02_bivar_newton_vs_descent.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bivariate Gradient Descent vs. Newton-Raphson"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"width: 100%; overflow: hidden;\">\n",
    "     <div style=\"width: 75%; float: left;\"> \n",
    "     The following example demonstrates bi-variate optimization using Gradient Descent and Newton-Raphson method. It is the goal to minimize the objective function $f(x,y)=(x-y)^4+2x^2+y^2-x+2y$ and compare the two optimization approaches. <div class=\"alert alert-block alert-info\">\n",
    "The provided example is authored by <b><a href=\"http://www.christopherhahne.de\" style=\"text-decoration: none;\">Christopher Hahne</a></b> and inspired by a <b><a href=\"https://www.math.colostate.edu/~gerhard/MATH331/lab/newton2d.html\" style=\"text-decoration: none !important;\">lab note</a></b> from Colorado State University.\n",
    " </div>\n",
    "     <br>last update: 02/10/2020\n",
    "     </div>\n",
    "     <div style=\"margin-left: 80%;\">\n",
    "        <b>Author</b><br><br>\n",
    "        <a href='http://www.christopherhahne.de', style=\"text-decoration: None; text-align: left;\">\n",
    "            <img align=\"left\" src=\"http://www.christopherhahne.de/images/about.jpg\" width=\"78\"/>\n",
    "            <br><br><br><br><br><br>\n",
    "            <b>Christopher<br>Hahne, PhD</b>\n",
    "        </a>\n",
    "    </div>\n",
    "</div>"
   ]
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   "cell_type": "markdown",
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   "source": [
    "As we aim to find the minimum of $f(x, y)$, we can take it directly as the objective function, which writes\n",
    "\n",
    "$$f(x,y)=(x-y)^4+2x^2+y^2-x+2y$$\n",
    "\n",
    "and implement it as"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "obj_fun = lambda x: (x[0]-x[1])**4 + 2*x[0]**2 + x[1]**2 - x[0] + 2*x[1]"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "To employ the gradient descent in the multivariate case, we may analytically construct its partial derivatives given by\n",
    "\n",
    "$$\\frac{\\partial f}{\\partial x}(x,y)=4(x-y)^3 + 4x-1$$\n",
    "\n",
    "$$\\frac{\\partial f}{\\partial y}(x,y)=-4(x-y)^3 + 2y+2$$\n",
    "\n",
    "This is re-written in vector form as\n",
    "\n",
    "$$\\nabla \\mathbf{F}(\\mathbf{x}) = \n",
    "    \\begin{bmatrix} \\frac{\\partial f}{\\partial x}(x,y)\\\\ \\frac{\\partial f}{\\partial y}(x,y)\\end{bmatrix} =\n",
    "      \\begin{bmatrix}  4(x-y)^3 + 4x-1 \\\\ -4(x-y)^3 + 2y+2 \\end{bmatrix}\n",
    "$$\n",
    "and implemented as"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "gradient = lambda x: [4*(x[0]-x[1])**3 + 4*x[0]-1, -4*(x[0]-x[1])**3 + 2*x[1]+2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gradient Descent\n",
    "\n",
    "The gradient descent is applicable for multivariate functions with dimensions $m$ such that $\\textbf{x}\\in\\mathbb{R}^m$ in\n",
    "\n",
    "$$\\mathbf{x}_{k+1}=\\mathbf{x}_k-\\gamma \\nabla \\mathbf{F}(\\mathbf{x}_k), \\qquad  k \\in \\mathbb{N}$$\n",
    "\n",
    "where $k$ is the iterative index, $\\nabla \\mathbf{F}(\\cdot)$ the gradient of candidate $\\mathbf{x}_k$ and $\\gamma$ the learning rate. An implementation of the gradient descent is given below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def multivar_descent(x, gradient, l=0.02, tol=1e-10, eps=1):\n",
    "    x_list = []\n",
    "    while tol<eps<100:\n",
    "        x_list.append(x.copy())\n",
    "        g = gradient(x)\n",
    "        x -= np.multiply(l, g)\n",
    "        eps = np.sum(np.abs(g)) # error\n",
    "        \n",
    "    return x_list, eps"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Newton-Raphson Method"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For minimization, the Newton-Raphson approach can be generalized to $m$ variables with the first-order derivative $\\nabla\\mathbf{F}(\\mathbf{x})\\in\\mathbb{R}^m$ from above and the second-order derivative $\\mathbf{H}(\\mathbf{x}) \\in \\mathbb{R}^{m\\times m}$ as the Hessian matrix, which in our case is given by\n",
    "\n",
    "$$\n",
    "\\mathbf H(\\mathbf{x}) = \\begin{bmatrix}\n",
    "      \\dfrac{\\partial^2 f(x,y)}{\\partial x^2} & \\dfrac{\\partial^2 f(x,y)}{\\partial x \\partial y}\\\\[1em]\n",
    "      \\dfrac{\\partial^2 f(x,y)}{\\partial y \\partial x} & \\dfrac{\\partial^2 f(x,y)}{\\partial y^2} \\end{bmatrix}\n",
    "      = \\begin{bmatrix}\n",
    "      12(x-y)^2 + 4 & -12(x-y)^2 \\\\\n",
    "      -12(x-y)^2 & 12(x-y)^2 + 2 \\end{bmatrix}\n",
    "$$\n",
    "and implemented as"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "hessian = lambda x: [[12*(x[0]-x[1])**2 + 4, -12*(x[0]-x[1])**2], [-12*(x[0]-x[1])**2, 12*(x[0]-x[1])**2 + 2]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One thus obtains the iterative scheme\n",
    "\n",
    "$$\\mathbf{x}_{k+1} = \\mathbf{x}_k - \\gamma \\big[\\mathbf H(\\mathbf{x}_k)\\big]^{-1} \\nabla\\mathbf{F}(\\mathbf{x}_k), \\qquad  k \\in \\mathbb{N}$$\n",
    "\n",
    "using the reciprocal of the second derivative with the invertible matrix of the Hessian matrix. Often this approach includes a small learning rate $ 0 < \\gamma \\le 1 $ instead of $\\gamma=1$ to ensure that the Wolfe conditions are satisfied at each iteration. For step sizes other than 1, the method is referred to as the relaxed or damped Newton's method whose implementation is provided hereafter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "def newton_hessian(x, gradient, hessian, l=1, tol=1e-10, eps=1):\n",
    "    x_list = []\n",
    "    while tol<eps<100:\n",
    "        x_list.append(x.copy())\n",
    "        g = gradient(x)\n",
    "        H = hessian(x)\n",
    "        x -= l*np.dot(np.linalg.inv(H), g)\n",
    "        eps = np.sum(np.abs(g)) # error\n",
    "        \n",
    "    return x_list, eps"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gradient descent solution found at [ 0.03349047 -0.56698094] in 433 iterations with error 9.920952948050399e-12.\n",
      "Newton method solution found at [ 0.03349047 -0.56698094] in 283 iterations with error 9.394707234378075e-12.\n"
     ]
    },
    {
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       "    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 http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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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AAAORgAIAAAAAAAAOBgBIAAAAAAAAOBgBIAAAAAAAACAgxEAAgAAAAAAAA5GAAgAAAAAAAA4GAEgAAAAAAAA4GD/B0LEj3u1YXvgAAAAAElFTkSuQmCC\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8d00ef0290>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "start_vals = [1., -1.]\n",
    "tol = 1e-11\n",
    "l=0.02\n",
    "pts_dsc, eps = multivar_descent(start_vals, gradient, l, tol=tol)\n",
    "print('Gradient descent solution found at %s in %s iterations with error %s.' % (pts_dsc[-1], len(pts_dsc), eps))\n",
    "l=0.1\n",
    "pts_hes, eps = newton_hessian(start_vals, gradient, hessian, l, tol)\n",
    "print('Newton method solution found at %s in %s iterations with error %s.' % (pts_hes[-1], len(pts_hes), eps))\n",
    "\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "plt.semilogx(range(len(pts_dsc)), np.sum(pts_dsc, -1), label='Gradient Descent')\n",
    "plt.semilogx(range(len(pts_hes)), np.sum(pts_hes, -1), label='Newton Method')\n",
    "#plt.xlim([1, max(len(pts_dsc), len(pts_hes))])\n",
    "plt.xlabel('Iterations $k$')\n",
    "plt.ylabel('Result $\\mathbf{x}$')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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 http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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"
    },
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width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8d00670d10>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# compute grid\n",
    "s = 1\n",
    "x = np.linspace(-1*s, 1*s, int(20*s)+1)\n",
    "y = np.linspace(-1*s, 1*s, int(20*s)+1)\n",
    "xx, yy = np.meshgrid(x, y)\n",
    "zz = obj_fun([xx, yy])\n",
    "\n",
    "# import plot libs\n",
    "%matplotlib inline\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from matplotlib import cm\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# plot functions\n",
    "fig, ax = (plt.figure(figsize=(8, 3)), plt.axes(projection='3d'))\n",
    "ax.scatter(xx, yy, zz, c=zz/zz.max(), cmap=cm.jet, linewidth=.5, s=5, label='$f(x, y)$')\n",
    "#ax.plot_wireframe(xx, yy, zz, cmap=cm.jet, linewidth=.5, color='orange', label='$f(x, y)$')\n",
    "#ax.plot_trisurf(xx.flatten(), yy.flatten(), zz.flatten(), cmap=cm.jet, linewidth=.2, label='$f(x, y)$')\n",
    "\n",
    "# initial guess and solution\n",
    "pts = pts_hes #pts_dsc\n",
    "ax.scatter(pts[0][0], pts[0][1], obj_fun(pts[0]), s=40, marker='x', color='k', label='Initial guess')\n",
    "ax.scatter(pts[-1][0], pts[-1][1], obj_fun(pts[-1]), s=40, marker='x', color='red', label='Solution')\n",
    "\n",
    "# plot gradient steps\n",
    "x_p = pts[0]\n",
    "z_p = obj_fun(x_p)\n",
    "for x_k in pts[1:min(25, len(pts))]:\n",
    "    z_k = obj_fun(x_k)\n",
    "    ax.quiver(x_p[0], x_p[1], z_p, x_k[0]-x_p[0], x_k[1]-x_p[1], z_k-z_p, linewidth=1, color='green')\n",
    "    x_p, z_p = x_k, z_k\n",
    "\n",
    "ax.legend()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}