007_GaussQuadrature2D.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from scipy.optimize import root\n",
    "import matplotlib\n",
    "matplotlib.use(\"nbagg\")\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from matplotlib import cm\n",
    "import matplotlib.pyplot as plt\n",
    "from jupyterthemes import jtplot\n",
    "jtplot.style()\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [],
   "source": [
    "import quadpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "scheme = quadpy.triangle.hammer_marlowe_stroud_3()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0. , 0.5, 0.5],\n",
       "       [0.5, 0. , 0.5],\n",
       "       [0.5, 0.5, 0. ]])"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scheme.points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.33333333, 0.33333333, 0.33333333])"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scheme.weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sympy import symbols, simplify, diff, init_printing, integrate, solve, lambdify\n",
    "init_printing()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "xi, eta = symbols(\"xi, eta\", real=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "N = [(1+1.e-19*xi), xi, eta, xi*eta, xi**2, eta**2] # shape consistency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "integrals = [integrate(integrate(N[i],(xi, 0, 1-eta)), (eta, 0, 1)) for i in range(len(N))]\n",
    "numIntegrals = np.array(integrals, float)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Quadrature rule 1: (symmetry arguments)\n",
    "Let ($\\xi_i$, $\\eta_i$) be the coordinates of the gauss points and $\\omega_j$ be the weights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$\\displaystyle \\eta^{2}$"
      ],
      "text/plain": [
       " 2\n",
       "η "
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Nlam[5](xi, eta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "Nlam = [lambdify((xi, eta), N[i], \"numpy\") for i in range(len(N))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "# def getPointsWeights(z):\n",
    "#     Xi, Eta, W = z[:2], z[2:4], z[4:]\n",
    "#     Xi = np.hstack((Xi, Eta[-1]))\n",
    "#     Eta = np.hstack((Eta, Xi[-2]))\n",
    "#     W = np.hstack((W, W[0]))\n",
    "#     arr = []\n",
    "#     for i in range(len(numIntegrals)):\n",
    "#         arr.append(0.5*Nlam[i](Xi, Eta) @ W - numIntegrals[i])\n",
    "#     return arr\n",
    "\n",
    "def getPointsWeightsMedians(z):\n",
    "    Xi, Eta, W = z[:3], z[3:6], z[6:]\n",
    "    arr = []\n",
    "    for i in range(len(numIntegrals)):\n",
    "        arr.append(0.5*Nlam[i](Xi, Eta) @ W - numIntegrals[i])\n",
    "    arr.append(Xi[0]-Eta[0]) # first point\n",
    "    arr.append(-Xi[1]/2. +1./2 - Eta[1]) # second point\n",
    "    arr.append(-2.*Xi[2]+1.-Eta[2]) # third point\n",
    "    return arr\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$\\displaystyle \\left[ 0.0, \\  0.0, \\  0.0, \\  0.0, \\  0.0, \\  0.0, \\  0.0, \\  0.0, \\  0.0\\right]$"
      ],
      "text/plain": [
       "[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# guess = np.array([0.5,0.5,0.5,0.,1,1])\n",
    "guess = np.random.random(6)\n",
    "# guess_med  = np.array([1./6, 1./6, 2./3, 1./6, 2./3, 1./6, 1./3,1./3, 1./3])\n",
    "guess_med  = np.array([0.5, 0., 0.5, 0.5, 0.5, 0., 1./3,1./3, 1./3])\n",
    "getPointsWeightsMedians(guess_med)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [],
   "source": [
    "soln = root(getPointsWeights, guess, method=\"hybr\", tol=1.e-8)\n",
    "solnAll = root(getPointsWeightsMedians, np.zeros(9), method=\"hybr\", tol=1.e-13)\n",
    "# soln"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solution: [0.16666667 0.66666667 0.16666667 0.16666667 0.16666667 0.66666667\n",
      " 0.33333333 0.33333333 0.33333333], \n",
      "message: The solution converged., \n",
      "function: [0.0, -5.551115123125783e-17, 0.0, 2.0816681711721685e-17, -5.551115123125783e-17, 0.0, 0.0, 2.7755575615628914e-17, 0.0]\n"
     ]
    }
   ],
   "source": [
    "print(\"Solution: {}, \\nmessage: {}, \\nfunction: {}\".format(solnAll.x, solnAll.message,\n",
    "                                                       getPointsWeightsMedians(solnAll.x)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Problem 2\n",
    " $$\\int_T (2-x - 2 y + 3 x^2 + 4xy - 2y^2) $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [],
   "source": [
    "x1, x2, x3 = 0, 1, 0\n",
    "y1, y2, y3 = 0, 1/2. , 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
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       "        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",
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       "\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"
    },
    {
     "data": {
      "text/html": [
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<mpl_toolkits.mplot3d.art3d.Line3D at 0x7f5f8dbb7208>]"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xT, yT = np.meshgrid(np.linspace(0,1,50), np.linspace(0,1,50))\n",
    "fig=plt.figure(figsize=(10,8))\n",
    "ax = fig.gca(projection=\"3d\")\n",
    "surfT = ax.plot_surface(xT, yT, 2-xT-2*yT + 3*xT**2 + 4*xT*yT-2*yT**2, cmap=cm.jet)\n",
    "fig.colorbar(surfT, shrink=0.5)\n",
    "ax.plot([x1, x2, x3, x1], [y1, y2, y3, y1], \"-ko\", zs=0, zdir=\"z\", lw=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x, y = symbols(\"x, y\", real=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = xi*x1 + eta*x2 + (1-xi-eta)*x3\n",
    "y = xi*y1 + eta*y2 + (1-xi-eta)*y3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sympy import Matrix\n",
    "J = Matrix([[x.diff(xi), x.diff(eta)], [y.diff(xi), y.diff(eta)]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "f = 2 - x - 2*y + 3*x**2 + 4*x*y - 2*y**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Aexact = integrate(integrate(f*J.det(), (xi, 0, 1-eta)), (eta, 0, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "xiv, etav, _ = scheme.points.T\n",
    "Anum = 0\n",
    "for i in range(xiv.shape[0]):\n",
    "    Anum += (f*J.det()).subs([(xi, xiv[i]), (eta, etav[i])])*scheme.weights[i]\n",
    "simplify(Aexact - 1./2*Anum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scheme = quadpy.triangle.hammer_marlowe_stroud_4()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "xiv, etav, _ = scheme.points.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Anum = 0\n",
    "for i in range(xiv.shape[0]):\n",
    "    Anum += (f*J.det()).subs([(xi, xiv[i]), (eta, etav[i])])*scheme.weights[i]\n",
    "simplify(Aexact - 1./2*Anum)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Problem 3: \n",
    "$$ \\int_\\mathcal{Q} 1 + 3x - 2y + 9x^2 - 4xy + 27y^2$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "N1L = lambda x: [(1-x)/2, (1+x)/2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sympy import tensorproduct, flatten"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "shp = flatten(simplify(tensorproduct(N1L(xi), N1L(eta))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "xvals = np.array([0., 2, 3/2, 0])\n",
    "yvals = np.array([0., 1, 1/2, 3])\n",
    "X,Y = np.meshgrid(np.linspace(xvals.min(), xvals.max(), 50),\n",
    "                  np.linspace(yvals.min(), yvals.max(), 50))\n",
    "fig = plt.figure()\n",
    "ax = fig.gca(projection=\"3d\")\n",
    "ax.plot(np.hstack((xvals[[0, 2, 1, 3]], xvals[0])),\n",
    "        np.hstack((yvals[[0, 2, 1, 3]], yvals[0])), \"-ko\", zs = 0, zdir=\"z\", lw=3)\n",
    "ax.plot_surface(X,Y, 1. + 3.*X - 2.*Y + 9*X**2 - 4*X*Y + 27*Y**2, cmap = cm.jet)\n",
    "ax.set_xlabel(r\"x\", fontsize=14)\n",
    "ax.set_ylabel(r\"y\", fontsize=14)\n",
    "ax.set_zlabel(r\"f(x,y)\", fontsize=14)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "shp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rearranging the points\n",
    "xQ = shp @ xvals[[0, 3, 2, 1]]\n",
    "yQ = shp @ yvals[[0, 3, 2, 1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "JQ = Matrix([[xQ.diff(xi), xQ.diff(eta)], [yQ.diff(xi), yQ.diff(eta)]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "J = simplify(JQ.det())\n",
    "Jfunc = lambdify((xi,eta), J, \"numpy\")\n",
    "xi_vals = np.linspace(-1,1,51)\n",
    "XI, ETA = np.meshgrid(xi_vals, xi_vals)\n",
    "fig1 = plt.figure(figsize=(8,8))\n",
    "ax1 = fig1.gca(projection=\"3d\")\n",
    "ax1.plot_surface(XI, ETA, Jfunc(XI, ETA), cmap = cm.jet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Aq_exact = integrate((1 + 3*xQ - 2*yQ + 9*xQ**2 - 4*xQ*yQ + 27*yQ**2)*J,\n",
    "                     (xi, -1, 1), (eta, -1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy.polynomial.legendre import leggauss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Aq_exact"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pts, wg = leggauss(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "func = simplify(1 + 3*xQ - 2*yQ + 9*xQ**2 - 4*xQ*yQ + 27*yQ**2)*J"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "func"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ptsQ = np.meshgrid(pts, pts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ptsQ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ptsQ[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ptsQ[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fun = lambdify((xi, eta), func, \"numpy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Aq_Gaussian = np.sum(fun(ptsQ[0], ptsQ[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "abs(Aq_Gaussian - Aq_exact)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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