Lecture-22-Phase-Field-Basics.ipynb

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    "!jupyter nbconvert Lecture-22-Phase-Field-Basics.ipynb --to slides --post serve"
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   "source": [
    "# Lecture 22:  Phase Field Models"
   ]
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   "source": [
    "### Sections"
   ]
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   "source": [
    "* [Introduction](#Introduction)\n",
    "* [Learning Goals](#Learning-Goals)\n",
    "* [On Your Own](#On-Your-Own)\n",
    "    * [The Order Parameter](#The-Order-Parameter)\n",
    "* [In Class](#In-Class)\n",
    "    * [The Free Energy Functional](#The-Free-Energy-Functional)\n",
    "    * [The Equation of Motion](#The-Equation-of-Motion)\n",
    "    * [Analytical Solution](#Analytical-Solution)\n",
    "    * [Numerical Solution (FiPy)](#Numerical-Solution-(FiPy)\n",
    "    * [In 2D](#In-2D)\n",
    "* [Homework](#Homework)\n",
    "* [Summary](#Summary)\n",
    "* [Looking Ahead](#Looking-Ahead)\n",
    "* [Reading Assignments and Practice](#Reading-Assignments-and-Practice)"
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   "source": [
    "### Introduction\n",
    "----"
   ]
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   "source": [
    "This workbook/lecture is derived from Boettinger, et al. in Annual Review of Materials Research, v32, p163-194 (2002).  \n",
    "\n",
    "doi: 10.1146/annurev.matsci.32.101901.155803"
   ]
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   "source": [
    "The phase field method makes possible the study of complex microstructural morphologies such as dendritic and eutectic solidification as well as polycrystalline growth."
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    "The major contribution of the method is the introduction of an order parameter used to delineate phases such as solid/liquid, $\\alpha~/~\\beta$, etc.  The concept of an order parameter is not new.  However, smoothly varying this order parameter through an interphase interface frees us from tracking the interface position and applying boundary conditions at interfaces having complex morphologies."
   ]
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   "source": [
    "[Top of Page](#Sections)"
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    "### Learning Goals\n",
    "----\n",
    "\n",
    "*  Introduction to the idea of an \"order parameter\".\n",
    "*  Observe a practical use for the Calculus of Variations.\n",
    "*  Introduction to what is meant by a non-homogeneous thermodynamic system.\n",
    "*  Code a simple microstructure simulation."
   ]
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   "source": [
    "[Top of Page](#Sections)"
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   "source": [
    "### On Your Own\n",
    "----\n",
    "\n",
    "Read this small excerpt from Boettinger's paper:\n",
    "\n",
    ">The method employs a phase-field variable, e.g., $\\phi$, which is a function of position and time, to describe whether the material is liquid or solid. The behavior\n",
    "of this variable is governed by an equation that is coupled to equations for heat\n",
    "and solute transport. Interfaces between liquid and solid are described by smooth\n",
    "but highly localized changes of this variable between fixed values that represent\n",
    "solid and liquid, (in this review, 0 and 1, respectively)."
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    "Therein is the key feature of phase field models.  The order (or the phase) is described by a field variable ($\\phi$) coupled to heat and mass transfer.  The result is that complex interface shapes do not require tracking of the position of the interface.\n",
    "\n",
    "This may not have significance to you, however there was a time when knowledge of the position of the interface was required for solidification calculations.  This boundary condition made dendrite computation difficult if not impossible."
   ]
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   "source": [
    "#### The Order Parameter"
   ]
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    "![](./images/Interface.png)\n",
    "\n",
    "The order parameter can be thought of as an envelope around probability amplitudes of atomic positions.  In the picture below we have a probability density of finding an atom at a particular position.  In this picture $\\phi = 0$ might be considered the solid, and $\\phi = 1$ would be the liquid."
   ]
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    "Using the order parameter in this way makes it easier to calculate solidification microstructures - we no longer have to track the interface (you'll see how this works below).\n",
    "\n",
    "The shape of this interface is a balance between two forces.  The energy increase for intermediate states between solid and liquid (from the bulk free energy) and energy costs associated with steep gradients in the phase-field order parameter."
   ]
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  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "[Top of Page](#Sections)"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "#### Review:  Calculus of Variations"
   ]
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    "The calculus of variations is a rich mathematical subject.  There are many books on the topic.  One of the canonical problems in the subject area is to compute the shortest arc between to points on a plane.  This, is a good place to begin your study of the topic.  For now I'll describe the major output of the CoV and the points relevant to phase field."
   ]
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    "The analogy between calculus and CoV is good.  If finding the minimum of a function can be done by inspecting derivatives then the minimum of a functional can be found by inspecting the so-called 'variational derivative'.  In particular the first chapter of Lev. D. Elsgolc's book \"Calculus of Variations\" presents this idea nicely."
   ]
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    "The CoV gives us the Euler-Lagrange equation.  This is the main tool of CoV:\n",
    "\n",
    "$$ \\frac{\\delta F}{\\delta \\phi} = \\frac{\\partial F}{\\partial \\phi} - \\frac{\\partial}{\\partial x} \\frac{\\partial F}{\\partial \\nabla \\phi} = 0$$"
   ]
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   "source": [
    "The scalar and gradient terms in $\\phi$ are treated as independent variables.  This equation is telling us that the function that minimizes the functional is the solution to the above differential equation."
   ]
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  {
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     "slide_type": "skip"
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   },
   "source": [
    "[Top of Page](#Sections)"
   ]
  },
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     "slide_type": "skip"
    }
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   "source": [
    "### In Class\n",
    "----"
   ]
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   "source": [
    "#### The Free Energy Functional"
   ]
  },
  {
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   "source": [
    "The Langragian is constructed from the free energy functional (and integrated over all space, V) and that, in turn is constructed from the bulk free energy and the gradient energy thus:"
   ]
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    "$$L(\\phi,\\nabla\\phi) = \\int_V \\Big[ ~~f(\\phi,T) + \\frac{\\epsilon^2_\\phi}{2}|\\nabla \\phi|^2~\\Big]~ dV$$\n",
    "\n",
    "Where L is the Lagrangian, the functional (hereafter F) is in the square brackets, V is the volume of the system, $\\phi$ is the order parameter, T is the temperature, $\\epsilon$ is the gradient energy coefficient and $\\nabla$ has the usual meaning."
   ]
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   "source": [
    "$f(\\phi,T)$ is the free energy density.  This is often referred to as the 'bulk' free energy term and the terms in $\\nabla\\phi$ are the gradient energy terms.  You may also hear these terms referred to as the 'non-classical' terms."
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    "At equilibrium the variational derivatives must satisfy the following:\n",
    "\n",
    "$$ \\frac{\\delta F}{\\delta \\phi} = \\frac{\\partial f}{\\partial \\phi} - \\epsilon^2_\\phi \\nabla^2 \\phi = 0$$\n",
    "\n",
    "Recall the definition of the Euler-Lagrange equation:\n",
    "\n",
    "$$ \\frac{\\delta F}{\\delta \\phi} = \\frac{\\partial F}{\\partial \\phi} - \\frac{\\partial}{\\partial x} \\frac{\\partial F}{\\partial \\nabla \\phi} = 0$$\n",
    "\n",
    "and the free energy functional:\n",
    "\n",
    "$$f(\\phi,T) + \\frac{\\epsilon^2_\\phi}{2}|\\nabla \\phi|^2$$"
   ]
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   "source": [
    "The first equation above tells us that the function $\\phi(x,t)$ is unchanging.  We will compute this interface profile below.  To develop a kinetic expression we make an educated guess (also known as an \"ansatz\" in the phase field literature) about the relaxation of a system towards equilibrium."
   ]
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     "slide_type": "skip"
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   "source": [
    "[Top of Page](#Sections)"
   ]
  },
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   "source": [
    "#### The Equation of Motion"
   ]
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  {
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   "source": [
    "We assume the following functional form for the equation of motion:\n",
    "\n",
    "$$\\frac{\\partial \\phi}{\\partial t} = - M_\\phi \\frac{\\delta F}{\\delta \\phi}$$\n",
    "\n",
    "This is the simplest expression that guarantees the free energy of the system will decrease over time.  In this form the phase-field variable, $\\phi$, is non-conserved.  The conserved form takes the divergence of the expression above as is done when expression accumulation in a control volume (as in Fick's second law)."
   ]
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   "source": [
    "Our equation of motion is therefore:\n",
    "\n",
    "$$\\frac{\\partial \\phi}{\\partial t} = - M_\\phi \\Big[\\frac{\\partial f}{\\partial \\phi} - \\epsilon^2_\\phi \\nabla^2 \\phi \\Big]$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "[Top of Page](#Sections)"
   ]
  },
  {
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   "source": [
    "#### Building the Bulk Free Energy '$f$'"
   ]
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   "source": [
    "There are two so-called helper functions that homogenize the free energy.  The interpolating function, $p(\\phi)$ and the double well function $g(\\phi)$."
   ]
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    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib notebook\n",
    "\n",
    "def plot_p_and_g():\n",
    "    phi = np.linspace(-0.1, 1.1, 200)\n",
    "    g=phi**2*(1-phi)**2\n",
    "    p=phi**3*(6*phi**2-15*phi+10)\n",
    "\n",
    "    # Changed 3 to 1 in the figure call.\n",
    "    plt.figure(1, figsize=(12,6))\n",
    "    plt.subplot(121)\n",
    "    plt.plot(phi, g, linewidth=1.0);\n",
    "    plt.xlabel('$\\phi$', fontsize=18)\n",
    "    plt.ylabel('$g(\\phi)$', fontsize=18)\n",
    "\n",
    "    plt.subplot(122)\n",
    "    plt.plot(phi, p, linewidth=1.0);\n",
    "    plt.xlabel('$\\phi$', fontsize=18)\n",
    "    plt.ylabel('$p(\\phi)$', fontsize=18)\n",
    "    \n",
    "    return"
   ]
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       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1200\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_p_and_g()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "We start by using the ordinary free energy of the pure components:\n",
    "\n",
    " * Pure A, liquid phase - $f_A^L(T)$\n",
    " * Pure A, solid phase - $f_A^S(T)$\n",
    "\n",
    "As we will be limiting ourselves to a pure material at this time, these are the only two free energies we need.  Near the melting point these free energies are often modeled as straight lines using the relationship for the Gibbs free energy:\n",
    "\n",
    "$$G = H - TS$$\n",
    "\n",
    "taking H and S to be constants.  Following conventions of the phase diagram modeling community we take the reference state of the component A to be the equilibrium phase at STP.  If this were a metal like Cu then the reference state would be the FCC phase.  For us, that will be the SOLID.  This sets:\n",
    "\n",
    "$$f_A^S(T) = 0$$\n",
    "\n",
    "Expanding the difference in free energy between the solid and the liquid around the melting point results in:\n",
    "\n",
    "$$f_A^L(T)-f_A^S(T) = L_A \\frac{(T_M^A - T)}{T_M^A}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "The next step is to homogenize the free energy for component A.  We build the free energy $f(\\phi,T)_A$ as follows:\n",
    "\n",
    "$$f(\\phi,T)_A = W_A~g(\\phi) + f_L p(\\phi) + f_S (1-p(\\phi))$$\n",
    "\n",
    "so that:\n",
    "\n",
    "$$f(\\phi,T)_A = W_A~g(\\phi) + L_A \\frac{(T_M^A - T)}{T_M^A}p(\\phi)$$\n",
    "\n",
    "Let us plot this and see what it looks like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from matplotlib.ticker import LinearLocator, FormatStrFormatter\n",
    "\n",
    "def plot_homogeneous_F():\n",
    "    plt.fig = plt.figure(2, figsize=(10,10))\n",
    "    plt.ax = plt.fig.gca(projection='3d')\n",
    "\n",
    "    phi = np.linspace(0.0, 1.0, 100)\n",
    "    temperature = np.linspace(0.0, 1.0, 100)\n",
    "    phi,temperature = np.meshgrid(phi,temperature)\n",
    "\n",
    "    W=30.0\n",
    "    L=1.0\n",
    "    Tm=0.5\n",
    "    g=phi**2*(1-phi)**2\n",
    "    p=phi**3*(6*phi**2-15*phi+10)\n",
    "\n",
    "    f = W*g+L*p*(Tm-temperature)/Tm\n",
    "\n",
    "    energyPlot = plt.ax.plot_surface(phi, temperature, f, label=None, \n",
    "                    cmap=plt.cm.coolwarm, rstride=5, cstride=5, alpha=0.5)\n",
    "    energyPlot = plt.contour(phi, temperature, f,20)\n",
    "\n",
    "    plt.clabel(energyPlot, inline=1, fontsize=10)\n",
    "    plt.ax.set_xlabel('$\\phi$')\n",
    "    plt.ax.set_ylabel('T')\n",
    "    plt.ax.set_zlabel('$f(\\phi,t)$')\n",
    "    \n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_homogeneous_F()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$L(\\phi,\\nabla\\phi) = \\int_V \\Big[ ~~f(\\phi,T) + \\frac{\\epsilon^2_\\phi}{2}|\\nabla \\phi|^2~\\Big]~ dV$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "From here it should be clear that the free energy space is homogeneous in the order parameter and temperature.  Now that the description of the bulk energy is complete we can return to the Euler-Lagrange equations and proceed to develop our equilibrium solution and our equations of motion."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "[Top of Page](#Sections)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "#### Analytical Solution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "The full expression for the equation of motion is:\n",
    "\n",
    "$$\\frac{\\partial \\phi}{\\partial t} = - M_\\phi \\epsilon^2 \n",
    "\\Big[\\nabla^2\\phi- \\frac{2W_A}{\\epsilon^2} \\phi(1-\\phi)(1-2\\phi)\\Big]-\\frac{30 M_\\phi L_A}{T_M^A}(T_M^A - T)\\phi^2(1-\\phi)^2$$\n",
    "\n",
    "While this is correct - it is often not explicitly written out like this when solving the equations numerically.  Further, it is better if you don't fully expand the derivatives when attempting the analytical solution."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "There is a fair bit of algebra and a few assumptions that enable the solution to the Euler-Lagrange equation above.  I will state the procedue and leave out the gory detail.  Remember we are after the expression that gives us $\\phi(x)$.  Keep this in mind as you read through the following bullet points.\n",
    "\n",
    " * First - assume that you are at the melting temperature.  The rationale is that this is the only temperature where BOTH phases CO-EXIST.  Any other temperature and it does not make sense to discuss an interface.  This removes the second term on the RHS of the above expression.\n",
    " * Second - you can use $\\frac{d\\phi}{dx}$ as an integrating factor to take the first integral of the Euler-Lagrange equation.\n",
    " * Third - after evaluating the constant (C=0 is the answer, but, why it is zero will test your reasoning skills) the equation is seperable and can be integrated.\n",
    " \n",
    " The result is:\n",
    " \n",
    " $$\\phi(x) = \\frac{1}{2} \\Big[ 1 + \\tanh \\Big( \\frac{x}{2\\delta} \\Big) \\Big]$$\n",
    " \n",
    " where $\\delta$ is related to the W and $\\epsilon$ parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from ipywidgets import interact, fixed\n",
    "\n",
    "fig = None\n",
    "def plot_equilibrium(W=500.0, epsilon=1.0):\n",
    "    global fig\n",
    "    if fig: plt.close(fig)\n",
    "    fig = plt.figure()\n",
    "    x = np.linspace(-1.0, 1.0, 200)\n",
    "    phi = 0.5*(1+np.tanh(x*np.sqrt(2*W)/(2*epsilon)))\n",
    "    plt.plot(x, phi, linewidth=1.0)\n",
    "    plt.xlabel('$x$', fontsize=24)\n",
    "    plt.ylabel('$\\phi(x)$', fontsize=24)    \n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello!\n"
     ]
    }
   ],
   "source": [
    "print 'Hello!'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "interact(plot_equilibrium, W=(1,1000,10), epsilon=fixed(1.0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "W and $\\epsilon$ can be parameterized in terms of the surface energy and the interface thickness to make a connection with the physical world."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "[Top of Page](#Sections)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "#### Numerical Solution (FiPy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib osx\n",
    "from fipy import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "L = 1.\n",
    "nx = 400\n",
    "dx = L/nx\n",
    "mesh = Grid1D(dx=dx, nx=nx)\n",
    "phase = CellVariable(name=\"phase\",mesh=mesh)\n",
    "viewer = MatplotlibViewer(vars=(phase,),datamin=-0.1, datamax=1.1, legend=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "This cell sets the initial conditions.  There is a helper attribute cellCenters that fetches a list of the x points.  The setValue helper functions and the 'where' keyword help you to set the initial conditions.  FiPy is linked to Matplotlib and once you created the viewer object you call .plot() to update."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "x = mesh.cellCenters\n",
    "phase.setValue(1.)\n",
    "phase.setValue(0., where=x > L/2)\n",
    "viewer.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "[Top of Page](#Sections)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "#### DIY:  Code the terms to complete the phase field description."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\\frac{\\partial \\phi}{\\partial t} = - M_\\phi \\epsilon^2 \n",
    "\\Big[\\nabla^2\\phi- \\frac{2W_A}{\\epsilon^2} \\phi(1-\\phi)(1-2\\phi)\\Big]-\\frac{30 M_\\phi L_A}{T_M^A}(T_M^A - T)\\phi^2(1-\\phi)^2$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import sympy as sp\n",
    "phi = sp.symbols('phi')\n",
    "sp.init_printing()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "((1-phi)**2*(phi**2)).diff(phi).simplify()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "(phi**3*(6*phi**2-15*phi+10)).diff(phi).simplify()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "\n",
    "$$\\frac{\\partial \\phi}{\\partial t} = - M_\\phi \\Big[\\frac{\\partial f}{\\partial \\phi} - \\epsilon^2_\\phi \\nabla^2 \\phi \\Big]$$\n",
    "\n",
    "\n",
    "$$f(\\phi,T)_A = W_A~g(\\phi) + L_A \\frac{(T_M^A - T)}{T_M^A}p(\\phi)$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "eps_sqrd = 0.00025 \n",
    "M = 1.0\n",
    "W = 0.5\n",
    "Lv = 1.\n",
    "Tm = 1.\n",
    "T = 1.0\n",
    "enthalpy = Lv*(Tm-T)/Tm\n",
    "S0 = W*2.0*phase*(phase-1.0)*(2*phase-1.0) + 30*phase**2*(phase**2-2*phase+1)*enthalpy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "This is our general statement of a diffusive PDE.  There is a transient term and a source term.  Translate from the description of the phase field model above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "eq = TransientTerm() == DiffusionTerm(coeff=eps_sqrd*M) - S0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "for i in range(50):\n",
    "    eq.solve(var = phase, dt=0.1)\n",
    "    viewer.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Just re-execute this cell after you change parameters.  You can execute it over and over until you are satisfied that you've reached equilibrium."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "You can try changing $\\kappa$, W, and T.  Changing T from the melting tmperature will result in a moving interface.  This is where things get interesting!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "[Top of Page](#Sections)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "#### In 2D"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "This one is important.  We will simulate a pair of curved particles (each with a different radius) at the melting temperature.  What do you think will happen?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib osx\n",
    "from fipy import *\n",
    "\n",
    "L = 1.\n",
    "nx = 200\n",
    "dx = L/nx\n",
    "dy = L/nx\n",
    "mesh = Grid2D(dx=dx, dy=dx, nx=nx, ny=nx)\n",
    "phase = CellVariable(name=\"phase\", mesh=mesh)\n",
    "x = mesh.cellCenters()[0]\n",
    "y = mesh.cellCenters()[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "phase.setValue(1.)\n",
    "x0 = 0.0\n",
    "y0 = 0.0\n",
    "#phase.setValue(0., where=(\n",
    "#                          ((x-x0)**2+(y-y0)**2 > L/3) & ((x-L)**2+(y-L)**2 > 0.2)\n",
    "#                          )\n",
    "#               )\n",
    "phase.setValue(ExponentialNoiseVariable(mesh=mesh, mean=0.5))\n",
    "viewer = Matplotlib2DGridViewer(vars=phase, datamin=0.0, datamax=1.0)\n",
    "viewer.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "The strength of FiPy is that you can use the same code here in 2D as above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "eps_sqrd = 0.00025 \n",
    "M = 1.0\n",
    "W = 0.5\n",
    "Lv = 1.\n",
    "Tm = 1.\n",
    "T = 1.\n",
    "enthalpy = Lv*(Tm-T)/Tm\n",
    "S0 = W*2.0*phase*(phase-1.0)*(2*phase-1.0) + 30*phase**2*(phase**2-2*phase+1)*enthalpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "eq = TransientTerm() == DiffusionTerm(coeff=eps_sqrd) - S0\n",
    "for i in range(500):\n",
    "    eq.solve(var = phase, dt=0.05)\n",
    "    viewer.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "[Top of Page](#Sections)"
   ]
  }
 ],
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