Implementation of benchmark 3

README.md

Implementation of Benchmark 3

Linting and testing

$ pylint *.py
$ flake8 *.py

TODO

• generate upload files from view.py
  • time.csv time data
  • contour plot data
• generate test and lint suite
• Dockerfile
• Fix README
• make main.py a command line tool
  • write to new directory
• expand out for other benchmarks

contour.csv

logo_dendrite.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/guyer/anaconda/envs/parallel2/lib/python2.7/site-packages/IPython/kernel/__init__.py:13: ShimWarning: The `IPython.kernel` package has been deprecated. You should import from ipykernel or jupyter_client instead.\n",
      "  \"You should import from ipykernel or jupyter_client instead.\", ShimWarning)\n"
     ]
    }
   ],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import fipy as fp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from fipy import numerix as nmx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dx = 1. # .5\n",
    "Lx = 200."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mesh = fp.Grid2D(dx=dx, Lx=Lx, dy=dx, Ly=Lx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "u = fp.CellVariable(mesh=mesh, name=\"u\", hasOld=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "phi = fp.CellVariable(mesh=mesh, name=r\"$\\varphi$\", hasOld=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = nmx.sqrtDot(mesh.cellCenters, mesh.cellCenters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "D = 10.\n",
    "tau0 = 1.\n",
    "W0 = 1.\n",
    "lamda = D * tau0 / (0.6267 * W0**2)\n",
    "theta = nmx.arctan2(phi.grad[1], phi.grad[0])\n",
    "theta.name = r\"$\\theta$\"\n",
    "theta_f = nmx.arctan2(phi.faceGrad[1], phi.faceGrad[0])\n",
    "theta_f.name = r\"$\\theta$\"\n",
    "n = fp.Variable(4)\n",
    "epsilon = fp.Variable(0.025)\n",
    "a = 1 + epsilon * nmx.cos(n * theta)\n",
    "a_f = 1 + epsilon * nmx.cos(n * theta_f)\n",
    "aprime_f = -epsilon * n * nmx.sin(n * theta_f)\n",
    "tau = tau0 * a**2\n",
    "W = W0 * a\n",
    "Delta = fp.Variable(value=0.3, name=r\"$\\Delta$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# u.constrain(-Delta, where=mesh.facesRight | mesh.facesTop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "n.value = 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "ueq = (fp.TransientTerm(coeff=1., var=u) \n",
    "       == fp.DiffusionTerm(coeff=D, var=u)\n",
    "       + fp.TransientTerm(coeff=0.5, var=phi))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "I0 = fp.Variable(value=((1,0), (0,1)))\n",
    "I1 = fp.Variable(value=((0,-1), (1,0)))\n",
    "Dphi = W0**2 * a_f * (a_f * I0 + aprime_f * I1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "phieq = (fp.TransientTerm(coeff=tau, var=phi)\n",
    "         == fp.DiffusionTerm(coeff=Dphi, var=phi)\n",
    "         + fp.ImplicitSourceTerm(coeff=1-phi**2, var=phi)\n",
    "         - fp.ImplicitSourceTerm(coeff=lamda * (1 - 2*phi**2 + phi**4), var=u))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "eq = ueq & phieq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "phi.value = -1\n",
    "phi.setValue(+1, where=r <= 8.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "u.value = -Delta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "faceNorm = phi.faceGrad / (phi.faceGrad.mag + (phi.faceGrad.mag == 0.) * 1.)\n",
    "faceNorm.name = r\"$\\hat{n}$\"\n",
    "curvature = faceNorm.divergence\n",
    "curvature.name = r\"$\\kappa$\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "radius = 1. / curvature\n",
    "radius.name = r\"$\\rho$\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "            fig.waiting = false;\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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\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",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // 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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "phiviewer = fp.Viewer(vars=phi, datamin=-1, datamax=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "            fig.waiting = false;\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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\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",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // 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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/guyer/Documents/research/FiPy/fipy/fipy/variables/variable.py:1170: RuntimeWarning: divide by zero encountered in divide\n",
      "  return self._BinaryOperatorVariable(lambda a,b: b/a, other)\n",
      "/Users/guyer/Documents/research/FiPy/fipy/fipy/variables/variable.py:1151: RuntimeWarning: invalid value encountered in multiply\n",
      "  return self._BinaryOperatorVariable(lambda a,b: a*b, other)\n"
     ]
    }
   ],
   "source": [
    "radviewer = fp.Viewer(vars=radius *(1 + phi) * (1-phi), datamin=-20, datamax=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "radviewer.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-23-b46aded2fd6d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0msweep\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m         \u001b[0mueq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msolve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdt\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m.05\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m         \u001b[0mphieq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msolve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdt\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m.05\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m \u001b[0;31m#        res = eq.sweep(dt=.1)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0;31m#        print res\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/guyer/Documents/research/FiPy/fipy/fipy/terms/term.pyc\u001b[0m in \u001b[0;36msolve\u001b[0;34m(self, var, solver, boundaryConditions, dt)\u001b[0m\n\u001b[1;32m    209\u001b[0m         \"\"\"\n\u001b[1;32m    210\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 211\u001b[0;31m         \u001b[0msolver\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_prepareLinearSystem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvar\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msolver\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mboundaryConditions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    212\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    213\u001b[0m         \u001b[0msolver\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_solve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/guyer/Documents/research/FiPy/fipy/fipy/terms/term.pyc\u001b[0m in \u001b[0;36m_prepareLinearSystem\u001b[0;34m(self, var, solver, boundaryConditions, dt)\u001b[0m\n\u001b[1;32m    168\u001b[0m                                                            \u001b[0mtransientGeomCoeff\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getTransientGeomCoeff\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvar\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    169\u001b[0m                                                            \u001b[0mdiffusionGeomCoeff\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getDiffusionGeomCoeff\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvar\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 170\u001b[0;31m                                                            buildExplicitIfOther=self._buildExplcitIfOther)\n\u001b[0m\u001b[1;32m    171\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    172\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buildCache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmatrix\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mRHSvector\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/guyer/Documents/research/FiPy/fipy/fipy/terms/binaryTerm.pyc\u001b[0m in \u001b[0;36m_buildAndAddMatrices\u001b[0;34m(self, var, SparseMatrix, boundaryConditions, dt, transientGeomCoeff, diffusionGeomCoeff, buildExplicitIfOther)\u001b[0m\n\u001b[1;32m     66\u001b[0m                                                                         \u001b[0mtransientGeomCoeff\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtransientGeomCoeff\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     67\u001b[0m                                                                         \u001b[0mdiffusionGeomCoeff\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdiffusionGeomCoeff\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 68\u001b[0;31m                                                                         buildExplicitIfOther=buildExplicitIfOther)\n\u001b[0m\u001b[1;32m     69\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     70\u001b[0m             \u001b[0mmatrix\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mtmpMatrix\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/guyer/Documents/research/FiPy/fipy/fipy/terms/binaryTerm.pyc\u001b[0m in \u001b[0;36m_buildAndAddMatrices\u001b[0;34m(self, var, SparseMatrix, boundaryConditions, dt, transientGeomCoeff, diffusionGeomCoeff, buildExplicitIfOther)\u001b[0m\n\u001b[1;32m     66\u001b[0m                                                                         \u001b[0mtransientGeomCoeff\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtransientGeomCoeff\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     67\u001b[0m                                                                         \u001b[0mdiffusionGeomCoeff\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdiffusionGeomCoeff\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 68\u001b[0;31m                                                                         buildExplicitIfOther=buildExplicitIfOther)\n\u001b[0m\u001b[1;32m     69\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     70\u001b[0m             \u001b[0mmatrix\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mtmpMatrix\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/guyer/Documents/research/FiPy/fipy/fipy/terms/binaryTerm.pyc\u001b[0m in \u001b[0;36m_buildAndAddMatrices\u001b[0;34m(self, var, SparseMatrix, boundaryConditions, dt, transientGeomCoeff, diffusionGeomCoeff, buildExplicitIfOther)\u001b[0m\n\u001b[1;32m     68\u001b[0m                                                                         buildExplicitIfOther=buildExplicitIfOther)\n\u001b[1;32m     69\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 70\u001b[0;31m             \u001b[0mmatrix\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mtmpMatrix\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     71\u001b[0m             \u001b[0mRHSvector\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mtmpRHSvector\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     72\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/guyer/Documents/research/FiPy/fipy/fipy/matrices/pysparseMatrix.pyc\u001b[0m in \u001b[0;36m__iadd__\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m     69\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     70\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__iadd__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 71\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_iadd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatrix\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     72\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     73\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/guyer/Documents/research/FiPy/fipy/fipy/matrices/pysparseMatrix.pyc\u001b[0m in \u001b[0;36m_iadd\u001b[0;34m(self, L, other, sign)\u001b[0m\n\u001b[1;32m     74\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_iadd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mL\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msign\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     75\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mother\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 76\u001b[0;31m             \u001b[0mL\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshift\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msign\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatrix\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     77\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     78\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__add__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "for step in xrange(1000000):\n",
    "    phi.updateOld()\n",
    "    u.updateOld()\n",
    "    for sweep in range(3):\n",
    "        ueq.solve(dt=.05)\n",
    "        phieq.solve(dt=.05)\n",
    "#        res = eq.sweep(dt=.1)\n",
    "#        print res\n",
    "    if step % 10 == 0:\n",
    "#        radviewer.plot()\n",
    "        phiviewer.plot()\n",
    "#        tsv.plot(filename=\"%d.txt.gz\" % step)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}

main.py

"""Run Benchmark Problem 3 using FiPy

    $ python main.py --folder=my_folder

All the data files will be written to my_folder/
"""
# pylint: disable=no-value-for-parameter

import os
import time

import numpy as np
# pylint: disable=redefined-builtin
from toolz.curried import pipe, do, iterate, curry, map, compose
# pylint: disable=import-error
from fipy import CellVariable, DiffusionTerm, Grid2D, TransientTerm, Variable
# pylint: disable=import-error
from fipy import numerix
from fipy.solvers.pysparse import LinearGMRESSolver as Solver
# from fipy.solvers.trilinos import LinearGMRESSolver as Solver
import click


def get_params():
    """Get the parameters for the simulation
    """
    return dict(
        mm=4.0,
        epsilon_m=0.05,
        theta_0=np.pi / 4.,
        tau_0=1.0,
        diff=10.0,
        w_0=1.,
        delta=-0.3,
        dx=1.0,
        nx=960,
        radius=8.0,
        dt0=0.1,
        center=(0.0, 0.0),
        steps=15001,
        output_frequency=10
    )


def get_mesh(params):
    """Build the mesh
    """
    return Grid2D(nx=params['nx'],
                  ny=params['nx'],
                  dx=params['dx'],
                  dy=params['dx'])


def mask(x_cell, y_cell, params):
    """Mask for the initial solid portion
    """
    return (((x_cell - params['center'][0])**2 +
             (y_cell - params['center'][1])**2) <
            params['radius']**2).value


def get_phase(mesh, params, value=1.):
    """Generate the phase cell variable
    """
    return pipe(
        mesh,
        lambda x: CellVariable(mesh=x, hasOld=True, value=-1.0),
        do(
            lambda x:
            x.setValue(
                value,
                where=mask(mesh.cellCenters[0], mesh.cellCenters[1], params)
            )
        )
    )


def get_tau(phase, params):
    """Tau function for phase transient term
    """
    return pipe(
        phase,
        lambda x: numerix.arctan2(x.grad[1], x.grad[0]),
        lambda x: w_func(x, params) / params['w_0'],
        lambda x: params['tau_0'] * x**2
    )


def get_coupling(params):
    """Calculate the coupling constant, "lambda"
    """
    return params['diff'] * params['tau_0'] / 0.6267 / params['w_0']**2


def get_source(phase, heat, params):
    """Phase field source term
    """
    return (phase - get_coupling(params) * heat * (1 - phase**2)) * \
        (1 - phase**2)


def w_func(theta, params):
    """W function dependent on the orientation
    """
    return params['w_0'] * \
        (1 +
         params['epsilon_m'] *
         numerix.cos(params['mm'] * (theta - params['theta_0'])))


def w_theta(theta, params):
    """Derivative w.r.t theta of the W function
    """
    return -params['w_0'] * params['mm'] * params['epsilon_m'] * \
        numerix.sin(params['mm'] * (theta - params['theta_0']))


def get_phase_diff(phase, params):
    """Diffusion coefficient for the phase equation
    """
    return pipe(
        phase,
        lambda x: numerix.arctan2(x.faceGrad[1], x.faceGrad[0]),
        lambda x: (w_func(x, params), w_theta(x, params)),
        lambda x: x[0]**2 * Variable(value=((1, 0), (0, 1))) -
        x[0] * x[1] * Variable(value=((0, -1), (1, 0)))
    )


def get_heat_eqn(phase, delta_t, params):
    """Make the heat equation
    """
    return TransientTerm() == DiffusionTerm(params['diff']) + \
        (phase - phase.old) / delta_t / 2.


def get_phase_eqn(phase, heat, params):
    """make the phase equation
    """
    return TransientTerm(get_tau(phase, params)) == \
        DiffusionTerm(get_phase_diff(phase, params)) + \
        get_source(phase, heat, params)


def get_equations(mesh, delta_t, params):
    """Make the heat and phase equation systems
    """
    return pipe(
        dict(phase=get_phase(mesh, params),
             heat=CellVariable(mesh=mesh,
                               hasOld=True,
                               value=params['delta'])),
        lambda x: (
            dict(name='heat',
                 eqn=get_heat_eqn(x['phase'], delta_t, params),
                 var=x['heat'],
                 solver=Solver(precon=None)),
            dict(name='phase',
                 eqn=get_phase_eqn(x['phase'], x['heat'], params),
                 var=x['phase'],
                 solver=Solver(precon=None))
        )
    )


@curry
def iterate_(func, times, value):
    """Use toolz iterate function to actually iterate
    rather than return an iterator object
    """
    iter_ = iterate(func, value)
    for _ in range(times):
        next(iter_)
    return next(iter_)


@curry
def map_(func, value):
    """Force evaluation of toolz map
    """
    return list(map(func, value))


@curry
def sweep_output(data, residuals):
    """Output from a sweep
    """
    print('sweep: {4}, {0} res: {1}, {2} res: {3}'.format(
        data['equations'][0]['name'],
        residuals[0],
        data['equations'][1]['name'],
        residuals[1],
        data['sweep_counter']
    ))
    data['sweep_counter'] += 1
    return data


@curry
def one_sweep(delta_t, equation):
    """Do one sweep
    """
    return equation['eqn'].sweep(equation['var'],
                                 dt=float(delta_t.value),
                                 solver=equation['solver'])


def sweep(data):
    """Do one sweep and output results
    """
    return pipe(
        data,
        lambda x: map_(one_sweep(data['dt']), x['equations']),
        sweep_output(data),
    )


@curry
def step_output(folder, data):
    """Output before time step
    """
    print ""
    print "write data to: {0}".format(folder)
    print "timestep: {0}, elapsed time: {1}".format(
        data['step_counter'],
        data['elapsed']
    )
    return data


def update(data):
    """Update after time step
    """
    data['step_counter'] += 1
    data['elapsed'] += float(data['dt'].value)
    data['dt'].setValue(float(data['dt'].value) * 1.0)
    return data


@curry
def timestep(folder, data):
    """Do a time step
    """
    return pipe(
        data,
        step_output(folder),
        dump_data(folder),
        do(lambda x: map_(lambda x: x['var'].updateOld(), x['equations'])),
        iterate_(sweep, 3),
        update
    )


def get_data(params, delta_t):
    """Generate the initial data structure
    """
    return dict(
        dt=delta_t,
        equations=get_equations(mesh=get_mesh(params),
                                delta_t=delta_t,
                                params=params),
        step_counter=0,
        sweep_counter=0,
        elapsed=0.0,
        params=params
    )


@curry
def dump_data(folder, data):
    """Dump data to a file
    """
    if data['step_counter'] % data['params']['output_frequency'] == 0:
        np.savez_compressed(
            os.path.join(
                folder,
                'data{0}.npz'.format(
                    str(data['step_counter']).zfill(7)
                )
            ),
            heat=np.array(data['equations'][0]['var']),
            phase=np.array(data['equations'][1]['var']),
            elapsed_time=float(data['elapsed']),
            step_counter=int(data['step_counter']),
            params=data['params'],
            wall_time=time.time()
        )
    return data


def sequence(*args):
    """Reverse compose
    """
    return compose(*args[::-1])


add_options = sequence(
    lambda x: x.items(),
    map_(lambda x: click.option('--' + x[0], default=x[1])),
    lambda x: compose(*x)
)


@click.command()
@click.option('--folder', default='data', help="name for data directory")
@add_options(get_params())
def run(folder, **params):
    if os.path.exists(folder):
        click.echo(
            "{0} directory already exists, remove to continue".format(folder)
        )
    else:
        os.makedirs(folder)
        iterate_(timestep(folder),
                 params['steps'],
                 get_data(params, Variable(params['dt0'])))


if __name__ == '__main__':
    run()

time.csv

view.py

"""View results for benchmark problem 3

To plot the solid fraction from directory "data_xxx"

    $ python view.py --folder data_xxx solid_fraction

To plot the free energy

    $ python view.py --folder data_xxx free_energy

To plot the tip position

    $ python view.py --folder data_xxx tip_position

To view the latest time step

    $ python view.py --folder data_xxx view_step --latest

To view a particular time step

    $ python view.py --folder data_xxx view_step --step 500

To save the data to CSV files for upload to the website

    $ python view.py --folder data_xxx save_data
"""
# pylint: disable=no-value-for-parameter

import glob
import os

from scipy.interpolate import interp1d
from scipy.optimize import brentq
import numpy as np
import click
from fipy import Viewer, CellVariable, numerix
from toolz.curried import curry, pipe, do, assoc, juxt, get
import matplotlib.pyplot as plt
import progressbar
import pandas

from main import get_mesh, map_, sequence, get_phase, w_func, get_coupling


@click.group()
@click.option('--folder',
              default='data',
              help="the name of the data directory to parse")
@click.pass_context
def cli(ctx, folder):
    """Use a group function to allow subcommands.
    """
    ctx.params['folder'] = folder


def get_filename(step, latest, folder):
    """Get the filename given the step
    """
    if latest:
        return sorted(glob.glob(os.path.join(folder, 'data*.npz')))[-1]
    return os.path.join(folder, 'data{0}.npz'.format(str(step).zfill(7)))


@curry
def get_var(data, name):
    """Make a variale
    """
    return CellVariable(
        get_mesh(data['params'].item()),
        value=data[name],
        name=name
    )


def get_vars(ctx, step, latest):
    return pipe(
        get_filename(step, latest, ctx.parent.params['folder']),
        np.load,
        lambda x: map_(get_var(x), ['heat', 'phase'])
    )


@curry
def save_vars(save, vars):
    if save:
        pipe(
            vars,
            get(1),
            lambda x: dict(phase=np.array(x),
                           x=np.array(x.mesh.cellCenters[0]),
                           y=np.array(x.mesh.cellCenters[1])),
            pandas.DataFrame,
            lambda x: x.to_csv('space.csv', index=False)
        )


# def debug(x):
#     import ipdb; ipdb.set_trace()
#     return x

@curry
def save_contour(save, vars):
    def reshape(arr, nx):
        return np.array(arr).reshape((nx, nx))

    if save:
        pipe(
            vars,
            get(1),
            lambda x: dict(phase=reshape(x, x.mesh.nx),
                           x=reshape(x.mesh.cellCenters[0], x.mesh.nx),
                           y=reshape(x.mesh.cellCenters[1], x.mesh.nx)),
            lambda x: plt.contour(x['x'], x['y'], x['phase'], (0.0,)),
            lambda x: x.collections[0].get_paths()[0].vertices,
            lambda x: dict(x=x[:, 0], y=x[:, 1]),
            pandas.DataFrame,
            lambda x: x.to_csv('contour.csv', index=False)
        )


@cli.command()
@click.option('--step', default=0, help='step to view')
@click.option('--latest/--no-latest',
              default=False,
              help='view the latest result available')
@click.option('--save/--no-save',
              default=False,
              help='save the spatial data to a CSV')
@click.pass_context
def view_step(ctx, step, latest, save):
    """Use Matplotlib to view the phase and heat variables
    """
    return pipe(
        get_vars(ctx, step, latest),
        do(save_vars(save)),
        do(save_contour(save)),
        map_(lambda x: Viewer(x, title=x.name).plot()),
        do(lambda _: click.pause())
    )


def plot2d(arr):
    """Plot a 2D graph
    """
    plt.plot(arr[:, 0], arr[:, 1])
    plt.show()


@curry
def save2d(filename, column_names, data):
    pandas.DataFrame(
        dict(zip(column_names, data.transpose()))
    ).to_csv(filename, index=False)
    click.echo('CSV file written to {0}'.format(filename))


def pbar(items):
    pbar_ = progressbar.ProgressBar(
        widgets=[progressbar.Percentage(),
                 ' ',
                 progressbar.Bar(marker=progressbar.RotatingMarker()),
                 ' ',
                 progressbar.ETA()],
        maxval=len(items)).start()
    for counter, item in enumerate(items):
        yield item
        pbar_.update(counter + 1)
    pbar_.finish()


def read_and_calc(f_calc):
    """Read in the data and return a result
    """
    return sequence(
        lambda x: x.parent.params['folder'],
        lambda x: os.path.join(x, 'data*.npz'),
        glob.glob,
        sorted,
        pbar,
        map_(
            sequence(
                np.load,
                f_calc
            )
        ),
        np.array
    )


def read_and_plot(f_calc):
    """Read in a file and plot using f_calc
    """
    return sequence(
        read_and_calc(juxt(get('elapsed_time'), f_calc)),
        plot2d
    )


def read_and_save(filename, column_names, f_calc):
    """Read in a file and save data to CSV
    """
    return sequence(
        read_and_calc(f_calc),
        save2d(filename, column_names)
    )


def calc_solid_fraction(ctx):
    return np.sum((1 + ctx['phase']) / 2) / ctx['params'].item()['nx']**2


@cli.command()
@click.pass_context
def solid_fraction(ctx):
    """Command to plot the solid fraction
    """
    read_and_plot(calc_solid_fraction)(ctx)


calc_tip_position = sequence(
    lambda x: dict(dx=x['params'].item()['dx'],
                   phase=x['phase'],
                   nx=x['params'].item()['nx']),
    lambda x: dict(xx=x['dx'] * (0.5 + np.arange(x['nx'])),
                   yy=x['phase'][:x['nx']]),
    lambda x: brentq(interp1d(x['xx'], x['yy']), x['xx'][0], x['xx'][-1])
)


def f_chem(phase, heat, params):
    return -phase**2 / 2 \
        + phase**4 / 4 \
        + get_coupling(params) * heat * phase * \
        (1 - 2 * phase**2 / 3 + phase**4 / 5)


def w_func_(phase, params):
    return w_func(
        numerix.arctan2(phase.grad[1], phase.grad[0]),
        params
    )


def grad_mag(phase):
    return phase.grad[1]**2 + phase.grad[0]**2


def free_energy_func(phase, heat, params):
    return np.array(
        (
            0.5 * w_func_(phase, params) * grad_mag(phase)
            + f_chem(phase, heat, params)
        ) * params['dx']**2
    ).sum()


calc_free_energy = sequence(
    lambda x: assoc(x, 'params', x['params'].item()),
    lambda x: assoc(x, 'mesh', get_mesh(x['params'])),
    lambda x: assoc(x,
                    'phase',
                    get_phase(x['mesh'], x['params'], value=x['phase'])),
    lambda x: assoc(x,
                    'heat',
                    CellVariable(mesh=x['mesh'], value=x['heat'])),
    lambda x: free_energy_func(x['phase'], x['heat'], x['params'])
)


@cli.command()
@click.pass_context
def tip_position(ctx):
    """Command to plot the tip position versus time
    """
    read_and_plot(calc_tip_position)(ctx)


@cli.command()
@click.pass_context
def free_energy(ctx):
    """Command to calculate the free energy
    """
    read_and_plot(calc_free_energy)(ctx)


@cli.command()
@click.pass_context
def save_time_data(ctx):
    read_and_save(
        'time.csv',
        ['time', 'solid_fraction', 'tip_position', 'free_energy'],
        juxt(get('elapsed_time'),
             calc_solid_fraction,
             calc_tip_position,
             calc_free_energy)
    )(ctx)


if __name__ == '__main__':
    cli()