advdiff.ipynb

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   "source": [
    "# Advection-Diffusion Equation\n",
    "\n",
    "Jupyter script to illustrate numerical integration, using upwind and central finite differences.\n",
    "\n",
    "Philipp Schlatter, October 2021\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pZrvvs2kSDDM"
   },
   "source": [
    "## Preliminaries\n",
    "\n",
    "Initialisation of the graphics:"
   ]
  },
  {
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      "displayName": "Philipp Schlatter",
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   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.pylab as pylab\n",
    "import matplotlib.animation\n",
    "from math import pi\n",
    "params = {'legend.fontsize': 12,\n",
    "          'legend.loc':'best',\n",
    "          'figure.figsize': (8,5),\n",
    "          'lines.markerfacecolor':'none',\n",
    "          'axes.labelsize': 12,\n",
    "          'axes.titlesize': 12,\n",
    "          'xtick.labelsize':12,\n",
    "          'ytick.labelsize':12,\n",
    "          'grid.alpha':0.6}\n",
    "pylab.rcParams.update(params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "IEFwjbRzSDDO"
   },
   "source": [
    "Definition of our initial condition, domain size and discretisation points. Here, we take either a wave packet, simply defined as \n",
    "\n",
    "$$f_1(x) = \\sin(2 x) \\cdot e^{-x^2/20} \\ ,$$\n",
    "\n",
    "or a square wave (top-hat signal, $f_2(x)$). A third option is a single blop centred around $x=0$,\n",
    "\n",
    "$$f_3(x) = \\cos(x/5) \\cdot e^{-x^2/10} \\ .$$\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {
    "executionInfo": {
     "elapsed": 204,
     "status": "ok",
     "timestamp": 1633636125693,
     "user": {
      "displayName": "Philipp Schlatter",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgHNqDMoaWsF9tVuJ60Ac_YEfqJKF_MQZZeS_Bhieg=s64",
      "userId": "08539669643645971775"
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     "user_tz": -120
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    "id": "zjJtjwACSDDO"
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   "outputs": [],
   "source": [
    "# Wavepacket\n",
    "f1 = lambda  x: np.sin(2*x)*np.exp(-x**2/20)\n",
    "# Square wave (top-hat function)\n",
    "f2 = lambda x: np.array([1 if (t>=-18 and t<=-16) else 0 for t in x])\n",
    "# one blob\n",
    "f3 = lambda x: np.cos(x/5)*np.exp(-x**2/10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "executionInfo": {
     "elapsed": 6,
     "status": "ok",
     "timestamp": 1633636127514,
     "user": {
      "displayName": "Philipp Schlatter",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgHNqDMoaWsF9tVuJ60Ac_YEfqJKF_MQZZeS_Bhieg=s64",
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   "source": [
    "# physical quantities\n",
    "L=40\n",
    "T=40\n",
    "c=2\n",
    "\n",
    "# numerical quantities\n",
    "nx=200\n",
    "dt=0.1\n",
    "\n",
    "# create data\n",
    "dx=L/nx    \n",
    "x=np.linspace(-L/2,L/2,num=nx,endpoint=False)\n",
    "nt = int(T/dt)+1\n",
    "t=np.linspace(0,T,num=nt)\n",
    "\n",
    "# set initial condition (f1, f2 or f3)\n",
    "u0=f1(x)"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {
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     "base_uri": "https://localhost:8080/",
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    "executionInfo": {
     "elapsed": 665,
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     "timestamp": 1633636130320,
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      "displayName": "Philipp Schlatter",
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   "outputs": [
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       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
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       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
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       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
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       "\n",
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       "    var x0 = msg['x0'] / fig.ratio;\n",
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       "    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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "        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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" 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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot initial condition    \n",
    "pp=plt.figure()\n",
    "plt.title('Initial condition')\n",
    "plt.plot(x,u0,'.-b',lw=1,label='initial condition')\n",
    "plt.xlabel(r'$x$')\n",
    "plt.ylabel(r'$f^\\prime(x)$')\n",
    "plt.grid()\n",
    "plt.legend(loc='upper right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JdDq_rwoSDDQ"
   },
   "source": [
    "\n",
    "---\n",
    "\n",
    "## Advection Equation\n",
    "\n",
    "In a first step, we consider the advection equation, i.e. the differential equation\n",
    "\n",
    "$$\\frac{\\partial u}{\\partial t} + c\\frac{\\partial u}{\\partial x} = 0 \\ .$$\n",
    "\n",
    "The solution can be obtained via the method of characteristics, and yields\n",
    "\n",
    "$$u(x,t) = u(x-ct,0) = u_0(x-ct)$$\n",
    "\n",
    "with the initial condition $u_0(x)$. In a periodic domain ($u(-20)=u(20)$), we do not need to provide addition inflow/outflow conditions (discussion related to type of partical differential equation, see course literature).\n",
    "\n",
    "Compute the numerical solution, using an upwind scheme in space and time (**FTBS** - forward time backward space). This scheme is, as discussed earlier, stable for Courant number $$0<\\sigma=c\\frac{\\Delta t}{\\Delta x}<1$$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 631,
     "status": "ok",
     "timestamp": 1633635950001,
     "user": {
      "displayName": "Philipp Schlatter",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgHNqDMoaWsF9tVuJ60Ac_YEfqJKF_MQZZeS_Bhieg=s64",
      "userId": "08539669643645971775"
     },
     "user_tz": -120
    },
    "id": "xn9LxOUPSDDR",
    "outputId": "311463d8-f4f1-494c-d4e9-c3d5c4e2427e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Courant number sigma=1.00 (<=1 for stability)\n",
      "numerical viscosity nux=0.20000   nut=-0.20000\n"
     ]
    }
   ],
   "source": [
    "sigma = c*dt/dx\n",
    "nux = 0.5*c*dx\n",
    "nut = -0.5*c*dx*sigma\n",
    "print(f\"Courant number sigma={sigma:.2f} (<=1 for stability)\")\n",
    "print(f\"numerical viscosity nux={nux:.5f}   nut={nut:.5f}\")\n",
    "\n",
    "u1=np.zeros((nx,nt))\n",
    "for i in range(0,nx):\n",
    "    u1[i,0] = u0[i]\n",
    "    \n",
    "# FTBS scheme for the advection equation\n",
    "for j in range(1,nt):\n",
    "    for i in range(0,nx):\n",
    "        u1[i,j] = u1[i,j-1] - c*dt/dx*( u1[i,j-1]-u1[i-1,j-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 17
    },
    "executionInfo": {
     "elapsed": 290,
     "status": "ok",
     "timestamp": 1633635950281,
     "user": {
      "displayName": "Philipp Schlatter",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgHNqDMoaWsF9tVuJ60Ac_YEfqJKF_MQZZeS_Bhieg=s64",
      "userId": "08539669643645971775"
     },
     "user_tz": -120
    },
    "id": "bZwiODRFSDDS",
    "outputId": "75f599e5-2543-4e7a-876e-1b70750d364a"
   },
   "outputs": [
    {
     "data": {
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       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            '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",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
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       "    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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
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       "    this._init_toolbar(this);\n",
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       "    var fig = this;\n",
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       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
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       "            // Full images could contain transparency (where diff images\n",
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       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
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       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
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       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
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       "        'style',\n",
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       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
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       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
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       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "        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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plt.rcParams[\"animation.html\"] = \"jshtml\"\n",
    "#plt.ion()\n",
    "\n",
    "fig = plt.figure(figsize=(8,5))\n",
    "\n",
    "def animate(j):\n",
    "    plt.cla()\n",
    "    plt.xlabel('$x$')\n",
    "    plt.ylabel('$f^\\prime(x)$')\n",
    "    plt.grid()\n",
    "    plt.plot(x,u0,'k--',lw=1,label='initial')\n",
    "    plt.plot(x,u1[:,4*j],'r',label='ADV')\n",
    "    plt.xlim(-20,20)\n",
    "    plt.ylim(-1.1,1.1)\n",
    "    plt.title(f\"time={t[4*j]:.2f}  $\\sigma$={sigma:.2f}\")  \n",
    "    plt.legend(loc='upper right')\n",
    "    \n",
    "ani=matplotlib.animation.FuncAnimation(fig, animate, frames=int((t.size-1)/4+1), repeat=False)\n",
    "#writer = matplotlib.animation.writers['ffmpeg']\n",
    "#writer = writer(fps=24)\n",
    "#ani.save('out.mp4', writer=writer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iz6GqFFqSDDS"
   },
   "source": [
    "We can make the following observations:\n",
    "* if the Courant number is $\\sigma=1$, then the FTBS discretistaion does not introduce any numerical dissipation or dispersion, and you recover the exact solution.\n",
    "* if $\\sigma<1$, the solution will decay over time due to numerical dissipation (*dissipative scheme*)\n",
    "* for $\\sigma>1$, the FTBS scheme is unstable, i.e. the solution will grow over time and eventually explode.\n",
    "\n",
    "Play with the various parameters ($\\Delta x$, $\\Delta t$, $c$, initial condition)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "j1yuIqbeSDDS"
   },
   "source": [
    "---\n",
    "\n",
    "## Advection-Diffusion equation\n",
    "\n",
    "In a second step, we consider the advection-diffusion equation, i.e. \n",
    "\n",
    "$$ \\frac{\\partial u}{\\partial t} + c\\frac{\\partial u}{\\partial x} = \\nu \\frac{\\partial^2 u}{\\partial x^2} \\ .$$\n",
    "\n",
    "The solution is obviously pure advection for $\\nu=0$, and adds a certain amount of dissipation for $\\nu>0$. Exponential growth is expected for $\\nu<0$, and the problem is not well-posed anymore.\n",
    "\n",
    "Here we discretise the equation using explicit Euler in time and central differences in space.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 1224,
     "status": "ok",
     "timestamp": 1633635954028,
     "user": {
      "displayName": "Philipp Schlatter",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgHNqDMoaWsF9tVuJ60Ac_YEfqJKF_MQZZeS_Bhieg=s64",
      "userId": "08539669643645971775"
     },
     "user_tz": -120
    },
    "id": "d6Jij2XeSDDT",
    "outputId": "5c1a2919-fdd0-4c61-9fba-66ac3b869268"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Courant number sigma=0.50\n",
      "               beta=0.05 (<=1/2 for stability)\n",
      "sigma^2/beta =5.00 (<=2 for stability)\n",
      "numerical viscosity nux=0.10000   nut=-0.05000\n",
      "wikipedia: 10.00000 (<=2) WRONG!\n"
     ]
    }
   ],
   "source": [
    "nu = 0.02    # stable for nu=0.05, unstable for nu<0.5\n",
    "\n",
    "sigma = c*dt/dx\n",
    "beta = nu*dt/(dx**2)\n",
    "nux = 0.5*c*dx\n",
    "nut = -0.5*c*dx*sigma\n",
    "print(f\"Courant number sigma={sigma:.2f}\")\n",
    "print(f\"               beta={beta:.2f} (<=1/2 for stability)\")\n",
    "print(f\"sigma^2/beta ={sigma**2/beta:.2f} (<=2 for stability)\")\n",
    "print(f\"numerical viscosity nux={nux:.5f}   nut={nut:.5f}\")\n",
    "print(f\"wikipedia: {dx*c/nu:.5f} (<=2) WRONG!\")\n",
    "\n",
    "u2=np.zeros((nx,nt))\n",
    "for i in range(0,nx):\n",
    "    u2[i,0] = u0[i]\n",
    "    \n",
    "# FTCS scheme for the advection-diffusion equation\n",
    "for j in range(1,nt):\n",
    "    for i in range(0,nx):\n",
    "        u2[i,j] = u2[i,j-1]   \\\n",
    "                 - c*dt/(2*dx)*( u2[(i+1)%nx,j-1]-u2[i-1,j-1] ) \\\n",
    "                 + nu*dt/(dx**2)*( u2[(i+1)%nx,j-1]-2*u2[i,j-1]+u2[i-1,j-1]  )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 17
    },
    "executionInfo": {
     "elapsed": 243,
     "status": "ok",
     "timestamp": 1633635959105,
     "user": {
      "displayName": "Philipp Schlatter",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgHNqDMoaWsF9tVuJ60Ac_YEfqJKF_MQZZeS_Bhieg=s64",
      "userId": "08539669643645971775"
     },
     "user_tz": -120
    },
    "id": "Vb6LjUm0SDDT",
    "outputId": "5061100b-5895-45cc-901b-64d7306567c5"
   },
   "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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plt.rcParams[\"animation.html\"] = \"jshtml\"\n",
    "#plt.ioff()\n",
    "\n",
    "fig = plt.figure(figsize=(8,5))\n",
    "\n",
    "def animate(j):\n",
    "    plt.cla()\n",
    "    plt.xlabel('$x$')\n",
    "    plt.ylabel('$f^\\prime(x)$')\n",
    "    plt.grid()\n",
    "    plt.plot(x,u0,'k--',lw=1,label='initial')\n",
    "    #plt.plot(x,u1[:,4*j],'r',label='ADV')\n",
    "    plt.plot(x,u2[:,4*j],'b--',label='ADV-DIF')\n",
    "    plt.xlim(-20,20)\n",
    "    plt.ylim(-1.1,1.1)\n",
    "    plt.title(f\"time={t[4*j]:.2f} $\\sigma$={sigma:.2f} beta={beta:.2f}\")   \n",
    "    plt.legend(loc='upper right')\n",
    "    \n",
    "ani=matplotlib.animation.FuncAnimation(fig, animate, frames=int((t.size-1)/4+1), repeat=False)\n",
    "#writer = matplotlib.animation.writers['ffmpeg']\n",
    "#writer = writer(fps=24)\n",
    "#ani.save('out.mp4', writer=writer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3bCM-g6KSDDT"
   },
   "source": [
    "Good cases to try (for $L=40$, $c=1$, $\\nu=0.05$):\n",
    "* nx=400, dt=0.1: Then we get $\\sigma=1$ and $\\beta=0.5$ and $\\sigma^2/\\beta=2$. Observation: solution to advection and advection-diffusion equation are exactly the same, and correspond to pure advection! Why? Check the numerical viscosity of the FTBS scheme. Why is the solution constant even though $\\nu_{num}>0$?\n",
    "* nx=400, dt=0.01: Solution is decaying, identical for both advection and advection-diffusion equation. Why? Check again the numerical viscosity of the FTBS scheme. Why does a smaller time step lead to a decaying solution?\n",
    "* nx=200, dt=0.1: The advection equation with $\\sigma=0.5$ is very dissipative and decays fast. The ADV-DIF solution is decaying slower, however with clear dispersion errors. Why?\n",
    "* nx=200, dt=0.11: Advection-diffusion equation is unstable, advection alone is stable. The time step limit of diffusion was violated.\n",
    "* nx=200, dt=0.01: Both solutions are much more damped, because of the properties of the temporal scheme."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Z9vmC6vVSDDU"
   },
   "source": [
    "---\n",
    "\n",
    "## Stability and truncation error\n",
    "\n",
    "The stability for the advection and diffusion equations separately are:\n",
    "* $\\sigma = c\\frac{\\Delta t}{\\Delta x} \\leq 1$ (note only necessary as based on CFL condition)\n",
    "* $\\beta = \\nu \\frac{\\Delta t}{\\Delta x^2} \\leq 1/2$ (necessary and sufficient)\n",
    "\n",
    "However, for the coupled advection-diffusion equation one gets the following\n",
    "\n",
    "$$\\sigma^2\\leq 2\\beta \\leq 1$$\n",
    "\n",
    "which can be re-written as two inequalities:\n",
    "* $\\beta \\leq 1/2$: $\\Delta t\\leq \\frac{1}{2\\nu}\\Delta x^2$ (as for diffusion equation)\n",
    "* $\\sigma^2/\\beta \\leq 2$: $\\Delta t\\leq 2\\nu/ c^2$ (independent of $\\Delta x$)\n",
    "\n",
    "One observes the following\n",
    "* for high viscosity the diffusive term is dominant: *viscous time-step limit*\n",
    "* for low viscosity: advection is stabilised by viscosity\n",
    "* for zero viscosity ($\\nu=0$): maximum $\\Delta t=0$, i.e. the scheme is unconditionally unstable (central discretisation of advection is always unstable)\n",
    "\n",
    "\n",
    "The truncation error for the upwind scheme is\n",
    "$$T(x_j,t^n) = \\frac{1}{2}c \\Delta x u_{xx} - \\frac{1}{2} \\Delta t u_{tt} $$\n",
    "\n",
    "and thus the numerical viscosity for the spatial scheme\n",
    "\n",
    "$$ \\nu_{num} = \\frac{1}{2}c \\Delta x  \\ , $$\n",
    " \n",
    "and the numerical viscosity for the temporal scheme (Euler forward) is\n",
    "\n",
    "$$ \\nu_{num,t} = -\\frac{1}{2} c^2 \\Delta t \\ .$$\n",
    "\n",
    "For the advection-diffusion scheme we have no diffusive errors in space (i.e. $\\nu_{num}=0$)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "        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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.animation as animation\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "\n",
    "def f(x, y):\n",
    "    return np.sin(x) + np.cos(y)\n",
    "\n",
    "x = np.linspace(0, 2 * np.pi, 120)\n",
    "y = np.linspace(0, 2 * np.pi, 100).reshape(-1, 1)\n",
    "\n",
    "# ims is a list of lists, each row is a list of artists to draw in the\n",
    "# current frame; here we are just animating one artist, the image, in\n",
    "# each frame\n",
    "ims = []\n",
    "for i in range(60):\n",
    "    x += np.pi / 15.\n",
    "    y += np.pi / 20.\n",
    "    im = ax.imshow(f(x, y), animated=True)\n",
    "    if i == 0:\n",
    "        ax.imshow(f(x, y))  # show an initial one first\n",
    "    ims.append([im])\n",
    "\n",
    "ani = animation.ArtistAnimation(fig, ims, interval=50, blit=True,\n",
    "                                repeat_delay=1000)\n",
    "\n",
    "# To save the animation, use e.g.\n",
    "#\n",
    "# ani.save(\"movie.mp4\")\n",
    "#\n",
    "# or\n",
    "#\n",
    "# writer = animation.FFMpegWriter(\n",
    "#     fps=15, metadata=dict(artist='Me'), bitrate=1800)\n",
    "# ani.save(\"movie.mp4\", writer=writer)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "name": "advdiff.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}