03_fdm_as_python_func.ipynb

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    "# A finite difference model as a Python function\n",
    "*Prof. dr.ir.T.N.Olsthoorn*\n",
    "\n",
    "*Heemstede, Sept. 2016, May 2017*"
   ]
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   "source": [
    "## Generalize the finite difference model into a callable function"
   ]
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   "source": [
    "The 3D finite difference computation in the previous chapter can be generalized by putting the generic parts in a callable Python function and turning the the user or case specific data into the arguments by which the function is called like so:\n",
    "\n",
    "Phi = fdm3( x, y, z, kx, ky, kz, FQ, IH, IBOUND )\n",
    "\n",
    "Doing so and adding some input error checking for convenience leads to the following code, that is save to disk for future use:"
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     "text": [
      "Overwriting fdm_a.py\n"
     ]
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    "%%writefile fdm_a.py\n",
    "# write the function in this cell to disk as file fdm.py\n",
    "\n",
    "import numpy as np\n",
    "#import pdb  # in case we need to debug this function\n",
    "\n",
    "def fdm3(x, y, z, kx, ky, kz, FQ, HI, IBOUND):\n",
    "    '''Returns computed heads of steady state 3D finite difference grid.\n",
    "    \n",
    "    Steady state 3D Finite Difference Model that computes the heads a 3D ndarray.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    `x` : ndarray, shape: Nx+1, [L]\n",
    "        `x` coordinates of grid lines perpendicular to rows, len is Nx+1\n",
    "    `y` : ndarray, shape: Ny+1, [L]\n",
    "        `y` coordinates of grid lines along perpendicular to columns, len is Ny+1\n",
    "    `z` : ndarray, shape: Nz+1, [L]\n",
    "        `z` coordinates of layers tops and bottoms, len = Nz+1\n",
    "    `kx`, `ky`, `kz` : ndarray, shape: (Ny, Nx, Nz) [L/T]\n",
    "        hydraulic conductivities along the three axes, 3D arrays.\n",
    "    `FQ` : ndarray, shape: (Ny, Nx, Nz), [L3/T]\n",
    "        prescrived cell flows (injection positive, zero of no inflow/outflow)\n",
    "    `IH` : ndarray, shape: (Ny, Nx, Nz), [L]\n",
    "        initial heads. `IH` has the prescribed heads for the cells with prescribed head.\n",
    "    `IBOUND` : ndarray of int, shape: (Ny, Nx, Nz), dim: [-]\n",
    "        boundary array like in MODFLOW with values denoting\n",
    "        * IBOUND>0  the head in the corresponding cells will be computed\n",
    "        * IBOUND=0  cells are inactive, will be given value NaN\n",
    "        * IBOUND<0  coresponding cells have prescribed head\n",
    "    \n",
    "    Returns\n",
    "    -------    \n",
    "    `Phi` : ndarray, shape: (Ny, Nx, Nz), [L]\n",
    "        the 3D array with the final heads with `NaN` at inactive cells.\n",
    "    \n",
    "    TO 160905\n",
    "    '''\n",
    "\n",
    "    import numpy as np\n",
    "    import scipy.sparse as sp\n",
    "    from scipy.sparse.linalg import spsolve # to use its short name\n",
    "#    pdb.set_trace()\n",
    "    x = np.sort(np.array(x))       # enforce ascending\n",
    "    y = np.sort(np.array(y))[::-1] # enforce descending\n",
    "    z = np.sort(np.array(z))[::-1] # enforce descending\n",
    "    \n",
    "    # as well as the number of cells along the three axes\n",
    "    SHP = Nz, Ny, Nx = len(z) - 1, len(y)-1, len(x)-1\n",
    "\n",
    "    Nod = np.prod(SHP)\n",
    "    \n",
    "    if Nod == 0:\n",
    "        raise AssertationError(\"Nx, Ny and Nz must be >= 1\")\n",
    "\n",
    "    # assert correct shape of input arrays\n",
    "    if kx.shape != SHP:\n",
    "        raise AssertionError(\"shape of kx {0} differs from that of model {1}\".format(kx.shape,SHP))\n",
    "    if ky.shape != SHP:\n",
    "        raise AssertionError(\"shape of ky {0} differs from that of model {1}\".format(ky.shape,SHP))\n",
    "    if kz.shape != SHP:\n",
    "        raise AssertionError(\"shape of kz {0} differs from that of model {1}\".format(kz.shape,SHP))\n",
    "    \n",
    "    # from this we have the width of columns, rows and layers\n",
    "    dx = np.abs(np.diff(x).reshape(1, 1, Nx)) # enforce positive\n",
    "    dy = np.abs(np.diff(y).reshape(1, Ny, 1)) # enforce positive\n",
    "    dz = np.abs(np.diff(z)).reshape(Nz, 1, 1) # enforce positive\n",
    "    \n",
    "    active = (IBOUND >0).reshape(Nod,) # boolean vector denoting the active cells\n",
    "    inact  = (IBOUND==0).reshape(Nod,) # boolean vector denoting inacive cells\n",
    "    fxhd   = (IBOUND <0).reshape(Nod,) # boolean vector denoting fixed-head cells\n",
    "\n",
    "    # half cell flow resistances\n",
    "    Rx = 0.5 * dx / (dy * dz) / kx\n",
    "    Ry = 0.5 * dy / (dz * dx) / ky\n",
    "    Rz = 0.5 * dz / (dx * dy) / kz\n",
    "    \n",
    "    # set flow resistance in inactive cells to infinite\n",
    "    Rx = Rx.reshape(Nod,); Rx[inact] = np.Inf; Rx=Rx.reshape(SHP)\n",
    "    Ry = Ry.reshape(Nod,); Ry[inact] = np.Inf; Ry=Ry.reshape(SHP)\n",
    "    Rz = Rz.reshape(Nod,); Rz[inact] = np.Inf; Rz=Rz.reshape(SHP)\n",
    "    \n",
    "    # conductances between adjacent cells\n",
    "    Cx = 1 / (Rx[:, :, :-1] + Rx[:, :, 1:])\n",
    "    Cy = 1 / (Ry[:, :-1, :] + Ry[:, 1:, :])\n",
    "    Cz = 1 / (Rz[:-1, :, :] + Rz[1:, :, :])\n",
    "    \n",
    "    NOD = np.arange(Nod).reshape(SHP)\n",
    "    \n",
    "    IE = NOD[:, :, 1:]  # east neighbor cell numbers\n",
    "    IW = NOD[:, :, :-1] # west neighbor cell numbers\n",
    "    IN = NOD[:, :-1, :] # north neighbor cell numbers\n",
    "    IS = NOD[:, 1:, :]  # south neighbor cell numbers\n",
    "    IT = NOD[:-1, :, :] # top neighbor cell numbers\n",
    "    IB = NOD[1:, :, :]  # bottom neighbor cell numbers\n",
    "    \n",
    "    R = lambda x : x.ravel()  # generate anonymous function R(x) as shorthand for x.ravel()\n",
    "\n",
    "    # notice the call  csc_matrix( (data, (rowind, coind) ), (M,N))  tuple within tupple\n",
    "    A = sp.csc_matrix(( -np.concatenate(( R(Cx), R(Cx), R(Cy), R(Cy), R(Cz), R(Cz)) ),\\\n",
    "                        (np.concatenate(( R(IE), R(IW), R(IN), R(IS), R(IB), R(IT)) ),\\\n",
    "                         np.concatenate(( R(IW), R(IE), R(IS), R(IN), R(IT), R(IB)) ),\\\n",
    "                      )),(Nod,Nod))\n",
    "    \n",
    "    # to use the vector of diagonal values in a call of sp.diags() we need to have it aa a \n",
    "    # standard nondimensional numpy vector.\n",
    "    # To get this:\n",
    "    # - first turn the matrix obtained by A.sum(axis=1) into a np.array by np.array( .. )\n",
    "    # - then take the whole column to loose the array orientation (to get a dimensionless numpy vector)\n",
    "    adiag = np.array(-A.sum(axis=1))[:,0]\n",
    "    \n",
    "    Adiag = sp.diags(adiag)  # diagonal matrix with a[i,i]\n",
    "    \n",
    "    RHS = FQ.reshape(Nod,1) - A[:,fxhd].dot(HI.reshape(Nod,1)[fxhd]) # Right-hand side vector\n",
    "    \n",
    "    Phi = HI.flatten() # allocate space to store heads\n",
    "    \n",
    "    Phi[active] = spsolve( (A + Adiag)[active][:,active] ,RHS[active] ) # solve heads at active locations\n",
    "    \n",
    "    Phi[inact] = np.NaN # put NaN at inactive locations\n",
    "    \n",
    "    return Phi.reshape(SHP) # reshape vector to 3D size of original model"
   ]
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   "cell_type": "code",
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   "source": [
    "import numpy as np # we always need this\n",
    "import fdm_a # import fdm_a module for use\n",
    "\n",
    "from importlib import reload  # we need reload if we edited the file fdm_a.py\n",
    "reload(fdm_a)  # if edited, must reload it\n",
    "\n",
    "fdm3 = fdm_a.fdm3  # for convenience create a local name to just write fdm3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This function should be saved in a .py file e.g. \"fdm3.py\" so that it can be used as a module that can be imported by other users or programs or scripts."
   ]
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   "cell_type": "markdown",
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   "source": [
    "## Apply the model\n",
    "\n",
    "To apply the model we specify coofdinates, conductivities, prescribed flows and prescribed heads and the `IBOUND` array. Then we call the function with the proper arguments. After the function computed the heads, we'll show them by a contour plot.\n",
    "\n",
    "###  Generate input to run the model with\n",
    "\n",
    "The lines below are case specific and could be placed in a script that can be run to set up the model afterw which the model is called from the script with the proper arguments"
   ]
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   "source": [
    "# specify a rectangular grid\n",
    "x = np.arange(-1000., 1000., 25.)\n",
    "y = np.arange(-1000., 1000., 25.) # backward, i.e. first row grid line has highest y\n",
    "z = np.arange(-100., 0., 20.)  # backward, i.e. from top to bottom\n",
    "\n",
    "SHP = (len(z)-1, len(y)-1, len(x)-1)\n",
    "\n",
    "k = 10.0 # m/d uniform conductivity\n",
    "kx = k * np.ones(SHP) # [L/T] 3D kx array\n",
    "ky = k * np.ones(SHP) # [L/T] 3D ky array with same values as kx \n",
    "kz = k * np.ones(SHP) # [L/T] 3D kz array with same values as kx\n",
    "\n",
    "FQ = np.zeros(SHP)    # all flows zero. Note sz is the shape of the model grid\n",
    "FQ[2, 30, 25] = -1200  # [m3/d] extraction in this cell\n",
    "\n",
    "HI = np.zeros(SHP) # initial heads\n",
    "\n",
    "IBOUND = np.ones(SHP)\n",
    "IBOUND[:, -1, :] = -1  # last row of model heads are prescribed\n",
    "IBOUND[:, 40:45, 20:70]=0 # these cells are inactive"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Call the function with the correct arguments"
   ]
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   "source": [
    "Phi = fdm3( x, y, z, kx, ky, kz, FQ, HI, IBOUND)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualization of the results: plot heads as contours"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the required plotting module and setup the plot and run ``%matplotlib notebook`` to allow plots beeing shown inside the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
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   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt # combines namespace of numpy and pyplot"
   ]
  },
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   "cell_type": "code",
   "execution_count": 6,
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       "    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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<img 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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x10e619240>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xm = 0.5 * (x[:-1] + x[1:]) # cell center coordinates\n",
    "ym = 0.5 * (y[:-1] + y[1:]) # same\n",
    "layer = 2 # contours for this layer\n",
    "nc = 50   # number of contours in total\n",
    "\n",
    "plt.xlabel('x [m]')\n",
    "plt.ylabel('y [m]')\n",
    "plt.title(\"Contours (%d in total) of the head in layer %d with inactive section\" % (nc, layer))\n",
    "plt.contour(xm, ym, Phi[layer], nc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* The white area is the aquifer part that was defined as inactive (impervious).\n",
    "* The red trough is the well location.\n",
    "* The two flanks and the front sides are closed (no FQ and no fixed head).\n",
    "* The head at the back side is prescribed and maintained at zero."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have developed from scratch a full 3D steady-state finite difference mode for which fixed heads, fixed flows and inactive subareas can be prescribed.\n",
    "\n",
    "This model is general, it can be called as a function and allows solving a wide range of different 3D steady-state groundwater flow problems in a finite difference setting.\n",
    "\n",
    "The function should be stored in a module (a .py file) and can then be imported from this module, like so\n",
    "\n",
    "import mymodule\n",
    "\n",
    "from mymodule import fdm3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examples\n",
    "\n",
    "Here we set-up a few simple examples that we can readily verify analytically. The examples are 2D and can easily be computed with our 3D model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# basic imports\n",
    "\n",
    "import numpy as np\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt # combines namespace of numpy and pyplot\n",
    "\n",
    "import fdm_a\n",
    "fdm3 = fdm_a.fdm3   # could also use from fdm_a import fdm3 (sets fdm3 as convenient local name)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example 1: flow between 2 fixed bounaries\n",
    "\n",
    "Consider the flow in an aquifer with constant transmissivity `kD=1000` m2/d, with fixed head `h=0` at the left and the right boundaries at `x=-L/2` and `x=+L/2` respectively, subject to uniform precipitation `N`.\n",
    "\n",
    "The analytical solution for this case is\n",
    "\n",
    "$h = \\frac N {2 kD} ( (\\frac L 2) ^2-x^2) $\n",
    "\n",
    "\n",
    "The model will consist of 1 layer, is `L=500` m wide, with cells of `dx=10` m and is subject to `N=0.01` m/d recharge.\n",
    "\n",
    "In order to put the fixed heads at the outer cell centers exactly at $\\pm -L/2$, we make the width of the outer cells very small, 0.001 m say."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# constants\n",
    "N = 0.01 # m/d, precipitaion suplus\n",
    "L = 500  # m,   width of the cross section\n",
    "k = 10   # m/d, aquifer conductivity\n",
    "D = 100  # m/d, aquifer thickness\n",
    "L = 1000 # m,   width of the cross section\n",
    "kD = k * D # m2/d, aquifer transmissivity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# model grid\n",
    "x = np.hstack((-L/2-0.001, np.linspace(-L/2, L/2, 51), L/2+0.001))\n",
    "y = np.array([-0.5, 0.5]) # make the model 1m wide\n",
    "z = np.array([-D, 0])   # use thickenss of model\n",
    "\n",
    "Nz, Ny, Nx = SHP = (len(z) -1, len(y)-1, len(x)-1)\n",
    "\n",
    "# cell center coordinates\n",
    "xm = .5 * (x[:-1] + x[1:])\n",
    "ym = .5 * (y[:-1] + y[1:])\n",
    "zm = .5 * (z[:-1] + z[1:])\n",
    "\n",
    "# cell size\n",
    "dx = np.abs(np.diff(x));\n",
    "dy = np.abs(np.diff(y));\n",
    "dz = np.abs(np.diff(z));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# boundary array\n",
    "IBOUND = np.ones(SHP)\n",
    "IBOUND[:, :, [0, -1]] = -1  # fix head of left and right boundary\n",
    "\n",
    "# conductivitys array\n",
    "K = k  * np.ones(SHP) \n",
    "\n",
    "# prescribed flow = precipitation surplus\n",
    "FQ = np.ones(SHP)\n",
    "FQ[0, :, :] = dx * N  \n",
    "\n",
    "# Initial heads, all zero\n",
    "HI = np.zeros(SHP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# run the model to compute the heads\n",
    "Phi = fdm3(x, y, z, K, K, K, FQ, HI, IBOUND)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vizualisation of the computed heads:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\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('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1073e4c50>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt # combines namespace of numpy and pyplot\n",
    "\n",
    "plt.figure()\n",
    "plt.xlabel('x [m]')\n",
    "plt.ylabel('head [m]')\n",
    "plt.title('Head between two fixed boundaries and constant precipitation {0} m/d'.format(N))\n",
    "plt.plot(xm, Phi.ravel(), 'bo-', label='numeric')\n",
    "\n",
    "# now add the analytical solution\n",
    "fi = N/(2*kD) * ((L/2)**2 - x**2)\n",
    "plt.plot(x, fi, 'xr', label='analytic')\n",
    "plt.legend()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This shows that the analytical and numerical solutions match. Notice, however, that we have made the outer two cells very narrow, so that the location of the `x[0]` and `xm[0]` and `x[-1]` and `xm[-1]` are almost indistinguishable, so that the position of the boundary are essentially the same for the numerical and the analytical model. (Just make the outer two cells as wide as the other cells to see the difference.\n",
    "\n",
    "The 3D model was used here as a 1D model along the `x`-axis. It should be evident that our 3D numerical model is very flexible in modeling 1D, 2D as well as 3D situations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example 2, semi-confined flow (mazure case)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Assume the case where we have a water body with constant head $h=h_w$ that at `x=0` is in direct contact with an semi aquifer that is charaterized with constant transmissivity `kD` convered by a semi-confining layer with constant resistance `c` above which we have a head that is maintained at a constant level $h=h_p$. This problem was solved by Marzure around 1930 when he studied groundwater flow from the IJssel Lake to a new adjacent polder with a 5 m lower maintained water level.\n",
    "\n",
    "The analytical solution for the head in the regional aquifer, that is, below the confining layer is\n",
    "\n",
    "$ \\phi - h_p = (\\phi_0 - h_p) \\,\\, \\exp (-x / \\lambda) $\n",
    "\n",
    "with $\\lambda = \\sqrt {kD c}$\n",
    "\n",
    "Let's work out this case to compare the analytical result with our model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import numpy as np, assumed numpy has been loaded above\n",
    "\n",
    "k = 25 # m/d conductivity of regional aquifer\n",
    "D = 50 # m   thickness of regional aquifer\n",
    "d = 10 # m   thickness of confining layer\n",
    "dtop = 0.001 # m dummy thickness of layer in which the head is maintained\n",
    "c = 500.0 # d  vertical hydraulic resistance of confining layer\n",
    "hw = -0.4   # m fixed IJssel lake elevation\n",
    "hp = -5.0 # m fixed polder water elevation.\n",
    "\n",
    "kD = k*D\n",
    "lam = np.sqrt(kD * c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.hstack((-0.001, np.linspace(0, 5000, 100)))\n",
    "y = np.array([-0.5, 0.5])\n",
    "grs = 0 # m,  ground surface elevation\n",
    "z = np.array([grs-D-d-dtop, grs-d-dtop, grs-dtop, grs])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "Nz, Ny, Nx = SHP = len(z)-1, len(y)-1, len(x)-1\n",
    "IBOUND = np.ones(SHP)\n",
    "IBOUND[0, :, :] = -1 # fixed head maintained in top layer (above confining layer)\n",
    "IBOUND[-1, :, 0] = -1 # fixed head in aquifer at x=0\n",
    "\n",
    "HI = np.zeros(SHP)\n",
    "HI[-1, :, 0] = hw # fixed level of IJssel Lake\n",
    "HI[ 0, :, :] = hp # fixed polder level\n",
    "\n",
    "FQ = np.zeros(SHP) # no fixed flows\n",
    "\n",
    "kAquif = k;\n",
    "kConf  = d/c;\n",
    "kTop   = 100;  #immaterial\n",
    "\n",
    "K = np.array([kTop, kConf, kAquif]).reshape(Nz, 1, 1) * np.ones(SHP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "Phi = fdm3(x, y, z, K, K, K, FQ, HI, IBOUND)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\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('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10ef718d0>]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.xlabel('x [m]')\n",
    "plt.ylabel('head [m]')\n",
    "plt.title('Head between two fixed boundaries and constant precipitation {0} m/d'.format(N))\n",
    "\n",
    "xm = 0.5 * (x[:-1] + x[1:])\n",
    "plt.plot(xm, Phi[-1][0], 'bo-')\n",
    "\n",
    "# now add the analytical solution\n",
    "fi = hp + (hw - hp) * np.exp(-x/lam)\n",
    "plt.plot(x, fi, 'xr-')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As can be seen, the analytical and the numeical model match. Notice that here we made the first cell width very small, so that the fixed head in the first cell falls almost exactly at zero. Had we not done so, then the fixed head of the numerical model would have been at `xm[0] = 50` i.e. in the center of the first cell, while the fixed head in the analytical solution would still be at exactly `x = 0`, which would lead to a difference between the two solutions. Just try this by setting the width of the first model cell equal to 100 m instead of 0.001 m.\n",
    "\n",
    "Another issue is that the numerical model is closed at the right-hand side, i.e. where `x = 5000 m`. In this example, this distance is so large that the effect of the left boundary is almost zero, so that the difference between the analytical solution and the numerical model is not visibile in the graph. Just try to make the right-hand side of the model less far to see the difference.\n",
    "\n",
    "Of course one could easily fix the right-hand boundary as well as the left-hand one, to obtain a solution that is bounded by fixed heads on either side. It's easy to derive the analytical solution for that case as well and to verify it with the numerical model. This is left as an exercise to the student.\n",
    "\n",
    "The analytical solution for the the same head at either side of the cross section is this\n",
    "\n",
    "$\\phi - h_p = (h_w - h_p ) \\frac {\\cosh (\\frac x \\lambda ) } {\\cosh (\\frac {L\\,/2} \\lambda)} $\n",
    "\n",
    "Also notice that we have now a 3 layer model, one row, a large number of columns and 3 layers. We simply could make the model full 3D by taking more than one row. It should also be clear that the properties of the layers can be varies arbitrarily on a cell by cell basis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example 3, same case, but using only two layers\n",
    "\n",
    "Instead of 3 layers, we may use only two and fix the head in the semi confining layer. Because of the derivation of our the finite difference method water flows between cell centers. This means that, when we use the semi confing layer to also prescribe the head, this head is prescribed at the center of the layer, and the water flows vertically from or to the center of that layer from the bottom of that layer, so that only half its thickness is active for vertical flow. For the model layout, it implies that we should put the center of the layer at the elevation of ground surface and only take the vertical flow through half the layer into account. This is worked out below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# aquifer\n",
    "k = 25 # m/d conductivity of regional aquifer\n",
    "D = 50 # m   thickness of regional aquifer\n",
    "d = 20 # m   thickness of confining layer\n",
    "c = 500.0 # d  vertical hydraulic resistance of confining layer\n",
    "hw = -0.4   # m fixed IJssel lake elevation\n",
    "hp = -5.0 # m fixed polder water elevation.\n",
    "\n",
    "kD = k*D\n",
    "lam = np.sqrt(kD * c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x = np.hstack((-0.001, np.linspace(0, 5000, 100)))\n",
    "y = np.array([-0.5, 0.5])\n",
    "grs = 0 # m,  ground surface elevation\n",
    "z = np.array([grs-D-d, grs-d, grs+d])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "Nz, Ny, Nx = SHP = len(z)-1, len(y)-1, len(x)-1\n",
    "IBOUND = np.ones(SHP)\n",
    "IBOUND[0, :, :]  = -1 # fixed head maintained in top layer (above confining layer)\n",
    "IBOUND[-1, :, 0] = -1 # fiex head in aquifer at x=0\n",
    "\n",
    "HI = np.zeros(SHP)\n",
    "HI[-1, :, 0] = hw # fixed level of IJssel Lake\n",
    "HI[ 0, :, :] = hp # fixed polder level\n",
    "\n",
    "FQ = np.zeros(SHP) # no fixed flows\n",
    "\n",
    "kAquif = k;\n",
    "kConf  = d/c;\n",
    "kTop   = 100;  #immaterial\n",
    "\n",
    "K = np.array([kConf, kAquif]).reshape(Nz, 1, 1) * np.ones(SHP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Phi = fdm3(x, y, z, K, K, K, FQ, HI, IBOUND)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\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('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10f501588>]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# %matplotlib notebook  # already done above\n",
    "# import matplotlib.pyplot as plt # combines namespace of numpy and pyplot\n",
    "\n",
    "plt.figure()\n",
    "plt.xlabel('x [m]')\n",
    "plt.ylabel('head [m]')\n",
    "plt.title('Head between two fixed boundaries and constant precipitation {0} m/d'.format(N))\n",
    "\n",
    "xm = 0.5 * (x[:-1] + x[1:])\n",
    "plt.plot(xm, Phi[-1][0], 'bo-')\n",
    "\n",
    "# now add the analytical solution\n",
    "fi = hp + (hw - hp) * np.exp(-x/lam)\n",
    "plt.plot(x, fi, 'xr-')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As can be seen, we get same result as before, but now with only two layers, of which the top one represents the semi confined layer in which center the head is prescribed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Cicular island with recharge\n",
    "\n",
    "This examples uses a flat model (one layer) and places a fixed head outside the boundary of the island."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\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('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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+gAlmM6SAnF8bemHJwAQ9go9MOY1SSCA0ODNqkh3ug/oT+k4JwBMwRwfVRhD+NAJB96Z8HbjPRrm+mHMYMzFY8vyjK3pe8jfrhkA8fDCF683BIx5Khj48YGBCfjoySLShIDx1QnwwUMIUAPvAL6M4amLww94CePBD4PWHCkA4uELUIUnDS8RvHwRfgkP6xwAWvqWJgmgj3Efgpc2F37DlxpePq0sYDxo4bmA5wMwhi/BsBwBXoSAZWSDxvfQCoBpEoh2yaAwBzC1H3hsQ0YpAAxeUbxoAK/w7oZrBvTg2tLwIj5q8AU7AgDhUcQHEh6q+BjA+bEcEf4G/UsHbA+QDfiGDSJchvAPrgNf3zHoeEPAGGfQ69Mr3uq0n/C+IOQJu0b4E94JhLHCf4fymhBwmDfkCQEjPIuXUmvuombpIegJu8YLDeMX9o17hZAyPirirMrS/Mh4DAR94f2DBzo+YJv4mwYAAa/x/EpojaklgNLcuwh9gO0gUoDnLCAVYcjSobkW1LU8o3LPT0wVwMc3PJfxAc8gtAjPYAAs4Dh34JoBhcFDniuTAmC4DwiRYzqGdhmYESHgECnpCQEDlBEm3ioEnD6PSxEc2BeiBmHeLp4BGC94L4TD8ozVvGMPVeaaARA3AqE/eAzg/Wkt7VIKAeeWHUBYCQ/qmgcQ4Rh8eWAuyOsiq8C8GHjFSnMAUR6DCUaLF304MG/hv84AYA6yag/Q0oRuuOihAQYxHkCYj5cC4Ii+xQDo9QDiOhHqBbwAAPGCx0MbL3XAbMhCg2chnti8JQDm7AcPJUy2xxdrDATweMLzGQCw9HWKBx68LTUAhIcSX8Wx5xN6IdkEXtMcWMMbAo8FQA4ewdrSD7k5gPBawJOM+4BQZji8IWC0B9DEeIvBsvawTQEw2EL68gjAhRd1KQkE4IaPScz9TJNAEMIFaNaSQEI0YBQAwuOPEONHrnNegw7oAzweVgAc5QFMtcXHBXTDhys89Ln3ETyg77DO99V4AHPjKR7PI55RWg8gvK8AQoxFgER6tLxuOXBBdAQhejyD8a5IE07Sc4wKAQcbSJNAwjuglQSCSAc8/+kajXjeI/w8MgmkFwBxrxDODkmD0NLyjD0U3Gk6c+0AiIc+XlR4AOGFmx5wtyNcAC+LBQCRMQxvTW0OIObswTUdLxEBryG+7PBQLAEgoAAvFQAkXjjhwMsJWXSpB3AUAIbz4AULwMULPAXAEX1LvZD48ocuPXMA0WeES5GggYGMyb7BW4Z7CggE6OCFifOGIwVAeD3xxQ9wjI/SOoAWD2DuhYXwF4AGa2UFAAxzgOK5OgBFzM2DZw6hCxwI+QAUW3MAEd6DJxdeogBNaAcvKjyoa55VeFURjo1Dk+nYKWUBw/uCe4JzhXmLnhAwoAleKHhTwnyx1rMPYwIeMmgUsu3h6UF/kMgD7cOBjyokIMArEH+opedAJAHzo+BdDvcMcwwBNvjIDMkMub5ZAbC19iSmDWDZGdg65p/hgE5ILsH1WgEQ7wnYFELFYfoB2kT7mO6imQNY6jPsBEfNE4bf8eGDOZGtOYAtABzxjIInE1Mx0qkfsB3oE57BeHfAw4k5m6VFy2u2mgNAPAdxb+H9g8extQ7gqBAw+gkbxjMU8w/DgQ8K/E+zDAzgD+/UsAwM3ldh3I5YBqb0PNZ4AHGvYF/wksdebssztvXcOdzv1w6AuCFY2iDMccODDBl2ePHiKwIvgrAQtAUA8TIJWcD4+kcWMB48GLBIRMDXOcJjeKgC+DC/DfNh4JXAyxAvkFoWMOb+4HeUh7cG4RdMosZLdRQAor+YcwJIxWRseEgRCkY4Fi9EQFUuBOztWwqAeNjgYQtvLbyOCAtDL7zQENpqhYBD5im8ieg7YA4HJl8jGQBzmwIEhAGaAiBCi7hvqI9lcDA/CvMhS+E4LwCGUBJAGw8vzOHBQxbhU9hLuGZM5se8HYAsNEHyAoAQD+NWFjBsBfcVYAzgBNwCCmH7sM9wDtxPeBoAzPA8w+OAviARpZQcBB1LAIgXGKYtoC7GnvcA9GH+JR7ccVZvaBcfWiF0CEgGyOE+IpSF3wIgoTw8TPAmwrMO24ftweMNOwl2g3L4uMPLLMy9xd8w/jAtAS8PtAGbwvw5vKjD8kCla7UCYGvtSfQL9xBjFl5agCs+cGETuO9WAES/Q2IbgBaJH4gI4CMU40ubBZxbLxPTHfCsRAgfugLmMfUE2cEYsyFjGR/T+HgIWcB4WQO4w/MAfdSGgL3PKJwrZAFjKgTGJDzjCJPCo47nQljCBt4k2DquDbaBVRtwH8KzA1qWjhK4IKyM8DLCyC0A9I6vuD6WVgHk4qMI4I97hCgWkqzw7AgHvODwkuIdFZa6Qbgf4IoPTIwvfNQjkoAxiVUF4gMf2zhgLxiTYek03PPariel57EGADFGwyoTcRKY5Rk7UutN2iIALjIjCwkvtHgrOLzo8bCDoePIvdTxVYoHAX5LD4Q38GDHVyJeOvCywLMCYwa04cBLCGCB+VH4UkSGI4weL9kYAMM6S2ErOLzgEcJDfzG3B0tPYGI4oCwFQDxE08n4JePCefByAfhiInhYkwygBygCcAEWwlIX+PvovsV9CP2EpwGAg69HPGwBIGEdwPhrtHRdeLnACwPvTMj0DRnCgP7Y44M2AFo4X5jriHsZMobx4AI0xusApjuBaAGwZj+AFKxThQ8CwCZe5LhuPPTja8acRtwnrGcJGwOo4AMk3QkkvSZcJ16q+MIFFISsRLxw43PgYQ0gxfWiXfQZmXyAnNoBOyrZHj4qoD/ajJdc6XnowXOAcYQXTM5DB48RkgwwxuDxw3xZjG3AGSAvPZA9iOkCsG18DMLe063g8ELBvM2QWBHa6N0KDs8JvDAx5uKQf84+tLvPwAsI8MBLGl4bTHHA9cCOYwAs2WDOXuD1h01iGgVsElAJGAnPjNL9a/UZHzjQAB8d+DDGix6hX9hyvKA3novQCbaOA2FFeNfC+nPaaxnx/AQYINsf8yKhFT4+oANsA2MyXnUBYIiPdUR7YDOAHrw3MD0FH2GlA21BE9hifGDcwJsLTzZ+33orONwrzHsNW8EBAuPlmYI9o5/xtqkYgxhPGK+ALIxdfLDGW8HhOkvLPeFDofbBX/MA5nTEfcPzD/0FiON5hfd1emifsT3Pr13rEAB3lZ8npwJUgApQgQtRAMCNjz98aLTmlF/IJV/EZcBjjgRBOGeCw+ciLqx1EQTAlkL8nQpQASpABajAXQUAevBWYl4kEkvg5UNiBjzLmmXFqCcV2F0BAuDut4AdoAJUgApQgTNTAHP+MF0C0ycAgJh/iHl+COvyoAJnoQAB8CxuEztJBagAFaACVIAKUIFxChAAx2nJlqgAFaACVIAKUAEqcBYKEAB9twn6IfswrGvka421qQAVoAJUgApQga0UwDJGWP8zzmLe6ty7n4cA6LsFWM8Jy7fwoAJUgApQASpABc5PAazdGBbSP7/eO3pMAHSIty7u/MpliTas48zjshXAkmRI9uNxPQrwnl/PvQ5Xynt+Hfcc6/mfdlNFNjd237q6gwDou+XYLeOVyzafBECflOdQG4vg13Y/O4drYB9tCvCe2/S6hNK855dwF9vXAAA87dBHAGyLxRIZBQiAV2UWfDFc1e0+XSzvOe/59SlwHVdMAKQH0GfpBECffmdWGzvhYdcqHtejAO/59dzrcKW859dxzwmABECfpRMAffqxNhWgAlSAClCBHRQgABIAfWZHAPTpx9pUgApQASpABXZQgABIAPSZHQHQpx9rUwEqQAWoABXYQQECIAHQZ3YEQJ9+rE0FqAAVoAJUYAcFCIAEQJ/ZEQB9+rE2FaACVIAKUIEdFCAAEgB9ZkcA9OnH2lSAClABKkAFdlCAAEgA9JkdAdCnH2tTASpABagAFdhBAQIgAdBndgRAn36sTQWoABWgAlRgBwUIgARAn9kRAH36sTYVoAJUgApQgR0UIAASAH1mRwD06cfaVIAKUAEqQAV2UIAASAD0mR0B0Kcfa1MBKkAFqAAV2EEBAiAB0Gd2BECffqxNBagAFaACVGAHBQiABECf2REAffqxNhWgAlSAClCBHRQgABIAfWZHAPTpx9pUgApQASpABXZQgABIAPSZHQHQpx9rUwEqQAWoABXYQQECIAHQZ3YEQJ9+rE0FqAAVoAJUYAcFCIAEQJ/ZEQB9+rE2FaACVIAKUIEdFCAAEgB9ZkcA9OnH2lSAClABKkAFdlCAAEgA9JkdAdCnH2tTASpABagAFdhBAQIgAdBndgRAn36sTQWoABWgAlRgBwUIgARAn9kRAH36sTYVoAJUgApQgR0UIAASAH1mRwD06cfaVIAKUAEqQAV2UIAASAD0mR0B0Kcfa1MBKkAFqAAV2EEBAiAB0Gd2BECffqxNBagAFaACVGAHBQiABECf2REAffqxNhWgAlSAClCBHRQgABIAfWZHAPTpx9pUgApQASpABXZQgABIAPSZHQHQpx9rUwEqQAWoABXYQQECIAHQZ3YEQJ9+rE0FqAAVoAJUYAcFCIAEQJ/ZEQB9+rE2FaACVIAKUIEdFCAAEgB9ZkcA9OnH2lSAClABKkAFdlCAAEgA9JkdAdCnH2tTASpABagAFdhBAQIgAdBndgRAn36sTQWoABWgAlRgBwUIgARAn9kRAH36sTYVoAJUgApQgR0UIAASAH1mRwD06cfaVIAKUAEqQAV2UIAASAD0mR0B0Kcfa1MBKkAFqAAV2EEBAiAB0Gd2BECffqxNBagAFaACVGAHBQiABECf2REAffqxNhWgAlSAClCBHRQgABIAfWZHAPTpx9pUgApQASpABXZQgABIAPSZHQHQpx9rUwEqQAWoABXYQQECIAHQZ3YEQJ9+rE0FqAAVoAJUYAcFCIAEQJ/ZEQB9+rE2FaACVIAKUIEdFCAAEgB9ZkcA9OnH2lSAClABKkAFdlCAAEgA9JkdAdCnH2tTASpABagAFdhBAQIgAdBndgRAn36sTQUGKPC2A9rYo4nf2uOkPCcVoAInBQiABEDfUCAA+vRjbSqgVMAKeU9TtrtVsd82nohwaBSMxamAUQECIAHQaDJJcQKgTz/WpgKrAlbAQ7WjQV7vzbTCIc5DQOxVm/WowKIAAZAA6BsLBECffqx9lQpoYK8H7p56Jmq+rKOfGkgkFHYIyypXqwABkADoM34CoE8/1r54BVqwZwE9L+C93UZqv8h5HgsgtsCQUOi8Gax+sQoQAAmAPuMmAPr0Y+2LU6AGfBrYs0LeVlA360ZZYVEDhzUoJBDOupNs99wUIAASAH02SwD06cfaZ69ACfhasKcFvV7Ae/LBlH2ksz9aQGyBYQkKCYSdN4bVzl4BAiAB0GfEBECffqx9dgr0AJ8G9iygtwHcPSG5Ma/d4kZZIFEDhjUoJBBucUd5jiMrQAAkAPrskwDo04+1D6/AaODTgl4H5KXQdlRtu2BSC4c1MCQQHtUk2K89FCAAEgB9dkcA9OnH2odTYGvgU4LeCLh7643EfumA86ghsQWGBMIBd4NNXKQCBEACoM+wCYA+/Vj7EApYoa8U0m159xSwZwW9raBu1n2ywqIKDHuhsOQhZLh41u1nu3sqQAAkAPrsjwDo04+1d1MgB32lxI0e4GvAnhb0PID3lN3EvXvilzv6oQXEJhjWoLDkJbQAIZNJHHeZVXdRgABIAPQZHgHQpx9rb6rATOirAJ8G9iygdxSwG33vLKCoAcMqFJaAkDA4+rayvaMqQAAkAPpskwDo04+1N1EgBb+cp8/q5XMAnwb2eiHvrTYRtP8kv9NZVQOHLSicDoRpqJhewc67zWqbKEAAJAD6DI0A6NOPtacpoPH2DYK+moevBXsW0BsJdw8NFv7hge1ZILEFhjUoLAKh1zuYmzNIGBxoIWxqiAIEQAKgz5AIgD79WHu4Ar3evlwCR8HL1wt8Wtizgt5omBt+TwoNWqFRC4Y1KBwGhLlQcW7OIL2CW5kTz2NVgABIAD1+OCwAACAASURBVLTazN3yBECffqw9RIEdoa/m4WsBnxb0RgBea2OSIfchaqS1Ra/mfFpAbIFhDxCavIOEQc3tZJmjKUAAJAD6bJIA6NOPtbsV6A3xKj19JS9fL/BpYM8KeltDXfe9alS0wqIGDGtQOAwIc6FiDQwyRDzLlNiuRQECIAHQYi/3yxIAffqxtlmBHm/fJOirefhawKeFPQ/kac9hvgfGChpgKzWphcPWOXqAsBQuznoHNTDIELHRclh8qgIEQAKgz8AIgD79WFutQAv8cgkdKfhl5vRZPX0l6KsBnwbErKCnaVOt7QEKtgAu7aIGDGttloCw5B10wWCPV5BJIwewygvvAgGQAOgzcQKgTz/WbipgBT+Hty8X3p0BfFrY64W8pzdF3afASzpPq4XDFhSOAsIcDA7zCjJppNNKWM2sAAGQAGg2mjsVCIA+/Vi7qEAMfikxDfT2jYC+Fqi1gK9VP9ZoFtxZ+oD+aKHMauEWSGz1oRcILd7Bbhi0egXpEbSaEsu3FCAAEgBbNlL/nQDo04+17ylgAT+Fty8X4p0NfTXg04JWD+hp297b6lrgluufFgxrbdeAsFRvOAz2zBWMO04Q3Nt8L+f8BEACoM+aCYA+/Vj7RgEP+Cnm9nmhrwZXHuCzgN5owGstU6O1ztZizNp2QjkLILbAcCQQemBQFSJOvYJp0ghB0GpKLF9TgABIAPSNEAKgTz/WloHg5/H25ZI4SsA1G/h6QG8UzG1lkT3QqAHDGUCYO28OBnPXpAoRp15BguBWZnjd5yEAEgB9I4AA6NPvimtPBD+tt28E9NVgTePd08LeKMB7+uvm2txLHjemfS0geqGwVL8ULu6FQYLgGLtgKwMVIAASAH3mRAD06XeFtWtZvWlyR2MZl9TjpwG/0nItORArefp6oU8Dez2gNxvqZllpDyxqwLAGhTUPoQUGtXMGNV7Be+Fhi0eQWcOzzPPy2yUAEgB9Vk4A9Ol3RbU3BL8cRGm9fVboq3n5WsBngb0BkPfAQ49uYm+PPfyg/zwWOGxBYQ8QemFQEyJOvYIEQb/dsAWDAgRAAqDBXDJFCYA+/a6g9o7gtzX0jQC+DtDbCuxGG2sXKGrAsBcIS97B0TCY9o8gONq02J5KAQIgAVBlKMVCBECffhdeWzvPzxnqTT1pHvArQVzJ01eDvpaHzwB7Xsh78InbeP+CQT/6Gp8X0ASHLSisAWEJ7iwwmJsvqJkrOBQEmTF84Q/TCZdHACQA+syKAOjT70JrHwT8tPP6RkHfAOCzgt7WYDfaYK2gqALDXiDcCgbT8DBBcLRZsT2VAgRAAqDKUOgB9Ml0TbVL8BcneDg8fpr5fR7ws3r6atDX8PBpYW8E5D00beuOvG0/LK14eHtMaOGwCYU1ICx5By0wmCur8Qq25gm6QsOxR5DrB7at7RpLEAAJgD67pwfQp98F1daAHy43hr9kAedaVm8P+OUSOnJcMgr6BgCfFfa2BrvRBmsFRQ0UdgPhVjCYAuNQEKytIUgQHG2/590eAZAA6LNgAqBPvwuo3RPuNYAfFIrhTzO/zwN+JcdVydNXgb6Wh88Ce17Qe1A2ngMovjmAFjBsQWEVCEveQQsM5uYLaryCLRB0hYZjEOT8wAt40E64BAIgAdBnVgRAn35nXFub3VsJ97bW8Wsld6SwloKf1ts3CPpGAF8P6G0Nd6OM9tEOSNSAYTcQbgWDaXh4KAjW1hAshYVxR7nH8Ci7Pp92CIAEQJ+1EgB9+p1pbWe498jgZ/T01aCv5eGzwN4IyBvRhsZge8AubdfSRgsKa0BY9A5aYDDn7dN4BTcDQYaFNXZ7fWUIgARAn9UTAH36nVntweHedOeO0R6/3Ny+nLdvI+jTAF8PpPXUOYLhWSAv9FdTpwaEm8Pg1iBYXUyaYeEj2P1x+kAAJAD6rJEA6NPvjGprvH6d4d4jgV9hTl/J01fz8o0EvpGQN7Kt2IA1cKY1eG1bmnI9QGjyDObmC2q8gmkZj0ewmjHcExZmSFhrq+dbjgBIAPRZLwHQp9+Z1A7wl06yKy3tEiV5WDJ70wQP6xw/j8cvA34zoE8DX5oyqeH01NnT+DTg1hMWbrU7DAZzIeKzAkGNN5AQuOcYmX9uAiAB0GdlBECffgevPdDrVwv3bgF+uTCvwdvX6+lrgVnr99hALGU1hvWUQWsDvnzAmn+9nsQW8NV+t8Kgyys42yNYyxi+ExamN1AzNq6jDAGQAOizdAKgT78D17bC3wCvn9fjp53fN8DbVwrvtiCt9XswCG252IBGAd1so+wBxhboaecIltopwWBpzmAWBnu9guk8QUtouLariDosXPIGct3A2WNh3/YJgARAnwUSAH36HbR2LuSr3MkjDvnGXj/LPL/Wci5pqHcw+JW8fT3QpwE5TZlgKLMhr9UXLYj1GrYFDjV9qZUZAYO7gWBt6Zhp3kCGhHvt+pj1CICXBoBfICKfJyKvERFc2xtE5HtF5CNXA3wXEflqEXk3kdPKsN8gIl+UGCf+++NFBHD3cyLyKSLyywUDJgAec2R39moDr58l3JuCnWaOXwqaSm/fltDXgiwv7Gnb7zSS7moaYMs1roXCVvuHgMEUzqyhYUuiSHwuegO77fZyKxIALxEA31dE3itjtA+IyK+IyPNF5ItF5B1E5AdE5CtE5KvW8p8lIp8qIu8nIr8mIgDKj1nLAirTgwB4MU+HQfCn9fqNDvcOBL/Rnj4NkFk9e5o2z8k0W/CWXosGCnuAD+exeAZzIWKVV7AFgluEhYtzAxkSPqex099XAuA1AeDHishzReRtROQPVqP5dBH5NBF5+/W/f11EvlJEnrf+95uIyItF5Dki8i0EwP6hduyaOfgbmOFb8/p5w707gl8NwlqApgW+Vjs1u3pISvuZbWuND9/Zy892bi0YtoCwBwbPDgS1YWGXN5DzAm0WfOTSBMBLBMDPXEPA8Nj9pIh8joi8cAW7d1y9e8EqnyUiPyEiTxKRN17Dwvjbz0Rm+0Mi8osignbpATzyeDb37UBev1a4N/19MviVwKsX+jTAZ4W9owCe2eySClZA1EBhDQhHwWAucWQXj2AtLKxNEqE30GvGZ1ifAHhpAPjHReTVIvKbIoIZU18uIu8hIu8qIn9bRP6QiHxEZKl/bJ3f94dXAPwNEQEkviAq8+0i8ioR+UQC4BmO8WKXJ8Nfr9evleDRAX65+X2WMO8s6NMC3wjQ055rlIVrIK11Li0Yts41EgY9XsHhoeFatnCPN5AQ2DLJC/udAHhpAJga6ONF5JUi8gEi8v4r3GF+Hz2AFzaUbZdjgb+O5V1i+KvN9Rvs9UsXbtaCn9XbV4OpmqdPA2E9sKdp12Yf25RugVuuFxoorLXbA4Ol9nJ/13gF74FgunyMZ36g1htoThDhvMBtRsWWZyEAXgsAfuDqEfybyRzAv7omfdTmAGI68mfU5wAiaozpgjiQW/LMLa2Y5zIpMGC+X0+iR22un9PrNxL8rDAI6T3QZwG+0aA3qr0ekKuZrKW9FhBuAYOHAEGtN3BKSJjzAk2P4F0LI7iHXFAcrxeRn8I/MAUMUb6rOy4NAD9MRH5Y5DT7G69chIDfU0TeeV0WBncfWcB/Y038+H4R+VtRFjDm+SEL+NkigoSQzxeRj1qJjlnAZz88LOv7FTx/Jfgb4fUzzvPLbdWWev1yod4c+FjBrxf6tMDXC2e99bYybQvcxX3S1qsBYQ8MWrx/GhBUzRG0eARr2cJeb2B3SJjrBW41nnznoQfw0gDwe0TkT61z/V4hIj++rgsImMPxTiLytes6gAgNf52IfEliRF8oIp8kIm8hIj/LdQB9Q+w4tXeAv1Fev2Qtv9ngV4KomdBnATdL2ePYX7snWshDS5qyW8Bgrh9TQNASFu7xBpZCwoTAtuGebQkC4KUB4NamyHUAt1a863xO+POGfGtz/Zxev5EePyv41UCs5enTQpy2XMksNNnHXSalrNRanqXVjAb0NEDYA4OlvmuhrwcEXfMDtd7AGBA1IWFCYMtMz/R3AiAB0Ge6BECffhvU1sLfBiHf2ly/RnZva56fJ9Sbg6wSOPVCnxbktOWC4ewNeF4DtgLiCCAcBYOHAcHU4xeDYPzbsJDwI9FtbyWHMBzsHSPz6hMACYA+6yIA+vSbXHtj+NOGfCd7/bRz/EaAX83Tp4E5TRkYyUjQe8vTLpDjj1fIg8Ma1YKhBghrZUowWKqT61cvCKYZw+n8wGHewOkhYULgMMPftCECIAHQZ3AEQJ9+E2trs30Hef5i+OsN+Tbm+rXCvaPBrwRnHuibCXyzwG60kfaA4iggHAWDhwHB2txAb0jYNC8wB4HMDh49dsa2RwAkAPosigDo029S7R09fzH8dYZ8R4R7tTCY86xZwa8Fda3frR6+cwE9q3FbwFADhC3vYHlR53Q+wnIlufK9IOieH1jLFO4JCZfmBbohEMoFEGQ42Dom5pYnABIAfRZGAPTpN6H2BPjrWeIlhr9ayHew1+8o4NeCPm1I1wt7rX5MMMA7TbYgrHV+LRS2gLDWjyOBoCssrPUGWucFEgJbZnqmvxMACYA+0yUA+vQbXHsQ/MUOkBL89YR8DYkeI8K92jl+uXKlMG8NqFqwpYE+K/C1zjnYwIY3ZwVEDRBuBYO9HkHNnMEaCJrmBsawNyok/NLIDLIZwpwTOHygTGmQAEgA9BkWAdCn38DaB4C/jUK+KfS0/rsUYh0Bfi0Aa0GfBfha57IY01MeecxSvFn25U9+oFlGW8AChS0g7IVBi1dwFAim7Zi8gVuHhAmBWnM+cDkCIAHQZ54EQJ9+g2oPSvjweP4GhHytXj9NuFc7x8/q8avB2Ajo88DeaLgbZKTigUQNFHpg0LLjB/TIZQ9rQFDj/bOAYNUb6A0Jt+YFdkEgE0NGjSd/OwRAAqDPigiAPv0G1D5P+LMmerS8fOnvM8CvF/o0Xj4r8B0V8noN2gqHXiCseQY1kBaucxQIpue0QCD6cgcEY28gIbDXJK+gHgGQAOgzcwKgTz9n7QPDX2W+Xw3+0gWdreCXC/d6Q72zwE8LfSNg743itXudVqep/oZodSFN+VwZLRS2YLDmGdwSBDUZwxYQrK4bqA0JaxaNpiew14QPXo8ASAD0mSgB0Kefo/aZwF8ly9cb8u3x+llCvSVAq4V4W94+DfT1At/WkNdrvL1wqAHCGTDo8Qj2hIUtEIh7EIOgOiRcSg4pZQgTAnvN/cD1CIAEQJ95EgB9+nXWvmz429Lrp5lHGG5SCfy80GcFvnMBPatxW8GwBYS9MOjdA1gTFvZ6A7uzhOOQMCHQaqIXVp4ASAD0mTQB0KdfZ+1axu/bRW2ucbgnRH966/XfMxI+4jYjz9/MkG8KZdpw72zwa3n6tNDnhr10DlinxXVXy6+prG5OC4UeGCyFiPcAwZb3rzY3UB0S3hwCc3sHvyyyAS4UrR4QQwsSAAmAPoMiAPr066h9nfCnWdMvLZML984EvxHQ1wV8e0NehxWfqnTAoQYIe2FwKxBMIa7lDWxBYewNJAT2GuM11iMAEgB9dk8A9OlnrH2+8Feb72cN+fZ4/fYCP42nzwR9s2EvdszkrPOpRpO1FjdAoRcGSyHiGSDYExZugV/8uzokXMoQ3iQcTE+gdTjMLU8AJAD6LIwA6NPPULs2708Z9o29LtYdPsI6f8pt3eKw75bw5/H6Wef4VbODGwstq6HPA3wtmDNYn6uoBxqVQNiCwZpXcAQIahNFUhBseQM3hUDc5ACCvdnBzW3jahDINQJd48xcmQBIADQbzZ0KBECffsrajqSPMOfvzOCvleGrmeun9fqNAr+Wt08FfT3AdxTQU1rzTbEeMFQAYS8MbgWCXm9gDQrdnsBZEKjeMo4QaB1G/eUJgATAfutBTQKgTz9F7QPCn3KNv9jzV1vfrxUCboV8NV4/zRzCcDNyWb293r7h0DcT9rTwqYAwhWHni1igUNGPGgxavYKW0HDLc7dw1t0L8HgDtckh5gWjR3oCCYHdw2JORQIgAdBnWQRAn36K2um8v/gNGUK/0aq7IeM35/nD2ULoNw7lPi3qRvz30vZuimzfveDP4/UrLedSXA+wEuZtgp8WtjzApz2HwgpdRRSgVmxfC4SNc/SAoMUj2ErkCNd3H9QOCoG9cwJ/J7qTuXCwGQJ/y2V6rFxTgABIAPSNEAKgT79G7UlJH2cAf1t6/UaB3xDo6wG+o4CedSz0gKEGCDthsOQRHA2CufYs3sCad3GoJ3AkBGb3DWZSiHXIjC1PACQA+iyKAOjTr1J7QNJHa62/DT1/rTBv/LsV/jRev9w8v03ATwNnFujTtDfKJsP7ecC2buouWaDQCYMlr+AMENQkiYyCQGhdyhAu7hoyIju4a7cQJoWox8bwggRAAqDPqAiAPv0KtY3z/noWej4I/FmTPdL5fi2whMBa+LOGeqsevxaoaaGv1U7L/jbeA/hed7zwqAXCFgxW2hkBgrn5gZqw8MiQsDY55LgQ+KLIfMIAYVJIa4j3/04AJAD2Ww9qEgB9+jUAMFCaY95fa7mXyXP+aoA2G/4OB34zoW9v0LOOgx4wHAGDBwDBVoKIxROYevt2g8CY03KeQM4HtI6QDcoTAAmAPjMjAPr0y9TWzPtTJn2cKfy1dvQYGfLNZgcXkju6PX4a8LN4+s4N9rRjxAKFGhiseQUHgWAutKvxBnpDwql3MW7vciCQ28Vph05fOQIgAbDPckItAqBPPwUAhreYcrHn3Ly/VtLHhGzfXs+fFf40y7tYlnXJreU3Dfy00DcK+DQgOsKeW+FY7Tm0QNiCwYEgaJkfmILg6JDwYSAw9vjlPIG5zGBzUgj3C9YOG305AiABUG8tuZIEQJ9+SW3Dki/aeX9XBH+ekO8w8GtB1mzoa51/qL12NNYLh7Nh0OgRzIHgKG+gZV7g5UJgbT4gl4bpGHmZKgRAAqDPkgiAPv2i2pNDv62kjxgUHev87eX508DfkHBvCeBa4KUBP6unr3XOYbY5uSErFGpgsNcrWKhnSRRJAa4nJHw2ENhaKHrIfECGgueMQAIgAdBnWQRAn34VAFSEfnu2eWslfVwA/GlDviavXw/4jYa+kcCn6ZvFtlvAZWnLAoReGCydywCCvd7AmvcOch0aAltrBLqSQjRLw9ALaBlS+bIEQAKgz4oIgD791tobhX5b8IfehBff0193c2UPPPTozb97dvioZfta5vyNmu9X2rM3O9dvBvhpPX0e4BsNeF479wCiFghbMFjrgwEEtd5ATUi4NS9wBgS6FouO7aoHAs3zARkK9g69cn0CIAHQZ10EQJ9+IuIM/R4w6SMGtV74a63vNzLkW0zysMJfC7o04NcDfa3zum10UgM9UKiBwV4QNEAgFMmBoMYb6A0J15aJ0c4JnLpQtCcppLpVHEPBY0ciAZAA6LMoAqBPvwwADgz97jDv7yLg7+jgd67A1xorFiA8CAgSAkUkAN/w+YAMBbeGjO93AiAB0GdBBECXfgcJ/Q6a97cH/Gnm+7nn+tW8cjUYa3n8tN6+UcDX6o/LlqPKLQ+c9jxaIGzBYK0/1rCwY25gT0i4vqbf3c7EZTf1BDIUrLXog5UjABIAfSZJAOzWT7PXb2XB5xmhX+O8vxLwbRX2HQp/I71+LdDSgJ8H+lrn77ZZZ0UPGGpgcAYIGsLCGm/gRUFgaz6gNhRs3iWE28Q5R+JanQBIAPRZEgGwW7+S96+y4LM26zcX+jUs9qxJ+qh5++Lf4rl6tYQP65y/FP60S7yoEz1KkNbr8dNAH2zJCn5HhT3tuLBCoQYEce4aDPZ4BHPtZfqigUB0r7VUjCVDWDsnsOZNNM0JfMnjbu9uDwSal4ZhKFg7nGzlCIAEQJvFpKUJgF36GRI/PAs+57J+J6z3V4LBI8GfGvxwP63wV4MwDfhZoG8L4Cv1RwtfXWNirWQBQk1/ekCw1K7DG9iTHDIbAkvbxz0stw+JR1/z4M3dfOzh239LCwJz8wGH7BISsoKZEOIZZktdAiAB0GdFBMAu/QZ7/3p2+5g87y/N0o0h8aHEzaWdOwipezx/avg7KviNgD4LZHbZdFJJA2et82hhUHOu2SCo8AaOhsDaEjHpbzFMlsDP5AXEvctBYG4+4JBQML2AreFi/50ASAC0W01cgwBo1m9Q4sdbRScOANgT+p0w728v+FMne+RgaCv404JYL/Rp2zfb7aAKGljLnWoEDB4AAnFpKQh6wsGHgcDRoeDqXsFcG3DMaCQAEgB9lkQANOm3UeKHM/RbWuzZm/Qx0/M3HP5KINUb7tWCmRX8tO2a7HTDwlYgPBIIDpwXuAUEjsoM3jwUrFobMI4vc5cQ3QgmABIAdZZSKkUANOnX4f0bnfixYeh3q7CvCv5mev16l4kJtmOBvnMHvtZ4sQChBgaty7ygf6V2LXMDk7Ka5BALBNYSOnAJcWJIaXmYQ4SCuxNC6AVsDaX27wRAAmDbSmolCIBq/Y7r/fNk/Y7O+E3Dx605f0Phb2uvnxb8RkGfJiFFbc+Vgq3lWLTn0MJgCwR7INAKggpv4JYQ2JMZ3J0UskVCCL2A2lFjKEcAJAAazCVTlACo1m8D719rr9+G988T+tXO+6st93JW8Ofx+s0Gv61AT237a8FeMNwTBC3ewAND4IykkGYoWLtANL2A1pE0qDwBkADoMyUCoFq/VuZv56LPkxM/Rs77s6z1d2jPnzVhxBLq7fH2HRX4WmOjBwg1MNjrESz152AQ2Ls8jGenENPSMJ6EkN+JjCa0ExJCTF5AzgNsDT8uAyNCAGxbCUPAPo0q+/2i4bDw8/qWCev+1eb+5ZZ96Uj8mB36HZX0cW9nkUceu3dH7i31op3zlytX8tD1ev00Hj8r+J0r9JXGkhUGvSDYExbOgWCunQmewFdItAbfab3weMDfXVhamxk8fGmY0aHg6g4hYVBxLmD/64keQAJgv/WgJj2AKv129v4ZEj8eutnZXUTj/etZ7Lm2VRzktHr/doW/3p1Bgt1YwG8k9FnOq7FxDZBp2kEZCwxqzjtq54/SvMBBEDhreZgZ8wFNC0Rr1wYM5egF1I4UZzkCIAHQZ0IEwKZ+g+f+7eD90y7UXMr6nTnv72zhTwtgXujTnqdpx50FNIBWa1oLg63zXAEE1jKDNVnBuA2hjcMkhNAL2DnwNNUIgARAjZ2UyxAAm/oN8P55Fn3eKPGjZ8kXb9LHdPjrmevXCvdqgawX/LTtN+12UoEWqHlDxK32R4HgxHCwxxNYAjfIqoHA3qVhuhJCcjuE1BJCOBdw8KAkABIAfSZFAGzqBwCMMzWCS2PjuX+GHT/2CP0eLuw7Gv60YGYFP227TTvdqUAL2NJujfAIXhgEaucDjgoFuxNCrPsEm7yA6R7BTAYpj2wCIAHQ99wnAFb1G+D9Q/vBA2jd8m1n719v6LeV9KHa2zcHUtqEDyv8jfD6WcDv3KGvNGYsMKgBwVZ7luze0tzEXk9gx97BsXeulhTiDQUfxgvIuYC+t3OzNgGQANg0kmoBAmBRHsPCz7Mzfxvev1GJH9qsX0voN13o+azgTwNqWvDTtKUcy7+tPaeyvVDsaRoo07bZgrfQjuactbbOCAJ7dwqZnRXcTAjJLQuziReQ28PVhxsBkACofSDnyxEAmwAYwr9p6BcVC0u/xC+sgd6/3mVfSrt94Ao0iR+1rN/hod+jeP5awKaFsFY7jfE7C/a0jw03FI4CwTOBwHS3EMt8wJ5QsGaB6KEJIVMygmMXfFgWJgywAIEMBd8fswRAAqD2SU4ANCqlDP8G7x9aD2v/hZdVLflDu+7fDt6/zUK/KRyNhr+eJV5awDYZ/PYGvtYg6QbC2SBonReY8zwOCgdbIPAooeDhXkBNMgiM7WZx6HRdQAJgayxyIWguBN22kXoJegCz+jiWfpnk/UM3gwfQsuWbd6/fmvew5v1rhn41Cz175vz17As8Av5abWTs7ejQV3qEdMGgBgRbYeFR3sBeCOxYKDr2BI4IBVsTQixewOEZwaq5gFwY2v4ypweQHkC71cQ1CIAmAEwyf1E3nf93Qd6/XUO/R4I/jdfPCH7nCn3DYNALgkeDwKQ/Fi8gNI09gd5QcO8OIbt4Abk9nOMNTgAkADrMhzuBlMQzhn97t317enT+EBJ2Zv6WloAp7fgxIvHDnPXbCv1eMPzNAr94urzmkRAvbKQpry1j8goSAm9k1YaCPQkhm3kBY2NMdwfpWhKG8wDz448ASADUPpk5B1CpVAv+0Mzg5I94PmAGAHPJHzMyf7U7hgwN/Wrm/eWWabEs9VJb5qXmuWt5/gxevxHgZ4U8pcHfKzYCDoeCYC0kbPUElsprwsGaLeMMnsBaKPhQXkDtHsG1haFNYWCYJJNB2uOXAEgAbFtJrQRDwHfU6Vj6BfVLyR+ebd8yyR+j5/5t7v0bNe9vBPx5wA/3XAl/HvDbCvhajxAPEKpBcJY3UJvYARFSCNTUbcwHtISCz8ILOHJJmLAzCLRXJ4OgMDOClzFLACQAtp7e9d8JgFkA7Nj5Y1LyR2vpF8+uHzEA9nj/Dh/6LXn+PPA3GfyOAn2lx0YvDA4DwR5voAbkcgAYOfvv6JHCatongxcQ7ZYWiN7SC9jcHSTnBZy6JEzqAYRSDAXfHZcEQAIgAdCnQBUAC9u+oc7GyR9H8P5Z1vxr7vM7MvSrnTPY8twNCPn2ePyODn0jYVAFgi1v4N4Q6AwF964NOGqfYPdcQKsXULMkDJNBOt5jBEACYIfZRFXoAewBQM3af7XwrzL546q9f9p5f9blXkrld4C/cwW/9JFj9QpOhcASPFp2DOmZD0gvoEjYHSQAnyYZpCsMzBAwQ8CLAgRAAqBPgXsAeOzwb2/yR2nHD1y+JnN4auKHxoOn8RiGe2kN/dbgTxHytXr9LgX8dgfBkidwBgRqwsgOCNQmtRl7kwAAIABJREFUhFi9gEOXhDlMGJgASAAkAI4AH3oAb1QckP07aeePVvhXA3Ajt3wzzf1rLfmSC8t6vH8Hhr+R4NdyWFofDq21ly3tWTyCbm/gCAjUhHQhQAqBmnpRmd6EkNlzAWOozM0FzC4MPTUMzK3hdOONIWB6AHWWUipFAFQDYLL0C+r1ZP+eSfg3XjdwU+/fBcLfCPAbDXytx8YIINSC4EVB4I5ewHh3kBjqLF7A4ckgDAO3hprjdwIgAdBhPlwIOoiXev/w90ICSCn5A1WCBzDM/4vfgOFvNQB07vur2fZt08zfEd4/b+i3Z85fI+yrDfl6wG9r4Gs9RjxAOAwEa8khFk+gZz7gBXkBW8kg6p1BmA3cGj6TficAEgB9pkUP4Ek/hn+1e/7Wwr/mzN8UtEZ7/3qWe9kZ/o4GfunjpRcEp0OgNTNYM6cv/g6MhWhBoMELWMsI7lkXsNcLyDCw70W6T20CIAHQZ3kEQBUARk/81vIvB8v+3S35o+X9G5n4MWre347wd3TwGwGCu0GgJSlEM69PA48VCKzNBTxCMsiuYWAuB2N4oxMACYAGc8kUJQDeeP+gTnhFKcO/qBJeGN7wL9paQ8A9W7+NCv/Gc//QpXj+3+7eP8uSL4NDv5qwb0/I99zAbysQrM4L3DoUPHlZmD29gF1h4JHZwK69gWGN15wRTAAkABIAfQrcC/9uMP8vt/dvx9ZvM7J/pyR/pJQz2/t3BvB37uDnBUGNN3A3CJzhBTTsDuL1Ah4mDDxsb2DuCpJ/yREACYA+/KEHcM/5f/FLoeL9wy0O6/9Ztn7TLP2Ctkvew8N7/zYI/Y72/F0a+HlAcBoEWhJCcAE9Id1cPccWcVovYCmjF925O4/vtjPh75tlA4cFodGpdFFo064gXA6m/nonABIACYA+BZoAuP/8v9biz1uHf5/yyGN3NB+e/KHN/M0BoNX755z3Zwn7joa/4BdxDgB5O28DSX1LokgLAptLxJTCwRYI1ABgHBgI1zswGQRNxhBY2h/4VE5uQwjlEO59ACzV3SQMbFkOhvMAlSOSAEgAVJpKoRg9gFoATJM/IOio+X+XFP61Jn9oMn81IeNg4LmynTt9tLx/e8DfKOgrPTZGweBmEGidD+hJCBk8F3BmMsguYeDe5WBc8wA5B1BEniQir/KhwHnWJgD67hsBsBcA4xeJJQHEMf/PEv5NQ7ua9f9K8/82Tf44iPfvSPA3G/pmweDuEHhmXkBvGLgVAtZ6D0M7Q3YFmTYPMHx+EQAJgD4IuubaBEAvAPZu/zZh/l8McJr5fz1r/5nCv7OSPyxz/0rev0rodxT8eUO+e4Ff+kD0egW1IOgKB1tCwVov4IGSQWasCVgK/dYAELZxszVcLRt4+DzANBGEACjCEDA9gD58JQCeALC0/Es003un9f/2mP/XvfXbnuHfgXP/RgCgB/6OAn4jQVADgZsBYDx9I75IzVzACw0DH3ceYCsRhB5AegB9EHTNta8cAFs7gOy//28OALdc/uWsw79n5v07KviNAEENAOI8m0FgzrunAcDJySBHCAPndgXJbgtnXQ/QkggCnW+SQQIE0gt4dyzSA0gPoA9fCYAn/TZaANox/y+e02cBwNLcv3SO4PD5fyPCv9rkj428f9qkjx7v37nAX3jc9ISFR0Bg19qAo+cCpu1pwDGuU1kT0AuAuD+3IVx9JnBcb/i2cJp5gEwE6XiTEwAJgB1mE1W5YgAM3r8OADx4Asgu8/+84d/RyR87ef+uAf5mQ+C1eQG12cCj5gFqlpE5r0QQWOQ1hoIJgKMB8JuUPPV7IvIJyrJHLkYAvBN0Um4BpwHA2Nv39NUEwt8OnACy2/w/DQBOXvevNvdP4/27JvjbEwI39wL2JIMYFoXWAiA0jyFQA3Kt5WB2TwT5nej1GD4iX7r+rRkCRrlrTgYhAI4GwH8mIt+iILYPFZG3UJQ7ehEC4IgEENzlAHfBfTEAAPdOANl1/t+M8O/kzF8rAJ5b2Lf0MLOGgzWh4OFewK3DwAYAhK4xBHrDwL3LwQxPBBmeCQylOA/wdhwSAEcD4KuVYPcKEXnLo9Odon8EwNb8P4h4oAxgy/y/hUtvqUdTd8j2b635fyMXf7Ys/NwJgDO8f5cCf72eQC8EDvMC9iaDeLOBJ84D7AXA1jzAzRNBuCNI4xVOABwNgO8kIr+kACdtOUVTuxYhAO4JgBvuAJJ686z7/w5d/y8FQE34F8NEGwI2zv/zLvtyrZ6/9Mk12hPY7QX0rgmoSerAxbeSQWpewAoAomnNtnCafYFbIeAY+loAePr9NQ+ebvvNWoD4j5ANHD6wajuCWDKBCYAEwIYCowFwVxrb4eQEwBYABu8fbs5br3fowFvAXWwCiBb+cIu0QLnezi3n/m3h+SsBqcbr5n0GWSBQ058aBJq9gJ4w8EHmAW6VCOLKBB4FgDDG5jxAzgHkOoDep1a5PlJF/2QmLPyt8065acsEQC0ABvjD7ekBQMcSMJYt4DwAeJgEEM/8P6P3D7fTA4BH8P5Z+xCeMBoAsz6NLACYc6Kl5xsKgKUTjgoDp55DwzzArRNBNAkkm2cCcykY43BjCHimB/ATReR56zfIa6I78wYReRvjnTpqcQLgBQDgqC3gtAD4Rqk3bvQSMBsCoAf+Ss7G0mAf7f3rBb+0f6NB0AKBrXMfOgzsCQHHH5LrDSklgsTeOBQ9QiZwNQSMTgYvYEgE4VqAExiAADgTALGw0KeLyD+YcOeO0iQB0AqA3iVg4ge/cg5gywM4AwCHZQCnMHewBJCtAPCo8DfLG6iFwBYAon9dXsAt5gFaE0HS8gdJBOlZCsYMgDEUhqhtgELXUjAMATMEPAenYJ5vhQz9Oc0folUC4AEA8IGHHr0xhgefuPz7bJeAsWYAa+brHXT+n8UDNwoALefsecJogEzTrhYANw8DH2ke4EEAEPcgQKBrKZj4Yy/1ABIANcPGWIYewJkewK8VkR8Ske8x3pVzKk4A3BoAlYtAEwCjYUQAPIkxG/5GegMJgKuanZnAV7UWID2AncxAAJwJgA+IyE+LyG8i0T25Qx/XeceOVo0A2AuA8A2Hg4tA32qxpwfQmACy1fIv5+L9GwmAaEsLgS2v42HmAY7OBL40DyBueroUzPDFoLkQ9O3DlgA4EwCfLyIfJCI/JiK/m5DbRx+N5DL9+SIR+XgRAeT9nIh8ioj8clKOAEgAvDGJ0iLQ1TUAmQDSfBSMAMCtvH8jIXAUAKJPh5gHOBoAcWFRm9pM4NFJIOjGkBAwAbD5LBhbgAA4EwCxK8g7i8gLx960TVr7LBH5VBF5PxH5NRH5AhH5GBF5BxGJM5oJgGcEgJqdPEYtA3NnoehHHrtjtHeygAmAzQFNAKxL1PIAHgYAE2A7XdXATOAjAGAJBh9e97o07wZCD2Dz+dBfgAA4EwABfgAm7A98bsevi8hXrsvYoO9vIiIvFpHnJHsdEwBnAuDTI7MJYWLHHEACYKTngC3gPBnAFo+cFwAt5xr5oNKAWe18Wg9gjqPSdg/hASQA3uwEAiluMoHDTiA5DyD+li4Fk2YBo0yYBxjG9UtXC+BC0JUhRgCcCYB/RUT+qIh8toi8fuSDdXJbgDqkkj5LRH4mOhcSWn5RRD4z+hsB8AoAsASOy/vsdoEuhoBvR0Zr/18LlBEA20+8FmwSAJct2HCUQsD4LRfKHbkdnNkDSABsG393CQLgTABE8gf2f/j9aFnLcKue0X3P5lfEh/dviMg7isgLotN9u4i8SkSwwHU4CIAEwBtjIAASAOPHUwvKWo8yegDvzvE76VVZC9AbAo4BMP43AbBlqef6OwFwJgB+bMUs/v6BTabDAwhnIaLEOBD1fuaBL29U17DLH47gWwhP5vDaWvd1CnsBl/YBRhOlLOCDhIDpAczbDEPA9bFEAMzo09rebYPt4DQeQALgqPfE0dqBT+dX1k4hMPlT+PeTVufO0To7vT8zAXB65yeeIDcHEDMxPoNzAIPqBEAowRBwAQ4bg5Mh4PbTix7A/TyA8YLO9AC2bfU8S9ADOBoA3/I0xaJ9YELG7fYN7fJbl8A8P2QBP1tEAIOfLyIftbr2mAV8uhvXA4C4Wk0CCUPAt8OUcwDvRyutDzEC4LYAWN7F49ZtGZd5+U3o4nbuYOw5vAuRS5iDcwCto2BmeQLgaADEHDmEUFsH9iZInf2tOlv//oUi8kki8hYi8rNcBzCVfwMAxClDGJhZwMsNSHf1aC0cnauDv+2cBYwuaL2A3iQQy7lGPWS84V/0QwuAmnMxCaSdBHJIAOQyMKOGZKYdAuBoAPw9EXmu4o79NSUoKpratQiTQGbOARwMgLEn7846fVEmL9cBzIynHCyKiGcOoAXKCID1Z9zZACAXgrZ7AAmAE1/wBMDRAPijIvIGxR3D2oB/QVHu6EUIgATAGxsthYBRIN4N5M5C0Kk3ruXRa3kAc9497V7A3ApuyPNGA2SaE43yAHIruLshWu4EEn9+hckav6UxyQsrQwAcDYAXZiDNyyEA9gIgpA37AXMv4FtD2xMAS265ggcQxT1eQG0IGOc5Jy/gCADUwh+0aZ2vK/x7+mrJPP9KJ8uVbWX05jrfqhOfn3sBLzcoLAIdf/xxIejmy1uEAEgAVJhJpQgBcGsAjF9MT3/d6dY88NBtPtGDT1z+/VAhrBtCvFuGgM/GA3jhAFi6PN8j4G7tFoxpz0UAXJWqLRtzaQAYf2iF9eU1IWACoHZYJeUIgATATtNZqxEADwCAMQQGAIwhsJTBG/4eL+UyYw6gCQBTSkm9b7lwbstriDZ3CAO3MoEtQDbCAxgPdYv3UfOIGAV+4VxaANSct8sDmPPooXO5E2q8f/GHW7jIXFs1D2BlEWg0GS8E/fInP3DntsUJHqNDwKXkkfD3sA8wOhSygG+2gcMfw1ZwBEDNUBtYhgBIAPSZEwHQCoDxi6AUAl7obTnSLOC4/uoBPCIAok93vIyPPHZjadU5gDkqakHgFQAgZDkqBGogzPKY0cJficficx1m/p8GAC3h30x7JQCMAQ3VzhIAb3ecFEn3Ak73AcZFMgSsGHIEQAKgwkwqRQiAFwCAy7tkecKO8gDWABC/3YHAFPBaQNdKBMnN2ZvkAcS1bDUPcAYE5nhb+0gYDX44rwX+vAD4tNoF7OEBdACgdhu4UQDYWgMQ5xnqASQAaoeloRwBcCYAfqCIfK8yK9hw0w5VlACoBUDcttJ2cGkSCMqmHsD4b+HlpPQAxjDWWtDZA4A4zyEWg0ZHWl7DXJkwtHLx0UmJIFYAG+0FzD1NSuHhGcCXnt8CgJr+dIV/ly+i+8eREkCSPmoBMPb+LUMgPGjyizmjTG4nkFa93CLQJyh8zbIeYTUEHMNemAMY/hbPqwh/Sz2AwfuHE7023MbwBRhGULByZgFzK7g5TAWzhPl9g4j8XRF58ZzT7NoqAbAFgLg9rf2Ab5/Bt1sL7wSAMSwuzLmQTwyG6X+7t4NLYczrASzB3SQvYM0DiK605gJa5+NtAYF7PFUs8If+tQDw0OHf3AVYPICVBJCT+UdzAK3z/06gJguojdwGbnMAvIE/nJkAeH9M0wM40wP4eBH5MBH5RBF5loh8v4h8vYj84B4P10nnJADuCYC4qcZM4JYHsASA6d9LWcS7rAWIzrWgMX4HxINhwI4gJ8irUFwLAHPdb43XS4PA0fAH/YZ6/0rEuVUCSHr+A2YAx+A4fRu4hU6Xo+QBJAA2HiMEwJkAGIv/jisIfrSIYLu4v7P+L+eTaD37j/Q7AbAIgLhN6yd9ywOIolwL8K5dt4Bu5jzAEpF1hoFPgKgYtdfqCdwa/k5waJ3/5wn/4oS15VyiR8WNmbTKHxAAy1vJde4DrFkCRgWA8cOCIeDbRxEBcCsARL7nx60Q+OYi8psi8ifWvXa/VfFuOGoRAuAdP0N4S4RXWgMAcVcnLga9cOX95I6cF3DGUjA4fykTGL9NTQTBCUbPA8y1GY3Mrb2AOPW5ewKt8IdrboV+T4BXeWKa4a92Uo0HUDOf0BL+TYBSO/8P1Y6QAYx+3MwB3HUJmPjTjDuBHBUyZvZrNgC+7wp5HyAi/0hEvk5EvltEXi8i7y8if0/5PJupgadtAuBJvfC6GQiAC70txwZLwSzvFH8mMNo5bCIIOjdpHuDpVdJw4c3wAp4zBO4Bf6fRavX+lQBQA38JrN08bNM+bACAWyWA4Bo3zwCOP87MS8CgMgHQAwLnWncmAP7qGgP8phX8XpAR6TdE5BnnKp6IXDEA4q697XrrjAAYvxQ2WgsQp8ztAtLaESQkgcT1g73uOg8wB3OtsLEFAFHWuDdwCwI1AFg7be05cW6ewFnwdwK8ilDD4K8EdinI5cq14K9VZ2L49y683Z4oDu9OzQBGB9JdQLgEzCREYAh4JgAi5PttcSL6pLu4Z7MEwJP6SgBE0dZSMHFzmkxglL/ERJAcCbVCutrlWw7uBbx0CNwL/k5D68K8f7imvXYAiWEx/vchEkDQIS4B02ADAuBMANwTzLY695UDIGSGF7AEgPhdmQjSuxRMBwCiylZ7AsfnOjk2oh1B8N9D5wFqoBFltABYI7GDJYTEA/6o3sAe8AvX5Z33NxT+ToacecT2eP+iR8RNi4YEkD3n/5Wg7xAAeA/+0NtcAsg1hn6DpREACYA+VCQA9oaBw0M+hIBxHyZkAi/NbpsIgnN2zQNExRisekK6Gi9gKfd+gyVhcIkzQ8FHBEEP+OF6NPB3ArzGs2yq908DcrmLsULjgPX/lmHWtwB0XLdnD2DUv5cAEo/7NPyL39JFoOOQcHMJGK7/Vx4WBEACIAHQp4AXAHH2jeYBltYAbM0DXCDylo40awkOWQ8QJ25BYGs5mBQqw90+Ay9g6Kp1eZjUoPfyCG4FfpvCH07W6/3TAKDB+4fmjhb+RZ/OKwGEHkDuBOJEgCuuTg9gLwDGLxILAC40thwTt4RD855t4WIATNs6bBi4BIs1ApscCh4FgaGd2TDohb7QT63Xbxr85WCtBH/4u9WTFy50g+xfnGr08i8x6MX/nrYFHE4SXOelBaBRxpwBTAAkAF4xwTkvnQCoBUAI3VoQ+oLmAeJyh4SB0dCZegFP76wBS8OMhsDRMDgK+jaHvxrQjV74OQeUDvhDc9r5f6OWf1m+j+6HjocvAI0TefYA5g4gytc6Q8AMAStNpVCMANgEwMg90AJAFN15HuDyTtSvB4jyU5eD6QFATR2UscwFzLUZBoXDCxg7NjRD0RsO1pxjzzIjPX+4jmHz/mqwuIP3LwXAeO9f/ObZ/xf1c3sAa+YN1sK/aHef+X84M3cAuT+uCYAEQN/TngB4DwDjT/0BO4LEUDhgQegY2DRz+XYJAy+uhtuj5QHMwZwmGaQEgSWgmxQKtkJgjUV9w3m/2hbwO4Gdoqtd8BcP3/QcM+f+5QAzFqUz+QPNnkX4d6HO5Ui9f/EAScO/8bNCHf6NG2QImCFgxcOERbIKEABvADB+LSl3BIkf+t55gGjLuB5gCQZHbQuH9ndLBslRUgnsRiSEpNCaDJdWKLgHAi8BBK3gd3j4a4FcsIuB4V+t928xUX/2L9oJnr5Nwr81AIzHtBoA4zx8AiABkHTXqwAB8KScckcQFG2FgSfNA8SptcvBLO+wehg4hsf03zFAbpYMgk6MzAiuAV3HDiGnd5gyfqtdJiYetMqme8f58HqzwO8EiK3Gc548VLTM+0N5Teg3166mXtqXqM/auX84tdX7hzq7hn/RAc7/Gz7e8g0yBMwQsM/UCIAqAIzeFi0AXEhtOUKcK4bCMwsD4zIO5QUsgZ3FC4g2DgiBtW75hvm42i02K51JE/KdAn9odGToNweOGyz9spj9WO8f2sx5Ah+Oz/OaB0+39Gbu3wnwHrfc5th7N239P5yI8/8IgHkFCIC+ZzsBMAuA+KMyDBw//L1h4DUEjLM/8NCjN3f2wScu/w4eQPw7N/9v1HqAyzvzdrVWLQCinmlnkBzM9XoB0ZYFAjvnA+I0Mz2B4aYfzSPYC34nqFM+o7o9f/FwTc+lhb8SKLb2/c213+n9i4EM/y55/9Jyd5du0e//2xX+zQFgvLAz5/8prX1EMXoACYA+OyIA3uinDAMHDyDqbbwvcAyBey0KncJndU3AHOC1EkJyEOdJCMn1QUNZlczgUH0LENR01fcIyNf2AF9ocRj4leAsnGir0C/ON3Du38k0n/zAzQ2IgawGgGVw08NfCSJz3j+UVWX/nuBwvZx09w/8ubT+X5j7hzLc/9cwnAmABECDuWSKEgDVABg9/a8gDLy8cw/iBURnzhwCcQk9cwNLw3u0h3AE8FnBD+WbXr9zgj/09Uy8fzEAuhZ/jsEuwF/8t3TxZ/ym3v4NhRn+Lb/iCYAEQAKgT4E7teEFjP0WO4SB0R9HNjCq50LBpeVg0vKaNQHvneORx+6oeCcMjF9Sb1rLC4g6o0PBuX6EXjvCwSewM9LYSBAcaPzuprQevxtQ1FBnKeEjB1uh4VKdXPJGCTBbod9cvQr8ofjRkz8WblvmGT66zv3Dv7u9f6fBsd6Uocu/XHPmbzxMCYAEQN9jmx7AewCIP4RXWQMAUfSCw8DLO26AF7AHAj2h4BxAhvvcs0ZgDR4j+7lWENwc/LaGP5xvYuj3BFyyJFvgmD33Lz3fkMWf0SjDv763sbk2AZAAaDaaOxUIgD0AiDoHCwOjS8F7Z00Gieum/9YuCXOCxcgTaPYC5iDLA4HWXUJw/pYnb+C8wNjsztUjaAW/06eV1+tXg7/liyV/aJZuKbXdgr9cvcrCz7V1/2oAWJr7hzq5pV+WIWXf+u0EiLtl/+LsYfAy/Ft/vRMACYAEQJ8CVQCMn+yTdgXBKcIzOn5pVMLAS5X76/zN2Blkeafu5AWM3wXxfZo1H3AQBKIZqzcwXN7RYbAH+tTgVwO4IFANILeAv1wfHaHfE2xdovfvNAjWmzY0/Is2GQJelCUAEgB9+EMPYBYAT6+s9ZdJYWC0PnhNQDQ52wuIcwxbFiYHXDkvm2Y+INrS1A33u+bNa3kCS+fKjMVeEIzfn74h7q/dC31DwQ+NzYS/XPsar2GuT8pFn2vwt5hYe90/lDu092/p4HKUkj/wmzr7lwB4O6IJgARA3/OdAHhPv9ZyMKiwvhlKYWAUsawJGC8UrfQCttYEjGEQ//ZsD5fW794dJAdOGm+eNhRshcAWyLVAUBESDublAcGbNnxjXV3bA3zhJKpQbyhcS/ToBb9omN65cMsuIoNDvydz61j2JQXF3nX/6u0Ykz9isBu+9h8aZ/i3PWAJgATAtpXUShAAs+q0ILAAgAspLUcKgPhbujNI8ADit0oYGD+HhaHDotBLldvQbM7zN2suIM7d7QXUQKDWk6eBx3B/S3MCvRDYqp/Y1wgQzJmsNXQ8AvJy/RgKfqPhLx6fcedzXrwe719l3l8KfymMxYkfi0kd0PsX23pt8efYGEveP7Rl3vuXod+7Y44ASAAkAPoU8AAg6m6cDIJTancGOZWV2x1FtvICnt6zWywNgxOdIQSi27NAcMJgUDVpAr8SiKVn6gn5og3Pci+l+o7t3lrwh9/3yvzFuatLv6DAJlu/4URM/lANtptCBEACoM1i0tL0AJoAEIX3SQbBmbVewBj8NACI8g9FE+g0ySSoMzQUnIO5I3kCS7CZ2o8hLByqnisMmqFvBPi12tgD/jJ96l3z7wSLCu9fPO8PdeKw8JTM36Vjy7HJ1m/xgAsuRXoA7z5uCIAEQAKgT4FibWMYGO2U1gRcCGs50jAw/mZMBjkBnnJ/4BgGl/fU/bBxDQBr9VMIjMHxdC6vFzB+6cT3STsnsAZjPcvExO+kltV1gCCaPDoMdkFfBpCK8rWWibFk+oaTaPbrRVlN2BflJmX9LuaeD/3it83n/uGkM71/aF+d/EH4uz9mCIAEwNaLqP47PYDdABi9MUYlg8SgqEwGWarkoa6VEZzCncYLmEJkzQt4CAgsQST+3jsvcAMQDGa5NxB2A18NvnJjrhf8SuBWg87eOX+D4Q/NjQz9lgCyvHdwBJuH2PkDV8DkD/0rnQBIANRbS64kAbAJgCigXBImeADjl48mGQTlD+YFTOGwFEpGOVcoOAdo2nl9Wk/gLAjcEARjM50FhW7YizvZyuwNZVvgVwO5g8EfujM79ItzWJZ9QfkWAGa3fUPFXu/f0snlSJd+wd/MyR+oRA/g/VcVAZAASAD0KVCtrQwDo42NvIA4Vc9cwBToDhUKPjIE1uAxtp3WkjFx2c7w8ERDH9O0FvpwNi/4nRn8pSCmzfpN642Gv1P7tV0/YvufMvcPJ2DyR98AJAASAPssJ9SiB7CpHyAwXjSjsTD0Tl5AXMaI3UGWdm4JpZQQgnK928ShbnOrOBTa0hMYv4dyNqGFNgsIauGyaaM7FrBAnxb8FuMqH6VEj1q9kWHfzHlqnr8U4vDf3tBv2qYmcUS95y8a3937h04g+YOev/JAIAASAH3PfgJgU78BXsAQBl7oajlipgx/m7AuIE6lyeqNy8QAqK2PcsPnAx4NAi3AZgXBYIda0Gza7aQCVuAL3dB4/Frgh98vDP4Wkxq/5l8KiHcTSO7P/Xvs4QdvDSbAX2zvVu8f6pZ2/rhJ/EAhev/6RyoBkADYbz2oSQBs6lcCQFRsLAkTv9BGzAVEe8o9gkvgdi9Td2JWcNqHkxzWzGAvBJbqt2CuliDSqhvbVC8IHgUIe4HvqOBXgkhtprBjsWecemboN4a+1ry/U1lt4gcKBwAMu37Efxu28HM8WLn0S/PVxL2AhQDYtpJaCQKgSr8BXkCcx7I9HMordwc5gdbgZWGW09tDwah3OE/gLAi0gGCtDyobTAqN9hR6QS/untbbd/oiUFz8KK/fgeEvhrf039Y1/+ptVbZ8Q8UR3r/g+YvHx73ED/xI75/C+ivh3ZhwAAAgAElEQVRF6AEkAPosiACo0u+yvIAnYDTuEJLWqXkSUwhsrQ+I8tPnBLYArGfNwNh2rEDm9Qyq7HbDQhbomwl+aLvUl951/jL9Tef8nVgn2uc3hbCa568GbPhtZuIH2r8J/+bgb+nActD7t+GA0pyKAEgA1NhJuQwBUK3fzl7A+CW0hoHxp5ARfAK01QuIf1sSQpamfQtEp21YvYDDIRANlsK4JfhqQVwrLHyiALVB3RY8Vxi0Qt8I8Ku1YQG/Uju5Nhph3xb84Xdt0kcKgxr4qwHksMSPGADj+YAhUpsu+xKPBXr/Oh4KmioEQAKgxk4IgD6VTrUHewEXSluO2u4gcbnM4tAxBOYA8ASGkbdPkxCS1imFgtNyMUTit7OEQA3EaUBQ007JKo8KhD3Ap4U+lKuFelvtnAn8LWbh2+2j1oZl7l9X4gdOHmAvhT/81rXuHyoGo+fcP/3LigBIANRbS64kPYBq/QIAxsRWWBIGRSzrArYg8PZ9cXfOlDMhpAZwadj2IiEwfu/k7KDlzZsNgmmftgLDXtBL+6uZ3zcL/Ertlvq0geevF/5Qr7XXb1qmlfWL8tNCv/HHT5f3Dw1w+Zf2q4kASABsW0mtBAHQpN8GXkD0x7EszAnqMqHgFPY0nsCepWFwnl09gfHLJ7231pBwra24bS0Iatsz2eTBCmuhTwN+izGVjxFeP7R+MPhDlzSh35K3zwR/ONmIxA+0Q+/fxoORAEgA9JkcAdCk33G9gLiMETuEpAB3KAgsAZR2wWjUr8FazcPW8gYGO7LA4CUAoQX4tNDXC3619juXeUGT1oQP1Jmd9IFz9AJgM/S7EOhyWBM/Ypum98/0drEXJgASAO1WE9cgAJr16/AC4hxhh5DwIvIsDh2/IA0JIag2cj5grb0UJPHfQ+YEWiCwBlhHA8Fgh1rQNNvtoApW4Aunbc3vC+V6PH5W8EN5hdfvSPC3mHJ7wehu719sdyMXfUbHbxZ+Tpd9wY+c+9c/MgmABMB+60FNAmCXfq2M4OiNlM4FjOGttjg0yh0kFJyCnnankB4IPNVpLRa9NwRaYc3qFczZ5NZg2At6cd9HQF9orzYvsXQex3y/HPyly7ygTAxc+O8Znr/p8BePJy38oU6a+Rvb6D3vXzwIXrTeVcJf1+vnphIBkADosyACYJd+KQDGLoXC7iAoknoB8bfBO4SgydbSMCnQWecDLmyaXyQ6bXtzCMQJrcu89HoDrSCI8iNgsGWzJVgcAXWtc2uhbzGM9jEb/Ar9aO3t64W/tP6MxZ5P58jt9oEfRq/5F0NkgD/8rej9iwcpM3/bAyFXggBIAOyznFCLANit32Av4EJVy6HdJzh9eQ3ICk4BrrQ+4B4QiHPeWzA6fvHE99IKgS0402bgWj11WwBht40rKlqATwt9KNcDfrX2B4Z8jwB/aR9Mod8W/J0Acb33tTX/UMSU+IEK9P4pRpWyCAGQAKg0lUIxAmC3fhslhMRg+PSos7mlYSbMB1zeqflFokdDYAqfp3Mn4WATBKLwaBCstRnbkhUE47pHhUIr7MXX5PX2oa2RW8Jl+tOT7IFuWcK+KbhpPX814DPB3wnuHrfcmZ55f6hnCv2iQmvLN5Thsi/2VxEBkABot5q4BgHQpd+ghBD0wRoKjsGwsUD0CawcS8OcDQSmL7Vwb3uze1sgNssrWLLJVn9cthxV9oCeFfpQvrXuYA/4ldotgOjVwV88VnLz/mLQCxHaHPzF7ahCv6jAuX9jhioBkADosyQCoE+/yg4hYS4gTrC+wTQJITHY5ULB+D14AhsLRKPoqPmAMyEQbbcyhE/n38MbiBNrwEsLgyVIddvhARrQePlCN1vQFw2b4pVZkjwWA753aMAPlVrJHsttjQfk/Tp3PXV3O1Na6Dk9t2WnD9R1L/mCRtw7fqARhn7Hj1ACIAHQZ1UEQJ9+GQBEgxN2CInBsBUKPkHi626u7CohsAZaPWHhGSAY7pAnXOy2X0cDFuA7GPihO4S/KJwLQWrz/vD7sNBvTJUM/faPQAIgAbDfelCTAOjTb619kFBw7OUwAiCqatYIXE6hmxNYazPI3to1JG3jdP6MJxB/VyeIoHBvWFgLgq1ztOzuaFDYA3sW6EPZVui5Z41Apdfv9L3w5Afu3JXU64cfW/P9UKbkpVsYaqznb2kzWh+wlfXbmvcXgx5Dv61RuvPvBEACoM8ECYA+/aLaE7OCcZYQDo6jTDlP4KD5gC1464XALNBFQInf03Bwrk4JBLMQeHq7F260BwQtMOgFwlz3R0GiB+5y/dKEd0O9FvSdbnRlkJbO5Zjrl0JcOHsL/lJgTP97BPylfTPBXzwOeub9oT6zfoe9MfwNEQAJgD4rIgD69KsAIH4yhILjF512lxDUmTgfcE8IzIFg7KEMwpu8gb0gWKsX249mrmBc3jJvcJidTmjIAnw4vRf64qGVXo4B/E63NfH65eAvBb/FHPTz/VD+UPC3dGg5clu94e/d8/5QuZT1GzfM0K9/JBIACYA+KyIA+vRLam8UCsZZa7uExDB5gsT++YBHg8C0PzUQLHoDZ4Ng/A602tfRodAKe+H6NdCX2m1OO6PHD030zvVD3YuGvxgAc+v9xaAYPH/x2GHWr3V0Dy5PACQA+kyKAOjTL1O7IxSMVqy7hFwoBC4MEL+N9CHhU11tpnC4c7UwagvGtCFYq2ewZJOt/oyy5V7IS88/G/oawKgFPzQzYr5frp3Dev6mwh8aZ9bvqOFYbocASAD0WRkB0KefAgBRZGAoGM1p5wOmL8iDegLRzTS8m0IgynjmBqJ+l0cQFTXgpYVBtDcKCIfbrrNBLfA1wO2mFzUQrcwLzIEf2tSEe1Gux+t3tvCHjofvrVzSB35XzfuLDTuFP/zG7d6coytTnQBIAPRZFQHQp1+htiEUjBas6wOeAQTmoC7ePzj3+0gIPDGGJVs43EmPR1DTRsnezg0KLbAXrlmbbLIB+OWArRf+LMkeJxCtzB+sJZJ0J3zEkId/5+b9DYe/+MuJ8DflNSMEQAKgz7IIgD79GgAYk1r8VguLRCcLRKN4LRSM32v7BeP3yWsEpuDWgrb0dysEnkAuCQnjb1pv4BQQjN9tLfuxeAZzbe0Nhj2gF1/HCOhbjKB4WDx+HvDL1b0I+MOF1ZI+Fmpdju55f6jMxI/W48L2OwGQAGizmLQ0AdCnX6W2Zq9gVD9/CEyhMAU2KwSm7VkgMFc33KThHsHQsCZEHMp6gdBirwEevRBnOacW+NCmZq7hZPBDN7YI+S4MFa3XJw/eUXU3z98w+ENDpXl/hD/LENKXJQASAPXWkitJAPTp16idhoLjt15lqzgU8ySFoP4ET2AKVynYxf9thcAcuGWXfVF6A4eD4PIGbx8WGNwDCttXoC9hgb3QqhP60MwIj58W/FCutb4fytSSPSzwd9+jaFjkObXR1lp/MfwtF7Ec5oxfVOK8P/3AGVWSAEgA9NkSAdCnn6L2wPmAOFtYIzBehqy1ZzDqDdo32AKBKGsFwRz0bQ2C6Hc1YUQLgyjXA4RHA8Me0LMA32Io1aMEfadbkVnLLwdu4QQaj1+p/siQb3qOw8IfOhpCv6+Nb1O63l9s8Jz3p3g5OIsQAAmAPhMiAPr0U9SuhYJRPZkPiD95kkJS2MstFJ2+cI3ZwbMhMG0/9985uAw3wzI/8NROIVlEBYIWGPQCYcvaNB5KBWy1TlP9XePhCw0owLIH/ErwlgO/5fbdXdQ5Vz+3TIzF69dqcyj84WTahZ7jsvh3d8ZvDv7wN877c42namUCIAHQZ10EQJ9+ytqXAYELW5b3AS7tJZyDtZxXr5UgMgIES220QHAKDAbr8XgJlRY4pZgF9gZB3wnYBnj8tOCXA7cU/HJlRmT6ntpt7e27XMjdg/A3xdyP1ygBkADos0oCoE8/Q+0BSSELSS1Hbrs4/L0VDk6dHca9gy0QmIMta0i4BGzasDDq5zyCNRAcBoO5l7PBYlzhY8t5WmV7QM8AfCha8/TVoC8HX+HUHo9fqd2RXr/0HPEyL13w1zvnDyeref7w+03oN05LZ9JHa+jM/Z0ASAD0WRgB0KefsfakpJCFym6PFgSm5Q8GgUv37ro1tHMDT/CWSRSZBYJotzlfMLYSbZjWaFk3xVveRA/MafqkCOuGZlrQtwX4lUCvNdcvV8+6P3B8jkPA30nw9e5Ul3tBGSZ9aIbD3DIEQAKgz8IIgD79OmqfLwTiYh984qM31xyHg0+/ye1v6X9rPHat5WJy5yj9bTQIntqrzBUMophgMFSaDYUdVqqqYoC9UdBXAjb83eLx04Ifylm9fmnbrSzi0gLPaOexh6PlYl7yuNvbEtvMCM8f4U9l8scqRAAkAPoskgDo06+z9nVCYA7WWiFh1Em9gbNBsAaV4YZrYBBlu4Awtqq94bAD8uLua7x8J/YozOsLbeWSMMJvW4FfDho9Xr8FLvPLvBD+Oh+tV1WNAEgA9Bk8AdCnX2dtR1IIzqjdLQRlB4WD0dQDD916+GJP4AJpuuSQElwdFQRHwmAwFjcUdlrd7Gpa2Av98EAf2jgS+OXgULu486luKdkDP+7q+UMHNMu9oBwzfmePsbvtEwAJgD6LIwD69HPUvmwIzIFTLUSM8rm5e5qwcAnScmHn0nnCjSwljITfS23GhqD1DqbGcy5gaAU9LfDlICrVqAR9KJdbzqXUZsmj2Ar35s7TCvHWlngh/DkeoVdflQBIAPQNAgKgTz9n7TOBQFxlYa3AE3x1zgssgVuvN9AKglvA4OkcirmDLUPaGg57IS++jpaHL5SthXdRpgf6vOCXq9+zXqB2fT+crzjfb6HO22OTOX84HT1/rXG57+8EQAKgzwIJgD79BtQ+MAQuhHR7KCEQFSwJIjlw03gDl/PkJ8lZsoa9IFgCz5pxjIDCAcY3rAkt7I2AvoWH7i/eXGtb6/ErgePIuX6nc0Qh3yr8ldb4Q6WXFKAwbMKBn2NYVG/xRvgbNjCmNkQAJAD6DIwA6NNvUO3zhEBcvHZeYA6SNJA2AwRbwFZaRibc7FaYuNV+y2iOCodWyIuvs+XlQ9map68H+kowt3DR/eyWXB9b4Jc7x5SQbwpzhL/WMLqC3wmABECfmRMAffoNrF3LDMZpKlvG4efRiSFos7R/MH7b0BuI0+0BgqXzxjddA4OhvGb+oNagRkOiB+7SPmtgL9TxQF8N8EZ7/DSgZwE/tNcV8kXF3eAPJ+cev9oxOr8cAZAA6LMyAqBPv8G1DwCBJ7iLLksJgajh8QaifitJZCYI5s6f3tyWZxDlLUCoOedgAxvenAX2cPIW8KFMLbxbg77ab70ePw345cqoF3Y+AV20vt8iwO1Rmu+HEvFv08O+hL/hg8fdIAGQAOgzIgKgT78JtQdB4EJLy1HaNg6/WZeJidvFvyNPIP4zhsAT4EQJIvhv69zAEiRpPYLLOfXzBMMNbXnrNDCItqxAmBpUqx8TDPBOk1bAS/ujAb6Fecpz+nKAFZ/H4u0rtaVJ8MjVdXn90GBpiZcU8DRev7hObr4ffs/u8IEfagkf+J2ev9ljzd4+AZAAaLeauAYB0KffpNoTILAGghoIXEjq9kinUDlCwjnI08wPRL3ZIFgC0PTGa4FwBBROMjp3s1rY0wBfC/pqv+e8fbPBb2GvuxCrTvRYBLk9Ys/eCRILv1m8foQ/t30frwECIAHQZ5UEQJ9+E2sPSgxZKOn2KHkDSxCImqWQcNr2YG9gCb4028rVwK3kEdTAntYjZwHCcHO83sKJxninaQvohYotD18o1/I41n7fAvxyIGkCvxPQFbZ0Wyjy9ojBL/1tE/iLT8JFnrcaX/rzEAAJgHpryZUkAPr0m1x7R08grix2aGgh8ASMr7ujizcs7AXBWTCoAcYgRA8QloxrFij2gF2pj6OALwdc8Tkt0Id6vaHe4eC3dObuoVnfDzU2gb/4RIS/yQ/6zuYJgJcEgO8tIj+C5LDVGnBtrxCRZ0TWgZ3Bv0ZEni0ifyAi3y8inyoir4zKfKiIfMla74Ui8rki8l0FCyMAdg697appIRA9evLSrSdEvQvZwfiTxhOIcoNDwmjSCoEW6NN6BFvA5vEMBsW1HsIZYLidTd6eSQt6oUbLw6cpV4K+HKSF9kaCH9p0ef1S+OsJ+S6duD1Mc/7CfD9Uf1HUyMuif3PO3x7jyXZOAuClAeAPiwjiA28oGAKA701F5MOxz7yIfIeI/K6IfPBa/j1E5EdF5CNE5HtF5INE5JtF5D1F5OczbRIAbSNup9IdEBiDYAkCUWZmSBjtO72BXhBcuDd9wy63sQZrNRhs1Y2NxAqEqYGN9Bz2GK8V8NJzjAC+hXXur9vXgkXv1nC5vg8FvxTivCHfFCxDwsdr47tC+OsZB8esQwC8RAB8vIi8PmNw8ATCo/cuIvJL6+/49y+s3j58yj1fRJ4kIh8S1f/ONdjwCQTAYw5jXa+cEIiTWL2BsScQ9Ush4fS3hbpujwYEnoCqkS08EwRbQNeCwVb99P56oVBnL9uX0sIeeqYp2wN9CwPlM4pz59T+rQV+OO+ddf3wB+1cv1PZ6H6l3yvDQ744Fz1/24+Q0WckAF4iAGJkvpmI/OIayv3x1Ww+UES+XUSemJgRrABh3+9bvXzwCj43KvPZKxC+OwFw9ADcur0dIBCXOCJBBO1sDII1MKt51jyewWARvZDXW28rS9SAW64v2npbQF8JQHs8fk3wW4j07tGT6IEWukO+qEzP31ZjZLvzEADPAQC/UUQ+dg3r5vqLkO37rK/Zp4rIL6+zuD5ZRL5URBDW/cci8lEi8uVJTiZsDY7+54jIt4rIr65lvj4yQrSD39+BALjd0Jx3Jm12MHqwzgnEPzXzAlFOExJGuV5voAIEU2/gcrr7YVztUjE1EMRvvTC49Cu/xmDu/o+Gu1HtaeFMa9OW9mrAVwK10A/rfsAe8DvVre3fiwK1BZ1TgDuVjxTt8fqlcNlc4w8Vcp4/ZvtqbftY5QiA5wCA8Ni9ecVwfl9EXl34HXMCf3JN5Kh5ABHyxfxAzPPr8AA+S0TeZO0COPGZx7Jz9iZRIAeBKILvh3A0to5DMWtIGHW03sCFju4elbUDUbCVKLI0qQNBlC0BUg2cPDC49E8PhEGcUSC39TCxgF7oWwv4TqAlyHXLH6Ogr3SeNNR7KjcT/HCC0o4e6W+aRA/Uyc75a4V8UZHZvluPIfv5XiAiv7JWw0yxn8K/Me3rVfa2zr/GOQCgR+V/KCI/LSKfs87z+yci8q7RHED8G9D3R9ZPO8wBRGIHQsLh4BxAzx04bF0LBOIijN7A2BO4kM3tMWpuIFpMwsL4Uy8Ioq7FK1gqHy60lYChBbceKEzNTnuuUebaA3fpuTWwVwKxuK0e6Cu1W9415P68wSb44SRbeP1wHg38dSd7EP5GjZtt26EH8JIA8M+vaP9PV4/hJ4nIl4nIn44yeJHZiyzgj1yzgL9tXTbmL6+Gh3AxlpJBFjA8gsgC/iYR+TPMAt52aG5ztskQiIvo2UbuBHaJAkZvYA4ET8CWJIssbOr3CnphsFU/Zw8jwHAbO6ufRQt6oRUNXI6EvhIMarx9qHsvucMLfqjf4/VDvdjB3B3yRUMM+x5h7Pj6QAC8JADEen3I1IWrBt9ySAL5YhH5schIEBt5noj8pXVOIYAQ6wDG7l+EgzF3EF5BZA3/dRH57oKhcRkY3wg8SO0B8wJxJZqQ8EJct0fNG3gAEKyBWc2r1vK4tbyDQaBWOzUDOgogWgEvviYN7C1cM34vYI+3bxPwSzks/Y7ReP3QhsnzR/A7yEN7QDcIgJcEgAMMwtwEAdAs2VErHMgbmELiwUGwBomt34I1aIFwBBge0QK1oBf63gI+lKu12fPbYTx+Kfjhv0sZvgsd3x70+h3R/HfqEwGQAOgzPQKgT7+D1R4EgbiqHm8g6lmSRHKg2EgUQZV0juAJ0jKh4aV5+yLQLa9d6/deKDw6HFohzwJ7LeBr/W7x9p3aShI78LchoV40pF3QOQU//PcUr19KnEz2ONiDu7M7BEACYKfprNUIgD79Dlrbsl4gLsGYIIIqvUkiqNuaH4gyuY0fFAkjW8Pg6XzyqNoOrJ5CdcNrwVZfeiFO2w+NZy+0penLKE+fC/pQOZfcXdvCLQd3pQWda+CH31RePxRsZfoS/LR2fB7lCIAEQJ+lEgB9+h249gbewBQE02lc3vmBThAcDYMW2GuBWM5wZsPhKGO1QJ4F9k6QVlkCpvZ7Lrxbgj78XeXtmwF+KRjGHr/0fDH44TfTXD9U4Hy/UTZ/zHYIgARAn2USAH36Hby2FQJxOQpvYApmNW8gylpBEHVaWcMok/EI4s+WEPFyqnyYWAN8FtCzlNUY1ihg7AG6Wv9aEBfXbZWt/V6CvhL4ZaEPhdOlXHLglzORWqg35a8U/PDfpXAvfhvm9UNj9PxpxtP5lSEAEgB9VksA9Ol3JrVzIWF0PbdwdAUC8VNpbiB+2wIEU/gMd0AZHj5BXWG+YAsGNUCoLZMazmg4nG2YLXDLnV9Tp1XGCn3ox1Bv3wkYk6ur7eLRAr8UNt1ev5g8CX6zx8G+7RMACYA+CyQA+vQ7o9oDvYFnBoLobs4r6IVBC+yNBLyRbcUG3IIvi7Fr29KUGwZ9J3h73P3L0MzvOwz4oSOtuX4oQ/iz2Ot5liUAEgB9lksA9Ol3ZrVLEIjLUHgDUay0pzB+SxM39vQIoj+GEHG4kR7voAUIY8OZBXSzjVMDb2kfNHV6gA/nMYV4UUEDfqm3D/VGevzQXjHcix8fiSQsgR+KcL7fbHs/XvsEQAKgzyoJgD79zrS2xhuISwv7CePfhbmB+CkOC88AwRPMZaTOrR2cyx6eAINosjZ3MO3tCMgb0YbGYDWQ1mrH0kYN+HCe3JIt4fxToA+Nbw1+OKcqyQMFXxbJT/Br2eLl/k4AJAD6rJsA6NPvjGvHEIjLiDM1St7AMwLBHIiGu9XhGUTVmncwNG2BwlBnK7AbbawWyAvnbsFeC/jw+xDoQ0OaxI5cuZi5cr/XMntRXj3PD4U14V6UY8h3tH0fvz0CIAHQZ6UEQJ9+F1B7cFgYioz2CKLNnLdP6xXsgEFUKc0bvAG3SjJJahg9YJi2sRUo9oBd2lcN6IU6NQ9fFfjwY25OH/6eC+96oA91p4IfTsBw7wU8UDe8BAIgAdBnbgRAn34XVNsZFoYS8fzAFARzoVnrHEELCJbKdsKgBghRRuMljI1mBBjuaYQW0EM/W7DXBL5R0HdqJ6NczitoBb8UQKsevxr44TeGe/e072OfmwBIAPRZKAHQp98F1taAYDw3EBJE8wNngCDaTNcSnA2DaL8QKg43veUhDOWsUJgzqq1B0Qp2uT5rYM8FfCloxZ0oLe3YC31oO23TFepNwQ//rQn3MtR7gQ/dzksiABIAO01nrUYA9Ol3obV7wsJGEERxa9awBQRPAFe4Pblwcq4/afUGEKK4FgpHwuGeRqiFvNDH4vy9+CJKYd1QxhLeRZ0c9OWADn9LvX27gl/aIcLfnrZ+vHMTAAmAPqskAPr0u/DaBwFBqJyDNq1XsAcGBwFhMBArGKaGNcKLaDFWK9ilbatAL1TqBb4SxM2APrS5mceP4Gex1estSwAkAPqsnwDo0+8KamuzhSGFIzScA650jqAFBEtle2FQA4Sntl9ntgkvHJpPOKiCCfK0sIdyJQ9faMMS3q1BosbbNx38cILSPD/8Rq/fIHO9wGYIgARAn1kTAH36XVHtHUEQKm8NgzWADHe9tOZgzio6wDBtZitQ7AK7tLMtr15cvhf40IYlvIvyvdCXA1NTcgcaiOf4Efyu6OE56VIJgARAn2kRAH36XWHtDUEQ6rbmCYY7oA0Rt8CuNG+wVa8HCkOdAXC4iyFaIC90sAV7KFfy8NWAr1ZPC31ooxXmRRmC3y7mxpOmChAACYC+UUEA9Ol3xbW18wMhkTE0jCqttQRRRusVRNncfMEW1NVgsAaeOauweAtrVjUbFnugLtdfDei1YK8FfFboK5VPoQ/l0v6n0Icyd3buwB/idfzw3zWPH37nLh5X/AAdcOkEQAKgz4wIgD79WFs2BkEorllTsAZ3JRhsASF+HwmFsfWMAsStLFILeHF/ap69UK4U0g2/19rIefo80Ie6BL+tLIrnMStAACQAmo3mTgUCoE8/1r5RYCAIos3aotLhnCVosngG0dZsIAz9LS0/02tFo6CxB+ZqfdaA3kzgs0AfyuauvxnmRUV6/HpNl/VGKEAAJAD67IgA6NOPte8p4AFBNNZYVBpF0vAw/maBQZSvwZgHCIMeGk9hqt1oQJxlnRbA04JeKNfj4SsBH/6eC+9qoQ/lmmFeFGKod5apsd2aAgRAAqBvhBAAffqxdlEBCwiikcY8QRRJvYJbwCDOUQPCFkym+vSAocbKrPDYA3GafrRCuHEbrT6UQrotWBwOfThhy9uHMvFyLvhvzvHTmAzL9CpAACQA9trOUo8A6NOPtZsK1LKGUfmpSQspCOLnxCs4EwY1QNcCwnBFVigL9WZBYvNeNQpY4M4CeqFsL/Ch/ibQhxNZvH0oz3X8vGbH+iUFCIAEQN/oIAD69GNttQJWEETDnV5BVM2FifF3a6hYA4Qoo4VCLxyq9d64YMubl3anBXsoX2vTAnxoK5fMgb/fC/Hij15vH8FvY+u70tMRAAmAPtMnAPr0Y22zAi0QRIMDvYI9MIg6uUSS+Fq13j0rGPacw3wPjBWscBc3rwG9Fuzh9xLw4bdSEosL+tBwy9uHMukF0uNntC4W71aAAEgA7DaeU0UCoE8/1u5WIAVBNJTSUgqCKOMIEddgEL/VsmpbQIj6WigMmnngsFv3CRW1kBdOrQHKHuBD+8OhD43W5vaFiyL4TbAsNllVgABIAPQNEQKgTz/WHqJAj1fQAIMomksg8QAh6rrkoIwAABBmSURBVGqgsAcMc5puDYtWqMv1WQN6qFeDPfxeW6bGBHxoLA3v4m+ppy8HffgbvX1DhjsbGaQAAZAA6DMlAqBPP9YersCOMOgFwqCFFgxDeavncLjmnQ1qAS803wK9UK4H+FA3O5+P0Nd5d1nt8AoQAAmAPiMlAPr0Y+1pCvSGiNGhXJgYf89kE+PPJe9gCwjxu2UxZisY1rQdDY1WmKv1TQt6aKO1CHXJw2cGPlTIefrwd4Z4pw1jNjxRAQIgAdBnXgRAn36svYkCvV7BDhhsAaEGCq1gGGs4EhJn3BsL3MXnb4EeytZgrwp8+DEX2rVAH8oyxDvDZNjmLAUIgARAn20RAH36sfamCmi8gqFDuQSSSUCohcLQNYvXcFN9nSfTQF44RQv2NgG+HPThb0zocFoCq2+iAAGQAOgzNAKgTz/W3k2BmTCIiyqEi8P11sLGsSal9Qg1uh0FFC1gl16XBvSasIcCVg8f6qSh3dC5XIYLoU9jkixzJAUIgARAnz0SAH36sfYhFMjBIDpWSp21egfDRTagEMW0YBia9ADiEbTXAl7oazFRI76YEuyFMtq5fDXgw2+EviOYEPvQqwABkADYaztLPQKgTz/WPpwCVhjEBZSAEL+VEkoMUNgDhjldt4JFK9Tl+qoCPVTshT3ULXn48FtpHRtC3+GGLDvUqQABkADYaTprNQKgTz/WPrwCWwOhEQxj/azew720V8Nd3MEW6IWyJe9eDfhqixYS+PYyE553tgIEQAKgz8YIgD79WPvsFBgNhEGAlqcwFkoRSh6hawDKLmDr6YAW8tB2DfTCuenh67kLrHMtChAACYA+WycA+vRj7bNXoAcIcdG1sHEsigUMd4BE9f2zwF3cqAb0at690BZDuupbxYJXogABkADoM3UCoE8/1r44BUpAiAvV7MemBcMez+ERxdYCnsar14I9/M6Q7hGtgH3aQwECIAHQZ3cEQJ9+rH3xCtSAUAuFQSQrHKbi9noTrTfJCnVp+7XQbVq2tekwgc9691j+WhQgABIAfbZOAPTpx9pXqUALCq1gOAoQt7oZFsDTePVCGcLeVneQ57kEBQiABECfHRMAffqxNhVYFdBAYSqWJqR8DgK3vHi5ayDsncOdZR+PrAABkADos08CoE8/1qYCSgWsgHg0OLRCHgFPaRgsRgU6FSAAEgA7TWetRgD06cfaVGCAAlY4HHDKIU0Q8obIyEaoQJcCBEACYJfh3FQiAPr0Y20qQAWoABWgAjsoQAAkAPrMjgDo04+1qQAVoAJUgArsoAABkADoMzsCoE8/1qYCVIAKUAEqsIMCBEACoM/sCIA+/VibClABKkAFqMAOChAACYA+syMA+vRjbSpABagAFaACOyhAACQA+syOAOjTj7WpABWgAlSACuygAAGQAOgzOwKgTz/WpgJUgApQASqwgwIEQAKgz+wIgD79WJsKUAEqQAWowA4KEAAJgD6zIwD69GNtKkAFqAAVoAI7KEAAJAD6zI4A6NOPtakAFaACVIAK7KAAAZAA6DM7AqBPP9amAlSAClABKrCDAgRAAqDP7AiAPv1YmwpQASpABajADgoQAAmAPrMjAPr0Y20qQAWoABWgAjsoQAAkAPrMjgDo04+1qQAVoAJUgArsoAABkADoMzsCoE8/1qYCVIAKUAEqsIMCBEACoM/sCIA+/VibClABKkAFqMAOChAACYA+syMA+vRjbSpABagAFaACOyhAACQA+syOAOjTj7WpABWgAlSACuygAAGQAOgzOwKgTz/WpgJUgApQASqwgwIEQAKgz+wIgD79WJsKUAEqQAWowA4KEAAJgD6zIwD69GNtKkAFqAAVoAI7KEAAJAD6zI4A6NOPtakAFaACVIAK7KAAAZAA6DM7AqBPP9amAlSAClABKrCDAgRAAqDP7AiAPv1YmwpQASpABajADgoQAAmAPrMjAPr0Y20qQAWoABWgAjsoQAAkAPrMjgDo04+1qQAVoAJUgArsoAABkADoMzsCoE8/1qYCVIAKUAEqsIMCBEACoM/sCIA+/VibClABKkAFqMAOChAACYA+syMA+vRjbSpABagAFaACOyhAACQA+syOAOjTj7WpABWgAlSACuygAAGQAOgzOwKgTz/WpgJUgApQASqwgwIEQAKgz+wIgD79WJsKUAEqQAWowA4KEAAJgD6zIwD69GNtKkAFqAAVoAI7KEAAJAD6zI4A6NOPtakAFaACVIAK7KAAAZAA6DM7AqBPP9amAlSAClABKrCDAgRAAqDP7AiAPv1YmwpQASpABajADgoQAAmAPrMjAPr0Y20qQAWoABWgAjsoQAAkAPrMjgDo04+1qQAVoAJUgArsoAABkADoMzsCoE8/1qYCVIAKUAEqsIMCBEACoM/sCIA+/VibClABKkAFqMAOChAACYA+syMA+vRjbSpABagAFaACOyhAACQA+syOAOjTj7WpABWgAlSACuygAAGQAOgzOwKgTz/WpgJUgApQASqwgwIEQAKgz+wIgD79WJsKUAEqQAWowA4KEAAJgD6zIwD69Duz2i8QkWeeWZ/ZXZ8CvOc+/c6xNu/5Od41e58JgARAu9XENQiAPv3OrPb3isgHnFmf2V2fArznPv3OsTbv+TneNXufCYAEQLvVEAB9mp1xbb4YzvjmdXad97xTuDOuxnt+xjfP0HUCIAHQYC6ZoqsH8LNF5M19LbH2GSjwgyLyF8+gn+ziOAV4z8dpeS4t8Z6fy53y9RMA+GVo4kki8ipfW+dZmwDou29vKyIv8jXB2lSAClABKkAFqMBOCrydiPzWTufe9bQEQJ/80O9tROTVvmZYmwpQASpABagAFdhYgbcQkReLyBs2Pu8hTkcAPMRtYCeoABWgAlSAClABKrCdAgTA7bTmmagAFaACVIAKUAEqcAgFCICHuA3sBBWgAlSAClABKkAFtlOAALid1jzTeSjw3iLyIyLy2NpdjJFXiMgzou4/KCJfIyLPFpE/EJHvF5FPFZFXRmU+VES+ZK33QhH5XBH5rvOQgL1cFfgiEfl4EUG2/8+JyKeIyC9TnbNT4AtE5PNE5DUigvGM+V5Y6+Uj1yt5FxH5ahF5NxF5VES+QURw7+ODtnB2t50dbilAAGwpxN+vTQEA4A+LyOMqE4MBfG8qIh++vlC+Q0R+V0Q+eBXrPUTkR0XkI9YXzQeJyDeLyHuKyM9fm6Bner2ftUL9+4nIr4kIIOJjROQdVpA408u6ym7j3r2viLxX5uofEJFfEZHni8gXr/f3B0TkK0Tkq9bytIWrNJvLv2gC4OXfY16hTYEAgI8XkddnqsITCI8evAa/FHkQfmH19mFZILxMsLbUh0T1v1NEXi4in2DrDkvvpMCvi8hXisjz1vO/yZot+BwR+Zad+sTT9ilQA8CPFZHnrqs5wJuP49NF5NNE5O3X/6Yt9OnOWgdXgAB48BvE7m2uQABAgNybicgvrqHcH1978oEi8u0i8sSkZ1hVFGHf71u9fPAK4sUSDqwWDiB8982viCe0KoCQL0KBzxKRn4kq/9BqD59pbZDld1UAAIh7hhAw/veTIvI564ccIP8dRQSe3nDgvv/E+hH3xrSFXe8dTz5RAQLgRHHZ9KEU+EYRwdc+5v/k7B4h2/cRkaeJyFPXuV5PEJFPFpEvFRGEdf//9u4n9LIxjuP4uyhpUkJEITYkEqVokiwoYkGxmijlTynThMRoIn8WI6lZmIgUNSPK34UoIQsSFnZqSkaMJVlIg/TJ99bp172/7vx+97lzzj3vu5y557nPeT3Pqc/v+Xe+A7YBzwCnr7m7X4GMDu0DDtR3Xuh8J+Xk/zOF6KffAjkY9mAFg+87VU3wzxsD7up39a3dGoEL6qzWn+q5zfOb5/liYA+wpZZrTC47v57/M4EEQPuCXWolBQyAK9ms3tQUgYzYrfe+vsPrHOidNYEZNchGjvVGADPCl/WBWefnCOBwu6EjgMNtu3lqnuUd2bB1I3C9I4DzkPmdVRQwAK5iq3pPixb4GPiypo2yBvCHGj2YrAHMSEJC39n1asCsAUyIyJTw5OMawEW3Stvypq37OgTscA1gW/gllD4JgPljLiP5u9esAdxeG4DWWwNoX1hCQ/kTbQUMgG19LX14AtfWrsAfa8Tw7npj+NbODt4cIZFdwDlGIs/Q/jo25qa63Uwv5SiZ7ALOiGB2Ab8KXOku4MF0iKwZy9E+OeonYXBXTf+f5y7gwbThpKK31M7+bMLKEo9MAWdH/kX1/GaaP3+0PVUbP/LMPtvZBWxfGFyTW+F5BAyA8yj5nTEJZJo3O3VPAv6sRf85HuKzDkLOAczu0Bs6Z4olLGR92OST6eCsHcyoYHYNPwK8MybIFbjXx4D8AZD3hX7tOYCDbdF3gctrrV/O9MyGrpwLmGCfz4XA83UOYKaG99bGr+4N2xcG2/xWfJaAAdC+oYACCiiggAIKjEzAADiyBvd2FVBAAQUUUEABA6B9QAEFFFBAAQUUGJmAAXBkDe7tKqCAAgoooIACBkD7gAIKKKCAAgooMDIBA+DIGtzbVUABBRRQQAEFDID2AQUUUEABBRRQYGQCBsCRNbi3q4ACCiiggAIKGADtAwoooIACCiigwMgEDIAja3BvVwEFFFBAAQUUMADaBxRQQIH/BT4FrgD+qlf45bVhG/nk1WJfAMcBrwO3baQQr1FAAQVaChgAW+patgIKDEngE+BzYNeCKv0KcIwBcEGaFqOAAgsVMAAulNPCFFBgwAIGwAE3nlVXQIEjEzAAHpmX31ZAgWEInAp8C+wG9lSVHwLuAS4Fpk3vTguAtwNPAk8Duf5k4E3gvir71poyfhx4cQ2NI4DD6CvWUoFRChgAR9ns3rQCoxDIer6PgGuA44H3gKsqGE4DmBUAXwKeAx4FzgC+AQ4BO6vMm4H9wDnAz52CDYCj6GbepALDFDAADrPdrLUCCswncC/wMHBsBbiEuVmfWQFwL3AC8E9d+FYFyus6Bf0ObAPeNwDO1zB+SwEFjq6AAfDo+vvrCijQVmALcBD4AzgX+HcDAfAJ4KzOda8Bh4E7Ov+WEcH7gX0GwLYNaukKKLAYAQPgYhwtRQEF+inwBnAicFpNBz9oAOxnQ1krBRRYroABcLne/poCCixPYAewHbgEOAX4qkbt3p5RhVlTwI4ALq/N/CUFFFiSgAFwSdD+jAIKLFVgK/ABcHVt2siPZ7PGy8BlwIEptdlMAPwFeMAp4KW2sT+mgAKbEDAAbgLPSxVQYKUEPqw3gfxd6wV/2+Dd5U0gOVA6G0/yJpA7N1iOlymggALNBAyAzWgtWAEFFFBAAQUU6KeAAbCf7WKtFFBAAQUUUECBZgIGwGa0FqyAAgoooIACCvRTwADYz3axVgoooIACCiigQDMBA2AzWgtWQAEFFFBAAQX6KWAA7Ge7WCsFFFBAAQUUUKCZgAGwGa0FK6CAAgoooIAC/RQwAPazXayVAgoooIACCijQTMAA2IzWghVQQAEFFFBAgX4KGAD72S7WSgEFFFBAAQUUaCZgAGxGa8EKKKCAAgoooEA/BQyA/WwXa6WAAgoooIACCjQTMAA2o7VgBRRQQAEFFFCgnwL/AQSjir9Q7LP1AAAAAElFTkSuQmCC\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\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('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x10f52fa20>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.linspace(-1000., +1000., 200)\n",
    "y = np.linspace(-1000., +1000., 200)\n",
    "z = np.array([0., -100.])\n",
    "\n",
    "xm = 0.5 * (x[:-1] + x[1:])\n",
    "ym = 0.5 * (y[:-1] + y[1:])\n",
    "zm = 0.5 * (z[:-1] + z[1:])\n",
    "\n",
    "Nx = len(xm)\n",
    "Ny = len(ym)\n",
    "Nz = len(zm)\n",
    "\n",
    "SHP = (Nz, Ny, Nx)\n",
    "\n",
    "ZM, YM, XM = np.meshgrid(zm, ym, xm, indexing='ij') # full 3D arrays of cell center coordinates\n",
    "\n",
    "DX = np.abs(np.diff(x).reshape((1, 1, Nx)) * np.ones(SHP))  # column width (3D aray)\n",
    "DY = np.abs(np.diff(y).reshape((1, Ny, 1)) * np.ones(SHP))  # row widths (3D array)\n",
    "\n",
    "x0 = 0.; y0 = 0. # center of the island\n",
    "\n",
    "RM = np.sqrt((XM - x0)**2 + (YM - y0)**2).reshape(SHP) # distance to center\n",
    "\n",
    "R = 750.0 # [m] radius of the island\n",
    "\n",
    "IBOUND = np.ones(SHP)\n",
    "IBOUND[RM>R] = -1\n",
    "\n",
    "k0 = 10 # [m/d]\n",
    "k  = k0 * np.ones(SHP) # uniform conductivity\n",
    "\n",
    "kD = float(k0 * np.abs(np.diff(z)))\n",
    "\n",
    "rch = 0.01 # [m/d] recharge rate\n",
    "FQ  = rch * DX * DY # [m3/d] cell inflows\n",
    "IH  = np.zeros(SHP) # [m] initial heads\n",
    "\n",
    "Phi = fdm3(x, y, z, k, k, k, FQ, IH, IBOUND) # run model, return heads\n",
    "\n",
    "# plot the heads a contours\n",
    "plt.figure()\n",
    "plt.xlabel('x [m]'); plt.ylabel('y [m]')\n",
    "plt.title('Circular island with radius R={0} m and recharge N = {1} m/d'.format(R,N))\n",
    "plt.contourf(xm,ym,Phi[0],50)\n",
    "\n",
    "# plot the heads along the cross section and compare with analytical solution\n",
    "plt.figure()\n",
    "plt.xlabel('x [m]'); plt.ylabel('y [m]')\n",
    "plt.title('Heads through the center of the island')\n",
    "centerRow = int(np.floor(Ny/2))\n",
    "plt.plot(xm, Phi[0, centerRow, :], label='Numeric')\n",
    "Island = np.logical_and(xm >= -R, xm <= R)\n",
    "plt.plot(xm[Island], N/(4 * kD) * (R**2 - xm[Island] ** 2), label='Analytic')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Notice the difference between the analytic and numeric solution. This difference depends on the size of the number of cells that are used. The finer the model, the better the agreement. A small agreement remains because the boundary of the numeric model is not perfectly circular. We will a develop and use an axisymmetric model in the next chapter."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Circular polder\n",
    "This circular polder is also a circular island with fixed boundary at distance R from its center, but instead of a uniform recharge we have leakage through a semi-confining top layer that we will simulate using an extra layer.\n",
    "\n",
    "Within the island we have a fixed head above the confining top layer. As an extra example we can choose to extend the polder to not be surrounded by open water with a fixed head but by other land where the head is fixed above the confing layer but at a different value.\n",
    "\n",
    "Much of the set-up below is copied from the previous example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "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('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\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('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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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, fig.canvas.height);\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;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
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       "<IPython.core.display.HTML object>"
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     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x10dd7d710>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import scipy  # we need bessel functions\n",
    "\n",
    "I0 = scipy.special.i0 # bessel function\n",
    "I1 = scipy.special.i1 # same\n",
    "K0 = scipy.special.k0 # same\n",
    "K1 = scipy.special.k1 # same\n",
    "\n",
    "z0=   0. # m, reference elevation, ground surface\n",
    "d =  10. # m, thickness of confining layer\n",
    "D = 100. # m, thickness of regional aquifer\n",
    "\n",
    "R  = 750. # m, radius of island\n",
    "x0 = 0.; y0 = 0. # center of the island\n",
    "\n",
    "hp = -2.0  # m, maintained head r<=R\n",
    "hl =  0.50 # m, maintained head r>R\n",
    "\n",
    "c  = 250. # d, vertical hydraulic resistance of confining layer\n",
    "k0 =  d/c # m/d vertical conductivity of confining layer\n",
    "k1 = 10. # m/d, conductivity of regional layer\n",
    "kD = k1 * D # m2/d transmissivity of regional aquifer\n",
    "lam = np.sqrt(kD * c) # m, spreading or characteristic length of aquifer system\n",
    "\n",
    "# The grid, coordinates and size\n",
    "x = np.linspace(-2000., +2000., 200)\n",
    "y = np.linspace(-2000., +2000., 200)\n",
    "z = z0 - np.array([0, d, d+D])\n",
    "\n",
    "xm = 0.5 * (x[:-1] + x[1:])\n",
    "ym = 0.5 * (y[:-1] + y[1:])\n",
    "zm = 0.5 * (z[:-1] + z[1:])\n",
    "\n",
    "Nx = len(xm)\n",
    "Ny = len(ym)\n",
    "Nz = len(zm)\n",
    "\n",
    "SHP = (Nz, Ny, Nx)\n",
    "\n",
    "ZM, YM, XM = np.meshgrid(zm, ym, xm, indexing='ij') # full 3D arrays of cell center coordinates\n",
    "\n",
    "DX = np.abs(np.diff(x).reshape((1, 1, Nx)) * np.ones(SHP))  # column width (3D aray)\n",
    "DY = np.abs(np.diff(y).reshape((1, Ny, 1)) * np.ones(SHP))  # row widths (3D array)\n",
    "\n",
    "RM = np.sqrt((XM - x0)**2 + (YM - y0)**2).reshape(SHP) # distance to center\n",
    "in_polder = RM[0, :, :]<=R\n",
    "in_land   = np.logical_not(in_polder)\n",
    "\n",
    "IBOUND = np.ones(SHP)\n",
    "IBOUND[0, :, :] = -1  # maintain head everywhere in confining layer\n",
    "\n",
    "k = np.ones(SHP) # uniform conductivity\n",
    "k[ 0, :, :] = k0/2  # m/d, top layer\n",
    "k[-1, :, :] = k1  # m/d, bottom layer\n",
    "\n",
    "rch = 0.01 # [m/d] recharge rate\n",
    "FQ = np.zeros(SHP)# [m3/d] cell inflows\n",
    "\n",
    "IH = np.zeros(SHP) # [m] initial heads\n",
    "H  = np.ones((Ny, Nx)) # m, maintained head in top layer\n",
    "H[in_land]  = hl # outside R\n",
    "H[in_polder]= hp # inside R\n",
    "\n",
    "IH[0, :, :] = H  # use in initial heads\n",
    "\n",
    "Phi = fdm3(x, y, z, k, k, k, FQ, IH, IBOUND) # run model, return heads\n",
    "\n",
    "# plot the heads a contours\n",
    "plt.figure()\n",
    "plt.xlabel('x [m]'); plt.ylabel('y [m]')\n",
    "plt.title('Circular polder with surrounding land, semi confined regional aquifer')\n",
    "plt.contourf(xm,ym,Phi[-1],50) # contour bottom layer\n",
    "\n",
    "# plot the heads along the cross section and compare with analytical solution\n",
    "plt.figure()\n",
    "plt.xlabel('x [m]'); plt.ylabel('y [m]')\n",
    "plt.title('Heads through the center of the polder and land')\n",
    "centerRow = int(np.floor(Ny/2))\n",
    "\n",
    "plt.plot(xm, Phi[-1, centerRow, :], label='Numeric')\n",
    "Island = np.logical_and(xm>=-R, xm<=R)\n",
    "\n",
    "# Analytical solution\n",
    "RL = R/lam # shorthand\n",
    "\n",
    "# head at x==R\n",
    "xPold = xm[np.abs(xm) <= R] - x0 # inside polder\n",
    "xLand = xm[np.abs(xm) >  R] - y0 # outside polder\n",
    "\n",
    "# head a x==R, analytical\n",
    "phiR = (hp * I1(RL) / I0(RL) + hl* K1(RL) / K0(RL)) / (I1(RL) / I0(RL) + K1(RL) / K0(RL))\n",
    "\n",
    "phiPold  = hp + (phiR - hp) * I0(np.abs(xPold) / lam) / I0(RL) # h in polder, r<=R\n",
    "phiLand  = hl + (phiR - hl) * K0(np.abs(xLand) / lam) / K0(RL) # h outside polder, r> R\n",
    "\n",
    "plt.plot(xPold, phiPold, 'r-', label='Poldm analytic')\n",
    "plt.plot(xLand, phiLand, 'g-', label='Land analytic')\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The analytical solution matches the numerical one except near the edges of the model, where the model is closed and the analytical solution is not. The numerical solution, therefore, becomes horizontal near the boundary, indicating no flow across it. One also notices the distortion of the circular color field in the first figure due to the boundaries of the square shape of our model. Notice that the only boundary conditions in this model are prescribed heads in the top layer, which are different inside and outside the radius `R`.\n",
    "\n",
    "One nicely see both analytical solutions, one for the land outside the polder (green) and one for the land inside teh polder (red).\n",
    "\n",
    "There is a small difference between the numerical and analytical solution in the center. Again, this may be due to the fact that the circular polder can't be perfectly circular due to the rectangular cells of the model. But the larger the number of cells, the smaller the difference will be.\n",
    "\n",
    "It is important to note that we used half the vertical conductivity of the top layer. This is because in the model, water flows vertically from the center of the toplayer, where the head is fixed to the bottom, that is, it passes only half the cell. To keep the resistance of this lower half of the cell equal to the given vertical hydraulic resisttance, we have to use $ k0 = (d/2) / c $ instead of $ k0 = d/c $"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## More efficient coordinates\n",
    "One sees that to set up a model, there area quite some lines that deal with the grid coordinates. This can be done a lot more efficient with a Grid class, the instances of which are invoked with the grid coordinates, after which a large number of variables can be requested from it, variables that are computed upon request."
   ]
  }
 ],
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