elastic_wave_2d_staggered_isotropic_v4.ipynb

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    "### Codigo para la propagación de onda elástica 2D PSV en un medio homogeneo mediante el esquema velocidad - esfuerzo y rejilla escalonada\n",
    "En este Notebook se presenta un codigo para la propagación de onda elástica 2D PSV en un medio homogeneo mediante el esquema velocidad - esfuerzo y rejilla escalonada propuesto por Virieux (1986), como resultado se muestra en la figura 1 cuatro cuadros donde se muestra el avance de la onda P mediante la divergencia, la onda S mediante el rotor y las velocidades $v_x$ y $v_z$\n",
    "\n",
    "#### Sistema de ecuaciones de onda elástica 2D\n",
    "El sistema de ecuaciones para la propagación de la onda elástica en 2D en el esquema velocidad - esfuerzo donde el movimiento de la particula es en la dirección x (horizontal) y en la dirección z (vertical) son:\n",
    "\n",
    "$$\n",
    "\\frac{\\partial v_x}{\\partial t} = \\frac{1}{\\rho} \\left( \\frac{\\partial \\tau_{xx}}{\\partial x} + \\frac{\\partial \\tau_{xz}}{\\partial z} \\right)\n",
    "$$\n",
    "$$\n",
    "\\frac{\\partial v_z}{\\partial t} = \\frac{1}{\\rho} \\left( \\frac{\\partial \\tau_{xz}}{\\partial x} + \\frac{\\partial \\tau_{zz}}{\\partial z} \\right)\n",
    "$$\n",
    "$$\n",
    "\\frac{\\partial \\tau_{xx}}{\\partial t} = (\\lambda + 2\\mu)\\frac{\\partial v_x}{\\partial x} + \\lambda \\frac{\\partial v_z}{\\partial z}\n",
    "$$\n",
    "$$\n",
    "\\frac{\\partial \\tau_{zz}}{\\partial t} = (\\lambda + 2\\mu)\\frac{\\partial v_z}{\\partial z} + \\lambda \\frac{\\partial v_x}{\\partial x}\n",
    "$$\n",
    "$$\n",
    "\\frac{\\partial \\tau_{xz}}{\\partial t} = \\mu \\left( \\frac{\\partial v_x}{\\partial z} + \\frac{\\partial v_z}{\\partial x} \\right)\n",
    "$$\n",
    "\n",
    "donde $ \\rm {\\rho} $ es la densidad, $ \\rm {\\lambda}$ y $ \\rm {\\mu}$ son los parámetros de Lamé, $ \\rm{(v_x,\\; v_z)}$ es el vector de velocidad de partículas , $ \\rm {\\tau_{xx}} $, $ \\rm{\\tau_{zz}} $, $ \\rm{\\tau_{xz}}$ son los componentes del tensor esfuerzo\n",
    "\n",
    "#### Implementación númerica mediante el metodo de rejilla escalonada\n",
    "Para la solución numérica de las ecuaciones de movimiento elásticas hay que discretizarlas en el tiempo y el espacio en una cuadrícula. Las velocidades de las partículas $\\rm{\\mathbf{v}}$, los esfuerzos $\\rm{\\tau_{ij}}$, los parámetros de Lamé $\\rm{\\lambda}$ y $\\rm{\\mu}$ son calculado y definido en coordenadas cartesianas discretas $\\rm{x = i \\; dx}$, $\\rm{z = j \\; dz}$ y tiempos discretos $\\rm{t = n \\; dt}$. $\\rm{dx}$ y $\\rm{dz}$ denota la distancia espacial entre dos puntos de cuadrícula adyacentes en el eje x y eje z respectivamente y $\\rm{dt}$ es la diferencia entre dos pasos de tiempo sucesivos. Por lo tanto, cada punto de la cuadrícula se encuentra en el intervalo $\\rm{i\\ en N | [1, nx]}$, $\\rm {j\\ en N | [1, nz]}$ y $\\rm{n\\ en N | [1, nt]}$, donde $\\rm{nx}$, $\\rm{nz}$ y $\\rm{nt}$ son el número de puntos discretos de la cuadrícula espacial y el número de pasos de tiempo, respectivamente.\n",
    "\n",
    "Finalmente, las derivadas parciales se reemplazan por operadores **de diferencia finita (FD)**. Se pueden distinguir dos tipos de operadores, operadores hacia adelante y hacia atrás $ \\rm {D^+, \\; D^-}$. La derivada de una función f(x) con respecto a una variable x puede ser aproximada por los siguientes operadores de segundo orden:\n",
    "\n",
    "$$\\rm{D^+_x f = \\frac{f_{i+1}-f_{i}}{dx} \\hspace{1 cm} \\text{operador hacia adelante}} $$\n",
    "\n",
    "$$\\rm{D^-_x f = \\frac{f_i-f_{i-1}}{dx} \\hspace{1 cm} \\text{operador hacia atras}} $$\n",
    "\n",
    "Para calcular las derivadas espaciales de las variables de campo de onda en las posiciones correctas entre sí, las variables no se colocan en los mismos puntos de la cuadrícula, sino que se escalonan por la mitad de la distancia del punto de la cuadrícula espacial (Virieux 1986). La Figura 1 muestra la distribución de los parámetros del material y las variables del campo de onda en la cuadrícula espacial.\n",
    "\n",
    "![Staggered grid](./Staggered_grid.png)\n",
    "\n",
    "En el siguiente paso, discretizamos las ecuaciones de movimiento para el problema 2D PSV utilizando un enfoque de diferencia finita escalonada. Primero, discretizamos la componente x de la ecuación de momento aproximando las derivadas espaciales\n",
    "\n",
    "$$\\rm{\\frac{\\partial \\tau_{xx}}{\\partial x} \\approx \\frac{\\tau_{xx}(j,i+1) - \\tau_{xx}(j,i)}{dx}}, \\rm{\\frac{\\partial \\tau_{xz}}{\\partial z} \\approx \\frac{\\tau_{xz}(j+1/2, i) - \\tau_{xz}(j-1/2,i)}{dz}} $$\n",
    "\n",
    "Y la derivada temporal viene dada por\n",
    "\n",
    "$$\\rho \\rm{\\frac{\\partial v_x}{\\partial t} \\approx \\rho_x(j,i+1/2) \\frac{v_x^{n+1/2}(j,i+1/2) - v_x^{n-1/2}(j,i+1/2)}{dt}} $$\n",
    "\n",
    "Insertandola en la ecuación diferencial parcial\n",
    "\n",
    "$$\\rm{\\rho \\frac{\\partial v_x}{\\partial t} = \\frac{\\partial \\tau_{xx}}{\\partial x} + \\frac{\\partial \\tau_{xz}}{\\partial z}} $$\n",
    "\n",
    "lleva a\n",
    "\n",
    "$$\\rho_x(j,i+1/2) \\frac{v_x^{n+1/2}(j,i+1/2) - v_x^{n-1/2}(j,i+1/2)}{dt} = \\frac{\\tau_{xx}^n(j,i+1) - \\tau_{xx}^n(j,i)}{dx} + \\frac{\\tau_{xz}^n(j+1/2, i) - \\tau_{xz}^n(j-1/2,i)}{dz} $$\n",
    "\n",
    "Despues  reordenando  para $v_x^{n+1/2}(j,i+1/2)$ se obtiene el siguiente esquema de FD explicito para el componente  x del la ecuación de  momentum:\n",
    "\n",
    "$$\\rm{v_x^{n+1/2}(j,i+1/2) = v_x^{n-1/2}(j,i+1/2) + \\frac{dt}{\\rho_x(j,i+1/2)}\\cdot \\biggl(\\frac{\\tau^n_{xx}(j,i+1) - \\tau^n_{xx}(j,i)}{dx} + \\frac{\\tau^n_{xz}(j+1/2, i) - \\tau^n_{xz}(j-1/2,i)}{dz} \\biggr)} $$\n",
    "\n",
    "Usando un enfoque similar, podemos derivar el esquema FD para la componente y de la ecuación de momento ...\n",
    "\n",
    "$$\\rm{v_z^{n+1/2}(j,i+1/2) = v_z^{n-1/2}(j,i+1/2) + \\frac{dt}{\\rho_z(j+1/2,i)}\\cdot \\biggl(\\frac{\\tau^n_{xz}(j, i+1/2) - \\tau^n_{xz}(j,i-1/2)}{dx} + \\frac{\\tau^n_{zz}(j+1,i) - \\tau^n_{zz}(j,i)}{dz} \\biggr)} $$\n",
    "\n",
    "... y los esfuerzos ...\n",
    "\n",
    "$$\n",
    "\\begin{split}   \n",
    "\\rm{\\tau^{n+1}_{xx}(j,i)}\\;&\\rm{= \\tau_{xx}^{n}(j,i) + dt\\cdot\\lambda(j,i)\\cdot \\biggl(v^{n+1/2}_{xx}(j,i) + v^{n+1/2}_{zz}(j,i) \\biggr) + 2 dt\\cdot  \\mu(j,i) \\cdot  v^{n+1/2}_{xx}(j,i)}\\\\ \n",
    "\\rm{\\tau^{n+1}_{zz}(j,i)}\\;&\\rm{= \\tau_{zz}^{n}(j,i) + dt\\cdot\\lambda(j,i)\\cdot \\biggl(v^{n+1/2}_{xx}(j,i) + v^{n+1/2}_{zz}(j,i) \\biggr) + 2 dt\\cdot  \\mu(j,i) \\cdot  v^{n+1/2}_{zz}(j,i)}\\\\ \n",
    "\\rm{\\tau^{n+1}_{xz}(j+1/2,i+1/2)}\\;&\\rm{=\\tau^{n}_{xz}(j+1/2,i+1/2) + dt\\cdot\\mu_{xz}(j+1/2,i+1/2)\\biggl(v^{n+1/2}_{xz}(j+1/2,i+1/2) + v^{n+1/2}_{zx}(j+1/2,i+1/2)\\biggr)}\\\\\n",
    "\\end{split}\n",
    "$$\n",
    "\n",
    "con las derivadas espaciales\n",
    "\n",
    "$$\n",
    "\\begin{split}  \n",
    "\\rm{v_{xx}(j,i)}\\; & \\rm{= \\frac{v_x(j,i+1/2)-v_x(j,i-1/2)}{dx}}\\\\ \n",
    "\\rm{v_{zz}(j,i)}\\; & \\rm{= \\frac{v_z(j+1/2,i)-v_z(j-1/2,i)}{dz}}\\\\ \n",
    "\\rm{v_{zx}(j+1/2,i+1/2)}\\; & \\rm{= \\frac{v_z(j+1/2, i+1)-v_z(j+1/2, i)}{dx}}\\\\ \n",
    "\\rm{v_{xz}(j+1/2,i+1/2)}\\; & \\rm{= \\frac{v_x(j+1,i+1/2)-v_x(j, i+1/2)}{dz}}\\\\\n",
    "\\end{split}\n",
    "$$\n",
    "\n",
    "#### Termino o función fuente\n",
    "\n",
    "En este codigo se uso como función fuente se uso una ondicula  cuya ecuación es:\n",
    "\n",
    "$$\n",
    "s= exp\\left(-f_0^2*((t-t_0)*dt)^2\\right)\n",
    "$$\n",
    "\n",
    "donde $f_0$ es la frecuencia dominante y $t_0$ es el retraso en tiempo"
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   "source": [
    "# Import Libraries \n",
    "# ----------------------------------------------\n",
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def d(comp,inpu,dire):\n",
    "    if(comp=='x'): idim = 0\n",
    "    elif(comp=='z'): idim = 1\n",
    "    \n",
    "    if(dire == '+'):\n",
    "        return (np.roll(inpu, -1, axis = idim)-inpu)/dx\n",
    "    elif(dire == '-'):\n",
    "        return (inpu - np.roll(inpu, 1, axis = idim))/dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Input Parameter\n",
    "# ----------------------------------------------\n",
    "\n",
    "# Discretization\n",
    "c1=20           # Number of grid points per dominant wavelength\n",
    "c2=0.6          # CFL-Number\n",
    "nx=400          # number of grid points in x-direction\n",
    "nz=400          # number of grid points in z-direction\n",
    "Tt=0.50\n",
    "idisp = 5 # display frequency\n",
    " \n",
    "# Source Signal\n",
    "f0= 25      # Center frequency Ricker-wavelet\n",
    "aa= 1/f0\n",
    "q0= 1      # Maximum amplitude Ricker-Wavelet\n",
    "xscr = int(nx/2)-1;  zscr = int(nz/2)-1 # Source position (in grid points)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Velocity and density\n",
    "model_vp=3000   # P-wave velocity in m/s\n",
    "model_vs=1500   # S-wave velocity in m/s\n",
    "rho= 2200      # Density in g/cm^3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
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   "source": [
    "## Preparation \n",
    "\n",
    "# Init wavefields\n",
    "vx=np.zeros((nx,nz))\n",
    "vz=np.zeros((nx,nz))\n",
    "txx=np.zeros((nx,nz))\n",
    "tzz=np.zeros((nx,nz))\n",
    "txz=np.zeros((nx,nz))\n",
    "#vz_x=np.zeros((nx,nz))\n",
    "#vx_z=np.zeros((nx,nz))\n",
    "#vx_x=np.zeros((nx,nz))\n",
    "#vz_z=np.zeros((nx,nz))\n",
    "vol   = np.zeros([nx,nz])\n",
    "curl  = np.zeros([nx,nz])\n",
    "\n",
    "# Calculate Lame  Parameters\n",
    "lam=rho*(model_vp**2 - 2*model_vs**2)\n",
    "mu=rho*model_vs**2 \n",
    "\n",
    "cmin=model_vp  # Lowest P-wave velocity\n",
    "cmax=model_vp  # Highest P-wave velocity\n",
    "fmax=2*f0              # Maximum frequency\n",
    "dx=cmin/(fmax*c1)      # Spatial discretization (in m)\n",
    "dz=dx \n",
    "dt=dx/(cmax)*c2        # Temporal discretization (in s)\n",
    "lampda_min=cmin/fmax   # Smallest wavelength\n",
    "\n",
    "# Create space and time vector\n",
    "x=np.arange(0,dx*nx-dx,dx) # Space vector\n",
    "z=np.arange(0,(dz*nz-dz),dz) # Space vector\n",
    "t=np.arange(0,(Tt-dt),dt)    # Time vector\n",
    "nt=len(t)       # Number of time steps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
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       "    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": {
      "text/html": [
       "<div id='92bec43f-6a6b-4664-af9e-6ed94679ca8a'></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Source signal - Ricker-wavelet\n",
    "#tau=np.pi*f0*(t-1.5/f0)\n",
    "#q=q0*(1-2*tau**2)*np.exp(-tau**2)\n",
    "\n",
    "# Initialise source\n",
    "s = np.zeros(nt)\n",
    "t0 = 3. * aa/dt\n",
    "for i in range(1,nt+1):\n",
    "    s[i-1]= np.exp(- 1./aa**2*((i-t0)*dt)**2)\n",
    "print(' %r <source< %r' %(s.min(),s.max()))\n",
    "\n",
    "# Plotting source signal\n",
    "plt.ion()\n",
    "fig4 = plt.figure(figsize=(9,4.5))\n",
    "plt.plot(t,s)\n",
    "plt.title('Source signal Ricker-Wavelet')\n",
    "plt.xlabel('Time in s')\n",
    "plt.ylabel('Amplitude')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot preparation\n",
    "# Initialize animated plot\n",
    "plt.ion()\n",
    "fig5 = plt.figure(figsize=(9,6))\n",
    "f1 = fig5.add_subplot(2, 2, 1)\n",
    "f2 = fig5.add_subplot(2, 2, 2)\n",
    "f3 = fig5.add_subplot(2, 2, 3)\n",
    "f4 = fig5.add_subplot(2, 2, 4)\n",
    "f1.set_title('curl')\n",
    "f2.set_title('div')\n",
    "f3.set_title('vx')\n",
    "f4.set_title('vz')\n",
    "\n",
    "curlp = f1.imshow(curl, interpolation='nearest', animated=True,\n",
    "                   vmin=-1.0e-11, vmax=1.0e-11, cmap=plt.cm.RdBu)\n",
    "divp = f2.imshow(vol, interpolation='nearest', animated=True,\n",
    "                   vmin=-1.0e-11, vmax=1.0e-11, cmap=plt.cm.RdBu)\n",
    "vxp = f3.imshow(vx, interpolation='nearest', animated=True,\n",
    "                   vmin=-1.0e-09, vmax=1.0e-09, cmap=plt.cm.RdBu)\n",
    "vzp = f4.imshow(vz, interpolation='nearest', animated=True,\n",
    "                   vmin=-1.0e-09, vmax=1.0e-09, cmap=plt.cm.RdBu)\n",
    "\n",
    "# Plot the receivers\n",
    "#for x, z in zip(irx, irz):\n",
    "#    plt.text(x, z, '+')\n",
    "\n",
    "plt.plot(zscr, xscr, 'r*', markersize=11)\n",
    "#plt.colorbar()\n",
    "#plt.xlabel('ix')\n",
    "#plt.ylabel('iz')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for n in range(1,nt+1):\n",
    "\n",
    "    # Inject source wavelet (explosion)\n",
    "#    txx[xscr,zscr]=txx[xscr,zscr]+q[n]\n",
    "#    tzz[xscr,zscr]=tzz[xscr,zscr]+q[n]\n",
    "        \n",
    "    txx[xscr,zscr]=txx[xscr,zscr]+s[int(n)-1]   \n",
    "    tzz[xscr,zscr]=tzz[xscr,zscr]+s[int(n)-1]\n",
    "    \n",
    "    txx[:,0] = 0.\n",
    "    tzz[:,0] = 0.\n",
    "    txz[:,0] = 0.\n",
    "    txx[:,nz-1] = 0.\n",
    "    tzz[:,nz-1] = 0.\n",
    "    txz[:,nz-1] = 0.\n",
    "    \n",
    "    # Update velocity\n",
    "#    # Calculating spatial derivative\n",
    "#    for i in range(1, nx-1):\n",
    "#        for j in range(1, nz-1):\n",
    "#            txx_x = (txx[i,j+1]-txx[i,j])/dx\n",
    "#            tzz_z = (tzz[i+1,j]-tzz[i,j])/dz\n",
    "#            txz_x = (txz[i,j]-txz[i,j-1])/dx\n",
    "#            txz_z = (txz[i,j]-txz[i-1,j])/dz\n",
    "           \n",
    "    # Update velocity\n",
    "    vx=vx+(dt/rho)*(d('x',txx,'-') + d('z',txz,'-'))\n",
    "    vz=vz+(dt/rho)*(d('x',txz,'+') + d('z',tzz,'+'))\n",
    "            \n",
    "    curl = d('z',vx,'+') - d('x',vz,'-')\n",
    "    vol = d('x',vx,'+') + d('z',vz,'-')            \n",
    "\n",
    "\n",
    "#    # Calculating spatial derivative\n",
    "#    for i in range(1, nx-1):\n",
    "#        for j in range(1, nz-1):\n",
    "#            vx_x[i,j] = (vx[i,j]-vx[i,j-1])/dx\n",
    "#            vz_z[i,j] = (vz[i,j]-vz[i-1,j])/dz\n",
    "#            vz_x[i,j] = (vz[i,j+1]-vz[i,j])/dx        \n",
    "#            vx_z[i,j] = (vx[i+1,j]-vx[i,j])/dz\n",
    "                       \n",
    "    # Update pressure\n",
    "\n",
    "    txx=txx+(lam *  vol + 2*mu * d('x',vx,'+')  ) * dt\n",
    "    tzz=tzz+(lam *  vol + 2*mu * d('z',vz,'-')  ) * dt\n",
    "    txz=txz+(mu * (d('z',vx,'+') + d('x',vz,'-') ) ) * dt \n",
    "                \n",
    "        # Plot every time step (nt)\n",
    "    if (n % idisp) == 0:\n",
    "        #plt.title('Time Step (nt) = %d' % n)    \n",
    "        curlp.set_data(curl)\n",
    "        divp.set_data(vol)\n",
    "        vxp.set_data(vx)\n",
    "        vzp.set_data(vz)\n",
    "        plt.gcf().canvas.draw()\n",
    "        "
   ]
  }
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