/s]\n",
    "E = -1e-2 # constant erosion rate [c/s]\n",
    "\n",
    "uniform_diffusion = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CReate the domain\n",
    "\n",
    "z = de.Chebyshev('z',nz,interval=[0.,H])\n",
    "domain = de.Domain([z],grid_dtype='float')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for -: 'float' and 'Chebyshev'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-15b30b64fd7f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      9\u001b[0m     \u001b[0;31m# Add vertically varying diffusion\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m     \u001b[0mncc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdomain\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnew_field\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'K'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m     \u001b[0mncc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'g'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mH\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mz\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mK_0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     12\u001b[0m     \u001b[0mproblem\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'K'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mncc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for -: 'float' and 'Chebyshev'"
     ]
    }
   ],
   "source": [
    "# Create the problem\n",
    "problem = de.IVP(domain, variables=['c','F'])\n",
    "problem.parameters['ws'] = ws\n",
    "problem.parameters['E'] = E\n",
    "\n",
    "if uniform_diffusion:\n",
    "    problem.parameters['K'] = K_0\n",
    "else:\n",
    "    # Add vertically varying diffusion\n",
    "    ncc = domain.new_field(name = 'K')\n",
    "    ncc['g'] = (H-z)*K_0\n",
    "    problem.parameters['K'] = ncc\n",
    "\n",
    "problem.add_equation('dt(c) + ws * dz(c) - dz(F) = 0')\n",
    "problem.add_equation('F - K * dz(c) = 0')\n",
    "\n",
    "# Add the time varying boundary conditions\n",
    "problem.add_bc('left(F) = E*abs(sin(t))')\n",
    "problem.add_bc('right(F) = 0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-01-16 13:34:31,078 pencil 0/1 INFO :: Building pencil matrix 1/1 (~100%) Elapsed: 0s, Remaining: 0s, Rate: 3.3e+01/s\n",
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      "2020-01-16 13:34:48,170 solvers 0/1 INFO :: Simulation stop time reached.\n",
      "2020-01-16 13:34:48,173 __main__ 0/1 INFO :: Total time: 17.057803\n",
      "2020-01-16 13:34:48,183 __main__ 0/1 INFO :: Iterations: 1885\n",
      "2020-01-16 13:34:48,186 __main__ 0/1 INFO :: Average timestep: 0.010000\n"
     ]
    }
   ],
   "source": [
    "solver = problem.build_solver(de.timesteppers.RK443)\n",
    "\n",
    "solver.stop_sim_time = 6*np.pi\n",
    "solver.stop_wall_time = 1000.\n",
    "solver.stop_iteration = np.inf\n",
    "dt = 0.01\n",
    "\n",
    "# Store data for final plot\n",
    "# Initial conditions\n",
    "z = domain.grid(0)\n",
    "c = solver.state['c']\n",
    "\n",
    "c.set_scales(1, keep_data=True)\n",
    "c_list = [np.copy(c['g'])]\n",
    "t_list = [solver.sim_time]\n",
    "\n",
    "start_time = time.time()\n",
    "while solver.ok:\n",
    "    solver.step(dt)\n",
    "    if solver.iteration % 20 == 0:\n",
    "        logger.info(\"Time step {}\".format(solver.iteration))\n",
    "        c.set_scales(1, keep_data=True)\n",
    "        c_list.append(np.copy(c['g']))\n",
    "        t_list.append(solver.sim_time)\n",
    "end_time = time.time()\n",
    "\n",
    "# Print statistics\n",
    "logger.info('Total time: %f' %(end_time-start_time))\n",
    "logger.info('Iterations: %i' %solver.iteration)\n",
    "logger.info('Average timestep: %f' %(solver.sim_time/solver.iteration))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "c_array = np.array(c_list)\n",
    "t_array = np.array(t_list)\n",
    "zmesh, tmesh = quad_mesh(x=z, y=t_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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       "    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 overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.pcolormesh(tmesh.T, zmesh.T, c_array.T, cmap='RdBu_r')\n",
    "plt.axis(pad_limits(tmesh, zmesh))\n",
    "plt.colorbar()\n",
    "plt.ylabel('z')\n",
    "plt.xlabel('t')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((95, 64), (64,), 95)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c_array.shape, z.shape, len(t_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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 overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc3d2fb9c50>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(c_array[0,:],z)\n",
    "plt.plot(c_array[40,:],z)\n",
    "plt.plot(c_array[45,:],z)\n",
    "plt.plot(c_array[50,:],z)\n",
    "plt.plot(c_array[-1,:],z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.8.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}