Convergence_block_coordinate_MM.ipynb

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    "We want to solve a 2-d problem with Gaussian increments over time and Laplacian increments over trials, with loss function (negative log-likelihood):\n",
    "\\begin{equation}\n",
    "L(x,z;\\Delta N) = \\sum\\limits_{k=1}^{K} \\sum\\limits_{r=1}^{R} \\left[ -\\Delta N_{k,r} \\, (x_k + z_r) + \\log(1+e^{x_k + z_r}) \\right] + \\frac{1}{2\\sigma} \\sum\\limits_{k=2}^{K} (x_k - x_{k-1})^2 + \\lambda \\sum\\limits_{r=2}^{R} |z_r - z_{r-1}|\n",
    "\\end{equation}\n",
    "\n",
    "In order to improve convergence and allow the use of\n",
    "Theorem 4.3 (Stationarity With Block Alternation)\n",
    "from [Jacobson&Fessler, 2007] (also on our slack channel),\n",
    "we replace the L1 norm with a Huber loss with small quadratic region (e.g., $c=10^{-3}$):\n",
    "\\begin{equation}\n",
    "|x| \\simeq\n",
    "H_c(x) =\n",
    "\\begin{cases}\n",
    "\\frac12 (c + \\frac{1}{c} x^2) & \\text{if $|x| < c$} \\\\\n",
    "x & \\text{if $|x| \\geq c$}.\n",
    "\\end{cases}\n",
    "\\end{equation}\n",
    "\n",
    "We obtain:\n",
    "\\begin{equation}\n",
    "L_c(x,z;\\Delta N) = \\sum\\limits_{k=1}^{K} \\sum\\limits_{r=1}^{R} \\left[ -\\Delta N_{k,r} \\, (x_k + z_r) + \\log(1+e^{x_k + z_r}) \\right] + \\frac{1}{2\\sigma} \\sum\\limits_{k=2}^{K} (x_k - x_{k-1})^2 + \\lambda \\sum\\limits_{r=2}^{R} H_c(z_r - z_{r-1})\n",
    "\\end{equation}\n",
    "\n",
    "We can now write a quadratic majorizer w.r.t. the variables $z$ as:\n",
    "\\begin{align}\n",
    "\\phi_z(z;\\bar x, \\bar z) &= \\sum\\limits_{k=1}^{K} \\sum\\limits_{r=1}^{R} \\left[ -\\Delta N_{k,r} \\, (\\bar x_k + z_r) + \\log(1+e^{\\bar x_k + \\bar z_r}) + (1 + e^{-(\\bar x_k + \\bar z_r)})^{-1} (z_r - \\bar z_r) + \\frac{1}{2} \\frac{(z_r - \\bar z_r)^2}{4} \\right] \\\\\n",
    "&+ \\frac{1}{2\\sigma} \\sum\\limits_{k=2}^{K} (\\bar x_k - \\bar x_{k-1})^2 + \\lambda \\sum\\limits_{r=2}^{R} \\frac12 \\left[ \\max(c, |\\bar z_r - \\bar z_{r-1}|) + \\frac{(z_r - z_{r-1})^2}{\\max(c, |\\bar z_r - \\bar z_{r-1}|)} \\right] \\\\\n",
    "&= \\sum\\limits_{k=1}^{K} \\sum\\limits_{r=1}^{R} \\left[ -\\Delta N_{k,r} \\, z_r + \\frac{z_r - \\bar z_r}{1 + e^{-(\\bar x_k + \\bar z_r)}} + \\frac{(z_r - \\bar z_r)^2}{2 \\cdot 4} \\right] + \\frac{\\lambda}{2} \\sum\\limits_{r=2}^{R} \\frac{(z_r - z_{r-1})^2}{\\max(c, |\\bar z_r - \\bar z_{r-1}|)} + \\mathrm{const}\n",
    "\\end{align}\n",
    "which is quadratic in $z$ and can be solved exactly in one iteration using a simple Kalman filter-smoother.\n",
    "For the quadratic term of the likelihood term, we have used the following fact about the second derivative of the logistic loss:\n",
    "\\begin{equation}\n",
    "\\frac{d}{dx}(\\log(1 + e^x)) = \\frac{1}{e^x + 2 + e^{-x}} \\leq \\frac{1}{4}.\n",
    "\\end{equation}\n",
    "A less conservative, expansion-point-dependent quadratic majorizer is the one with second derivative $\\max(4, 2 + |\\bar x_k + \\bar z_r|)^{-1}$. Even less conservative options may be sought if needed.\n",
    "\n",
    "A quadratic majorizer w.r.t. the variables $x$ is:\n",
    "\\begin{align}\n",
    "\\phi_x(x;\\bar x, \\bar z)\n",
    "&= \\sum\\limits_{k=1}^{K} \\sum\\limits_{r=1}^{R} \\left[ -\\Delta N_{k,r} \\, x_k + \\frac{x_k - \\bar x_k}{1 + e^{-(\\bar x_k + \\bar z_r)}} + \\frac{(x_k - \\bar x_k)^2}{2 \\cdot 4} \\right] + \\frac{1}{2\\sigma} \\sum\\limits_{k=2}^{K} (x_k - x_{k-1})^2 + \\mathrm{const}.\n",
    "\\end{align}\n",
    "\n",
    "Because the function $L_c$ is coercive and the majorizers have uniform upper and lower curvature bounds, conditions (R1), (R2), (R3), (C4), (C5) and (C6) from [Jacobson&Fessler, 2007] hold. This guarantees the convergence of an algorithm that cyclically alternates MM steps over $x$ and $z$.\n",
    "\n",
    "A possible advantage of this algorithm is that it uses one Kalman filter-smoother over $x$, then one over $z$ alternatively. In a sense, $x$ and $z$ are improved gradually together. Alternative solutions perform multiple Kalman iterations over $x$ for a fixed and possibly suboptimal value of $z$, therefore spending unnecessary effort trying to fine tune $x$ to refine a solution which is off anyway because of a suboptimal $z$ (and vice versa)."
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    "import numpy as np\n",
    "import scipy as sp\n",
    "import scipy.special\n",
    "import scipy.linalg\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt"
   ]
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   "cell_type": "code",
   "execution_count": 2,
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   "source": [
    "def Do_Kalman_Likelihood(y, sigma2obs, sigma2e, x0):\n",
    "    \"\"\"MAP solution, inverse covariance matrix, and marginal loglikelihood of state-space model\n",
    "\n",
    "    :param y: Observations (K,)\n",
    "    :param sigma2obs: Variance of observation noise (vector)\n",
    "    :param sigma2e: Variance of process noise (vector: sigma2e[i] variance of x[i] - x[i-1])\n",
    "    :param x0: Initial value of state\n",
    "    :return: x_map, L, marginal_loglikelihood, joint_loglikelihood\n",
    "    \"\"\"\n",
    "    # Build diagonals of information matrix\n",
    "    assert(len(y) == len(sigma2obs) and len(y) == len(sigma2e))\n",
    "    D = 1. / sigma2obs + 1. / sigma2e + np.concatenate((1. / sigma2e[1:], [0.]))\n",
    "    B = -1. / sigma2e\n",
    "    B[0] = 0.\n",
    "    \n",
    "    # Find Cholesky factorization of Hessian\n",
    "    U = sp.linalg.cholesky_banded((B, D), lower=False)\n",
    "\n",
    "    # Solve linear system\n",
    "    G = y / sigma2obs\n",
    "    G[0] += x0 / sigma2e[0]\n",
    "    x_map = sp.linalg.cho_solve_banded([U, False], G)\n",
    "\n",
    "    # Compute joint and marginal probabilities\n",
    "    joint_loglikelihood = -.5 * ( np.sum(np.log(2*np.pi*sigma2e)) + np.sum(np.diff(x_map)**2 / sigma2e[1:])\n",
    "                                                                  + (x_map[0] - x0)**2 / sigma2e[0]\n",
    "                                + np.sum(np.log(2*np.pi*sigma2obs)) + np.sum((y - x_map)**2 / sigma2obs) )\n",
    "    marginal_loglikelihood = len(y)/2. * np.log(2*np.pi) + joint_loglikelihood - np.sum(np.log(U[-1]))\n",
    "    return x_map, U, marginal_loglikelihood, joint_loglikelihood"
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   "source": [
    "def Do_MM(DN, c, lam, sigma2x, sigma2x0, x0, sigma2z0, z0, max_iter=100, tol=1e-6):\n",
    "    \"\"\"Find MAP solution of 2d model using MM\n",
    "\n",
    "    :param dN: Observations (R,K,)\n",
    "    :param c: Radius of Huber approximation to L1 norm\n",
    "    :param lam: Coefficient of L1 penalization of changes along z\n",
    "    :param sigma2x: Variance of x process noise\n",
    "    :param sigma2x0: Variance of initial state x\n",
    "    :param x0: Initial value of state x\n",
    "    :param sigma2z0: Variance of initial state z\n",
    "    :param z0: Initial value of state z\n",
    "    :return: x_map, z_map, loglikelihood_map\n",
    "    \"\"\"\n",
    "    # Initialize\n",
    "    z = np.zeros((DN.shape[0],))\n",
    "    x = np.zeros((DN.shape[1],))\n",
    "    xz = x[None,:] + z[:,None]\n",
    "    joint_loglikel = np.zeros(max_iter)\n",
    "    # Iterate\n",
    "    for i in range(max_iter):\n",
    "        # Block MM over z\n",
    "        B = 1. / np.sum(1. / np.maximum(4., 2. + np.abs(xz)), axis=1)\n",
    "        A = np.sum(1. / (1. + np.exp(-xz)) - DN, axis=1)\n",
    "        sigma2z = np.concatenate(([sigma2z0], np.maximum(c, np.abs(np.diff(z))) / lam))\n",
    "        z = Do_Kalman_Likelihood(z - A*B, B, sigma2z, z0)[0]\n",
    "        xz = x[None,:] + z[:,None]\n",
    "        # Block MM over x\n",
    "        B = 1. / np.sum(1. / np.maximum(4., 2. + np.abs(xz)), axis=0)\n",
    "        A = np.sum(1. / (1. + np.exp(-xz)) - DN, axis=0)\n",
    "        sigma2x_ = np.concatenate(([sigma2x0], np.ones(len(x)-1) * sigma2x))\n",
    "        x = Do_Kalman_Likelihood(x - A*B, B, sigma2x_, x0)[0]\n",
    "        xz = x[None,:] + z[:,None]\n",
    "        # Compute likelihood\n",
    "        joint_loglikel[i] = ( np.sum(DN * xz - np.log(1. + np.exp(xz))) - .5 * (\n",
    "                           (len(x) - 1) * np.log(2*np.pi*sigma2x) + np.sum(np.diff(x)**2 / sigma2x)\n",
    "                           + np.log(2*np.pi*sigma2x0) + (x[0] - x0)**2 / sigma2x0 \n",
    "                           + np.log(2*np.pi*sigma2z0) + (z[0] - z0)**2 / sigma2z0 )\n",
    "                           + np.log(lam/2.) - lam * np.sum(np.abs(np.diff(z))) )\n",
    "        # Check convergence\n",
    "        if i > 0 and joint_loglikel[i] - joint_loglikel[i-1] < tol * np.abs(joint_loglikel[i]):\n",
    "            return x, z, joint_loglikel[:i+1]\n",
    "    return x, z, joint_loglikel"
   ]
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   "execution_count": 4,
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       "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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f70a1e5ae80>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "K = 200\n",
    "R = 45\n",
    "x = .1 + .2 * (np.arange(K) > 100)\n",
    "z = .1 + .2 * (np.arange(R) > 15)\n",
    "DN = (x[None,:] + z[:,None] > np.random.rand(R, K)).astype(float)\n",
    "plt.figure()\n",
    "plt.imshow(DN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
      "Wall time: 4.05 µs\n"
     ]
    },
    {
     "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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-5745.4095864\n"
     ]
    }
   ],
   "source": [
    "%time\n",
    "c = 1e-3\n",
    "sigma2x = .1\n",
    "sigma2x0 = 10\n",
    "x0 = 0\n",
    "sigma2z0 = 10\n",
    "z0 = 0\n",
    "lam = 10.\n",
    "x, z, joint_loglikel = Do_MM(DN, c, lam, sigma2x, sigma2x0, x0, sigma2z0, z0)\n",
    "plt.figure()\n",
    "plt.plot(joint_loglikel)\n",
    "print(joint_loglikel[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f70a1e357b8>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(x)\n",
    "plt.plot(z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}