Interactive_Optimization.ipynb

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    "\n",
    "<p align=\"center\">\n",
    "    <img src=\"https://github.com/GeostatsGuy/GeostatsPy/blob/master/TCG_color_logo.png?raw=true\" width=\"220\" height=\"240\" />\n",
    "\n",
    "</p>\n",
    "\n",
    "## Subsurface Data Analytics \n",
    "\n",
    "## Interactive Gradient Descent\n",
    "\n",
    "#### Michael Pyrcz, Associate Professor, University of Texas at Austin \n",
    "\n",
    "##### [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](https://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1) | [GeostatsPy](https://github.com/GeostatsGuy/GeostatsPy)\n",
    "\n",
    "\n",
    "### PGE 383 Exercise: Interactive Gradient Descent\n",
    "\n",
    "Here's a simple demonstration of gradient descent. \n",
    "\n",
    "* I also have a lecture that describes the basics of optimization for machine learning model training, [Optimization Lecture](https://www.youtube.com/watch?v=4nYz5j0sAQs&list=PLG19vXLQHvSC2ZKFIkgVpI9fCjkN38kwf&index=23&t=578s) that may be helpful.\n",
    "\n",
    "In this demonstration you will be able to take a customimizable loss function.\n",
    "\n",
    "* you can vary the magnitude and spatial correlation of the noise\n",
    "\n",
    "* **magnitude of noise** is controlled by the standard deviation of a Gaussian random residual \n",
    "\n",
    "* **spatialcorrelation of noise** is controlled by the size of a Gaussian kernal applied to convolve the random noise to impose spatial structure \n",
    "\n",
    "Then you can set the:\n",
    "\n",
    "* **initial parameter combination** ($\\phi_1, \\phi_2$)\n",
    "\n",
    "* **initial learning rate** \\[0.1,5\\]\n",
    "\n",
    "* **momentum** \\[0.0,1.0\\]\n",
    "\n",
    "* **exponential decay coefficient**\n",
    "\n",
    "#### Import Required Packages\n",
    "\n",
    "We will also need some standard packages. These should have been installed with Anaconda 3."
   ]
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  {
   "cell_type": "code",
   "execution_count": 31,
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    "%matplotlib inline\n",
    "%matplotlib notebook\n",
    "import sys                                              # supress output to screen for interactive variogram modeling                                             \n",
    "import math                                             # square root operator\n",
    "import numpy as np                                      # arrays and matrix math\n",
    "import matplotlib.pyplot as plt                         # plotting\n",
    "import scipy                                            # kernel for convolution\n",
    "from ipywidgets import interactive                      # widgets and interactivity\n",
    "from ipywidgets import widgets                            \n",
    "from ipywidgets import Layout\n",
    "from ipywidgets import Label\n",
    "from ipywidgets import VBox, HBox\n",
    "from scipy.interpolate import griddata\n",
    "from matplotlib.animation import FuncAnimation\n",
    "import scipy.signal as signal\n",
    "from scipy.interpolate import RegularGridInterpolator\n",
    "from matplotlib import animation"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "#### Set the Parameters for The Demonstration\n",
    "\n",
    "Here we set the grid size and extent, and color map applied in this demonstration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx = 100; ny = 100                                      # size of the loss function grid\n",
    "cmap = plt.cm.inferno                                   # set the colormap\n",
    "xmin = 0.0; xmax = 100.0; ymin = 0.0; ymax = 100.0      # set the extents\n",
    "X, Y = np.mgrid[ymin:ymax:complex(ny), 0:100:complex(nx)] # make location mesh for interpolation method\n",
    "XY = np.vstack((Y.flatten(), X.flatten())).T            \n",
    "XY_list = list(map(tuple, XY))                           \n",
    "x = np.zeros(100); y = np.zeros(100)                    # initialize the descent path\n",
    "truth = np.zeros([100,100])                             # initialize the 2D loss function map\n",
    "np.random.seed(73073)                                   # set random number seed for repeatable results"
   ]
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   "cell_type": "markdown",
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   "source": [
    "#### Make the Exhaustive Loss Function\n",
    "\n",
    "Let's ensure a global minimum in the middle of the solution space and add some structured noise to increase the difficulty\n",
    "\n",
    "* local minimums for gradient descent to get stuck"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
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       "        }\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 https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from https://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",
       " * https://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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // 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=\"863.1833333333333\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Gradient Descent')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make the truth loss function\n",
    "nsmooth = 20                                            # controls the spatial continuity in the noise, in cells\n",
    "noise_std = 80.0\n",
    "\n",
    "for iy in range(100):\n",
    "    for ix in range(100):\n",
    "        truth[iy,ix] = math.sqrt((iy-50)*(iy-50) + (ix-50)*(ix-50))\n",
    "\n",
    "noise = np.random.normal(loc=0.0, scale=1.0, size=(100,100))\n",
    "w = np.ones((nsmooth,nsmooth))/(nsmooth*nsmooth)\n",
    "\n",
    "gkern1d = signal.gaussian(nsmooth, std=nsmooth*0.2).reshape(nsmooth, 1); gkern2d = np.outer(gkern1d, gkern1d) # Teddy Hartanto, 2017, stack overflow \n",
    "gkern2d = gkern2d/np.sum(gkern2d.flatten())\n",
    "\n",
    "noise = signal.convolve2d(noise,gkern2d,mode = 'same',boundary='symm')   \n",
    "\n",
    "truth = truth + noise*noise_std\n",
    "\n",
    "truth = (truth - np.min(truth))/(np.max(truth) - np.min(truth))*100.0\n",
    "\n",
    "# initialize the fast interpolator to evaluate the loss function at any location\n",
    "interp = RegularGridInterpolator((np.linspace(ymin,ymax,ny),np.linspace(xmin,xmax,nx)),truth, method = 'linear')\n",
    "x = np.zeros(100); y = np.zeros(100)                          # descent path arrays\n",
    "\n",
    "fig = plt.figure(figsize = (12,10)); ax = plt.gca()\n",
    "plt.xlim([0,100]); plt.ylim([0,100])\n",
    "c1 = ax.contourf(X, Y, truth, cmap = plt.cm.inferno,vmin=0,vmax=100,levels=np.linspace(0, 100, 50))\n",
    "ax.contour(X, Y, truth, levels=10, linewidths=0.5, colors='black',linestyles='dashed') \n",
    "cbar = plt.colorbar(c1);\n",
    "cbar.set_label('Loss Function',rotation = 270,labelpad = 20)\n",
    "plt.rc('xtick', labelsize=10); plt.rc('ytick', labelsize=10) \n",
    "plt.rc('axes', titlesize=20); plt.rc('axes', labelsize=15)\n",
    "plt.xlabel(r'$\\phi_1$'); plt.ylabel(r'$\\phi_2$'); plt.title('Gradient Descent')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Set Parameters for this Model Run and Run the Animation\n",
    "\n",
    "You can change the following parameters and then watch the animation of the gradient descent path.\n",
    "\n",
    "* **r** - learning rate (distance units of the \\[0,100\\] parmaeter space \n",
    "* **momentum - momentum weight (weight on the previous step), from \\[0.0 - no mommentum, 1.0 - next step is previous step\\]\n",
    "* **make_video** - False, run and visualize, True, only make the specified mpeg video file\n",
    "* **x\\[0\\]**, **y\\[0\\]** - initial location for descent path \n",
    "* **delta** - offset applied for numerical differentiation to calculate the local gradient by sampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "r0 = 10.0                                    # initial learning rate\n",
    "momentum = 0.9                               # momentum                         \n",
    "delta = 0.001                                # delta for numerical differentiation of the loss function\n",
    "k = 0.04                                     # exponential decay parameter\n",
    "x = np.zeros(100); y = np.zeros(100)         # initialize the descent path array\n",
    "x[0] = 5.0; y[0] = 50.0                      # initial location in the parameter space\n",
    "make_video = False                           # make a video (True or False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Gradient Descent Path Animation \\#1\n",
    "\n",
    "The following animation shows the gradient descent path given the above loss function and gradient descent parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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 https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from https://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",
       " * https://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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // 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=\"863.1833333333333\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.close()\n",
    "# set up the plot\n",
    "fig = plt.figure(figsize = (12,10))\n",
    "ax = plt.gca()\n",
    "ax.set_xlim([xmin,xmax]); ax.set_ylim([ymin,ymax])\n",
    "ax.set_xlabel(r'$\\phi_1$'); ax.set_ylabel(r'$\\phi_2$'); ax.set_title('Gradient Descent Optimization')\n",
    "plt.rc('xtick', labelsize=10); plt.rc('ytick', labelsize=10) \n",
    "plt.rc('axes', titlesize=20); plt.rc('axes', labelsize=15) \n",
    "point, = ax.plot([],[], marker=\"o\",c='white', \n",
    "            markeredgecolor = \"black\", ms=30, alpha = 0.5)\n",
    "cbar = plt.colorbar(c1);\n",
    "cbar.set_label('Loss Function',rotation = 270,labelpad = 20)\n",
    "global line\n",
    "\n",
    "x = np.clip(x,xmin+delta,xmax-delta); y = np.clip(y,ymin+delta,ymax-delta) # ensure start is not too close to edge\n",
    "for i in range(1,100):    \n",
    "    gradient_x = (interp((y[i-1], x[i-1]+delta)).item()-interp((y[i-1], x[i-1]-delta)).item())/(2*delta)\n",
    "    gradient_y = (interp((y[i-1]+delta, x[i-1])).item()-interp((y[i-1]-delta, x[i-1])).item())/(2*delta)\n",
    "    \n",
    "    r = r0 * math.exp(-k*i)    \n",
    "    \n",
    "    if i > 1: # include mommentum\n",
    "        x_step = momentum*prev_x + (1.0-momentum)*(-1*r*gradient_x) # integrat momentum\n",
    "        y_step = momentum*prev_y + (1.0-momentum)*(-1*r*gradient_y) # integrat momentum\n",
    "    else: \n",
    "        x_step = -1*r*gradient_x \n",
    "        y_step = -1*r*gradient_y \n",
    "      \n",
    "    x[i] = x[i-1] + x_step                   # step forward\n",
    "    y[i] = y[i-1] + y_step \n",
    "    \n",
    "    x[i] = np.clip(x[i],xmin+delta,xmax-delta); y[i] = np.clip(y[i],ymin+delta,ymax-delta) # ensure point is not too close to edge\n",
    "\n",
    "    prev_x = (x[i] - x[i-1])                 # store current step for momentum on next step\n",
    "    prev_y = (y[i] - y[i-1])\n",
    "               \n",
    "def init():                                  # animation initialization function\n",
    "    ax = plt.gca()\n",
    "    c1 = ax.contourf(X, Y, truth, cmap = plt.cm.inferno,vmin=0,vmax=100,levels=np.linspace(0, 100, 50))\n",
    "    ax.contour(X, Y, truth, levels=10, linewidths=0.5, colors='black',linestyles='dashed') \n",
    "    \n",
    "def update(frame):                          # animation steps over frames\n",
    "    N = 10\n",
    "    ax = plt.gca()\n",
    "    N = min(N,frame)\n",
    "    top = min(frame,90)\n",
    "    point.set_data(x[frame-N:top],y[frame-N:top])\n",
    "\n",
    "ani = FuncAnimation(fig, update, frames = np.arange(1, len(x)-20), init_func = init, # make the animation\n",
    "    interval=100, blit=True, repeat = False)\n",
    "\n",
    "if make_video:                               # set up formatting for the movie files\n",
    "    writer = animation.FFMpegWriter(fps=15, metadata=dict(artist='Michael Pyrcz'), bitrate=100000)\n",
    "    ani.save('gradient_descent.mp4', writer=writer)\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Gradient Descent Path Animation \\#2\n",
    "\n",
    "Here's another animation that shows the gradient descent path given the above loss function and gradient descent parameters.\n",
    "\n",
    "* this time we provide the path and do not repeat the animation\n",
    "\n",
    "* I thought this would be a useful alternative to visualize this information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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 https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from https://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",
       " * https://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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // 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=\"863.1833333333333\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set up the plot\n",
    "fig = plt.figure(figsize = (12,10))\n",
    "ax = plt.gca()\n",
    "ax.set_xlim([xmin,xmax]); ax.set_ylim([ymin,ymax])\n",
    "ax.set_xlabel(r'$\\phi_1$'); ax.set_ylabel(r'$\\phi_2$'); ax.set_title('Gradient Descent Optimization')\n",
    "plt.rc('xtick', labelsize=10); plt.rc('ytick', labelsize=10) \n",
    "plt.rc('axes', titlesize=20); plt.rc('axes', labelsize=15) \n",
    "point, = ax.plot([],[], marker=\"o\",c=plt.cm.inferno((interp((x[0],y[0])).item())/100), \n",
    "            markeredgecolor = \"white\", ms=15, alpha = 1.0)\n",
    "cbar = plt.colorbar(c1);\n",
    "cbar.set_label('Loss Function',rotation = 270,labelpad = 20)\n",
    "global line\n",
    "\n",
    "x = np.clip(x,xmin+delta,xmax-delta); y = np.clip(y,ymin+delta,ymax-delta) # ensure start is not too close to edge\n",
    "\n",
    "for i in range(1,100):    \n",
    "    gradient_x = (interp((y[i-1], x[i-1]+delta)).item()-interp((y[i-1], x[i-1]-delta)).item())/(2*delta)\n",
    "    gradient_y = (interp((y[i-1]+delta, x[i-1])).item()-interp((y[i-1]-delta, x[i-1])).item())/(2*delta)\n",
    "    \n",
    "    r = r0 * math.exp(-k*i)    \n",
    "    \n",
    "    if i > 1: # include mommentum\n",
    "        x_step = momentum*prev_x + (1.0-momentum)*(-1*r*gradient_x) # integrat momentum\n",
    "        y_step = momentum*prev_y + (1.0-momentum)*(-1*r*gradient_y) # integrat momentum\n",
    "    else: \n",
    "        x_step = -1*r*gradient_x \n",
    "        y_step = -1*r*gradient_y \n",
    "      \n",
    "    x[i] = x[i-1] + x_step                               # step forward\n",
    "    y[i] = y[i-1] + y_step \n",
    "    \n",
    "    x[i] = np.clip(x[i],xmin+delta,xmax-delta); y[i] = np.clip(y[i],ymin+delta,ymax-delta) # ensure point is not too close to edge\n",
    "\n",
    "    prev_x = (x[i] - x[i-1])                              # store current step for momentum on next step\n",
    "    prev_y = (y[i] - y[i-1])\n",
    "               \n",
    "def init():                                             # animation initialization function\n",
    "    ax = plt.gca()\n",
    "    c1 = ax.contourf(X, Y, truth, cmap = plt.cm.inferno,vmin=0,vmax=100,levels=np.linspace(0, 100, 50))\n",
    "    ax.contour(X, Y, truth, levels=10, linewidths=0.5, colors='black',linestyles='dashed') \n",
    "    \n",
    "def update(frame):\n",
    "    N = 5\n",
    "    ax = plt.gca()     \n",
    "    point.set_data(x[frame],y[frame])\n",
    "    point.set_color(plt.cm.inferno((interp((y[frame],x[frame])).item())/100))\n",
    "    line, = plt.plot(x[:frame],y[:frame],c='white',alpha=0.05,linewidth=5)\n",
    "\n",
    "ani = FuncAnimation(fig, update, frames = np.arange(1, len(x)), init_func = init, # make the animation\n",
    "    interval=100, blit=True, repeat = False)\n",
    "\n",
    "if make_video:                                               # set up formatting for the movie files\n",
    "    writer = animation.FFMpegWriter(fps=15, metadata=dict(artist='Me'), bitrate=1800)\n",
    "    ani.save('gradient_descent.mp4', writer=writer)\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Comments\n",
    "\n",
    "This was a basic demonstration of gradient descent optimization, commonly applied to train machine learning models. \n",
    "\n",
    "* I have many other demonstrations and even basics of working with DataFrames, ndarrays, univariate statistics, plotting data, declustering, data transformations and many other workflows available at https://github.com/GeostatsGuy/PythonNumericalDemos and https://github.com/GeostatsGuy/GeostatsPy. \n",
    "\n",
    "* Also, check out my YouTube channel. I put all my university lectures online [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig). \n",
    "  \n",
    "#### The Author:\n",
    "\n",
    "### Michael Pyrcz, Associate Professor, University of Texas at Austin \n",
    "*Novel Data Analytics, Geostatistics and Machine Learning Subsurface Solutions*\n",
    "\n",
    "With over 17 years of experience in subsurface consulting, research and development, Michael has returned to academia driven by his passion for teaching and enthusiasm for enhancing engineers' and geoscientists' impact in subsurface resource development. \n",
    "\n",
    "For more about Michael check out these links:\n",
    "\n",
    "#### [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](https://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1)\n",
    "\n",
    "#### Want to Work Together?\n",
    "\n",
    "I hope this content is helpful to those that want to learn more about subsurface modeling, data analytics and machine learning. Students and working professionals are welcome to participate.\n",
    "\n",
    "* Want to invite me to visit your company for training, mentoring, project review, workflow design and / or consulting? I'd be happy to drop by and work with you! \n",
    "\n",
    "* Interested in partnering, supporting my graduate student research or my Subsurface Data Analytics and Machine Learning consortium (co-PIs including Profs. Foster, Torres-Verdin and van Oort)? My research combines data analytics, stochastic modeling and machine learning theory with practice to develop novel methods and workflows to add value. We are solving challenging subsurface problems!\n",
    "\n",
    "* I can be reached at mpyrcz@austin.utexas.edu.\n",
    "\n",
    "I'm always happy to discuss,\n",
    "\n",
    "*Michael*\n",
    "\n",
    "Michael Pyrcz, Ph.D., P.Eng. Associate Professor The Hildebrand Department of Petroleum and Geosystems Engineering, Bureau of Economic Geology, The Jackson School of Geosciences, The University of Texas at Austin\n",
    "\n",
    "#### More Resources Available at: [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](https://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1)  \n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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