duffing-stuffing/duffing-estimation.ipynb

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    "# Duffing-stuffing parameter estimation\n",
    "\n",
    "Goals:\n",
    "\n",
    "  * Estimate parameters for a Duffing-like model such that it describes the behavior of the system with low error in different experimental schemes (varying resonnance frequencies, degradation, etc.).\n",
    "  * Simulate the system and perform various analyses (sensitivity, stability, etc.)\n",
    "  \n",
    "\n",
    "## Table of contents\n",
    "\n",
    " 1. [Empirical data](#empiric-data)\n",
    " 2. [Frequency response](#frequency-response)\n",
    " 3. [Model](#model)\n",
    " 4. [Loss function](#loss-function)"
   ]
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    "%matplotlib notebook\n",
    "\n",
    "import os\n",
    "import numpy as np\n",
    "import random\n",
    "import itertools\n",
    "from scipy.stats import skew\n",
    "from scipy.interpolate import interp1d\n",
    "from tqdm import tqdm_notebook as tqdm\n",
    "from toolz import curry\n",
    "from scipy import signal\n",
    "from scipy.optimize import minimize\n",
    "from scipy.io import loadmat\n",
    "\n",
    "# PyDSTool requires scipy 0.X\n",
    "# However, solve_ivp was introduced in scipy 1.X.\n",
    "from scipy.integrate import odeint, solve_ivp\n",
    "#from pydstool_integrator import simulate as ds_simulate\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "#from matplotlib import animation\n",
    "#plt.rcParams[\"animation.html\"] = \"jshtml\""
   ]
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   "cell_type": "markdown",
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    "<a name=\"empiric-data\"></a>\n",
    "## Empirical data\n",
    "\n",
    "Data is measured through frequency scans at lab.\n",
    "\n",
    "Read data from `.mat`-files as a dict of numpy arrays. We focus primarily on the XY-trace data, containing a stable-state period of 100 observations per frequency, for 5 experiments total with variying resonnance frequencies."
   ]
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   "source": [
    "def read_xy(matfile, experiment_no):\n",
    "    \"\"\"Experiment number in [0, 5]\"\"\"\n",
    "    xy = loadmat(matfile)['XYPost'][0, experiment_no]\n",
    "    print(\"Variables (rows x observations): \", xy.dtype.names)\n",
    "    xy_data = dict([(k, xy[i]) for i, k in enumerate(xy.dtype.names)])\n",
    "    t_min, t_max = xy_data['t'][0,0], xy_data['t'][-1,0]\n",
    "    f_min, f_max = xy_data['f'][0,0], xy_data['f'][-1,0]\n",
    "    print(\"Resonnance frequencies: (%d, %d)\" % (xy_data['XResfFreq'][0,0], xy_data['YResfFreq'][0,0]))\n",
    "    print(\"Resonnance amplitudes: (%.2f, %.2f)\" % (xy_data['XResAmp'][0,0], xy_data['YResAmp'][0,0]))\n",
    "    print(\"T = %.2f\" % (t_max - t_min,))\n",
    "    print(\"t in [%.2f, %.2f]\" % (t_min, t_max))\n",
    "    print(\"f in [%.1f, %.1f]\" % (f_min, f_max))\n",
    "    print(\"x shape: %d x %d\" % xy_data['x'].shape)\n",
    "    print(\"y shape: %d x %d\" % xy_data['y'].shape)\n",
    "    return xy_data\n",
    "\n",
    "\n",
    "def read_amp(matfile):\n",
    "    ds_name = os.path.splitext(os.path.basename(matfile))[0]\n",
    "    print(\"Reading ds '%s'\" % ds_name)\n",
    "    amp = loadmat(matfile)[ds_name]\n",
    "    _, n_vars = amp.shape\n",
    "    amp_data = dict([(amp[0,i][1][0][0][0],  amp[0,i][0][:,0]) for i in range(n_vars)])\n",
    "    print(\"Variables: %s\" % ','.join(amp_data.keys()))\n",
    "    return amp_data"
   ]
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   "cell_type": "code",
   "execution_count": 3,
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     "name": "stdout",
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     "text": [
      "Reading first experiment\n",
      "Variables (rows x observations):  ('x', 'y', 's', 'f', 'v', 't', 'XResAmp', 'XResfFreq', 'YResAmp', 'YResfFreq')\n",
      "Resonnance frequencies: (7600, 8100)\n",
      "Resonnance amplitudes: (1.03, 1.10)\n",
      "T = 55.78\n",
      "t in [0.00, 55.78]\n",
      "f in [0.0, 10000.0]\n",
      "x shape: 101 x 100\n",
      "y shape: 101 x 100\n"
     ]
    }
   ],
   "source": [
    "# Read first experiment\n",
    "print(\"Reading first experiment\")\n",
    "xy_data = read_xy('data/XYPost.mat', 0)"
   ]
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    "#amp_pre = read_amp('data/APre.mat')\n",
    "#amp_post = read_amp('data/APost.mat')\n",
    "#amp_postb = read_amp('data/APostB.mat')"
   ]
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   "source": [
    "#### Plotting\n",
    "\n",
    "Three types of plots:\n",
    "\n",
    "  * Frequency scan with amplitude mean/std.\n",
    "  * Trajectory plot in (x, y)-plane.\n",
    "  * Trajectory over time for x and y."
   ]
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  {
   "cell_type": "code",
   "execution_count": 5,
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   "source": [
    "def plot_std_freqscan(xy_data):\n",
    "    linewidth = 0.6\n",
    "    fig, (ax11, ax12) = plt.subplots(\n",
    "        nrows=1,\n",
    "        ncols=2,\n",
    "        figsize=(8, 4)\n",
    "    )\n",
    "    rows = list(filter(\n",
    "        lambda r: xy_data['f'][r,0] != 0,\n",
    "        range(xy_data['f'].shape[0])\n",
    "    ))\n",
    "    ax11.errorbar(\n",
    "        xy_data['f'][rows,0],\n",
    "        np.mean(xy_data['x'][rows, :], axis=1),\n",
    "        np.std(xy_data['x'][rows, :], axis=1),\n",
    "        linewidth=linewidth\n",
    "    )\n",
    "    ax11.axvline(x=xy_data['XResfFreq'][0,0], linestyle='--', color='red', linewidth=0.8)\n",
    "    ax11.axvline(x=xy_data['YResfFreq'][0,0], linestyle='--', color='red', linewidth=0.8)\n",
    "    ax11.set_xlabel(r'$f$')\n",
    "    ax11.set_ylabel(r'$x$')\n",
    "    ax12.errorbar(\n",
    "        xy_data['f'][rows,0],\n",
    "        np.mean(xy_data['y'][rows, :], axis=1),\n",
    "        np.std(xy_data['y'][rows, :], axis=1),\n",
    "        linewidth=linewidth\n",
    "    )\n",
    "    ax12.axvline(x=xy_data['XResfFreq'][0,0], linestyle='--', color='red', linewidth=0.8)\n",
    "    ax12.axvline(x=xy_data['YResfFreq'][0,0], linestyle='--', color='red', linewidth=0.8)\n",
    "    ax12.set_xlabel(r'$f$')\n",
    "    ax12.set_ylabel(r'$y$')\n",
    "    plt.suptitle(\"Amplitude mean and standard deviation per frequency\\nRed lines are resonnance frequencies\")\n",
    "    #plt.tight_layout()\n",
    "    \n",
    "    \n",
    "def plot_xy(rows, xy_data):\n",
    "    linewidth = 0.6\n",
    "    fig, ((ax11, ax12), (ax21, ax22)) = plt.subplots(\n",
    "        nrows=2,\n",
    "        ncols=2,\n",
    "        figsize=(8, 6)\n",
    "    )\n",
    "    for row in rows:\n",
    "        ax11.plot(xy_data['x'][row, :], linewidth=linewidth)\n",
    "        ax12.plot(xy_data['y'][row, :], linewidth=linewidth)\n",
    "        ax21.plot(xy_data['x'][row, :], xy_data['y'][row, :], linewidth=linewidth)\n",
    "        ax22.plot(xy_data['f'][row, :])\n",
    "        \n",
    "    ax11.set_ylabel(r'$x$')\n",
    "    ax12.set_ylabel(r'$y$')\n",
    "    ax21.set_xlabel(r'$x$')\n",
    "    ax21.set_ylabel(r'$y$')\n",
    "    ax22.set_ylabel(r'$f$')\n",
    "    plt.suptitle(\"XY-data plots for given frequencies\")\n",
    "    #plt.tight_layout()\n",
    "    \n",
    "    \n",
    "def plot_xyt(rows, xy_data, normalizer=lambda x: x, sim_xy_data=None):\n",
    "    N = len(rows)\n",
    "    linewidth = 0.6\n",
    "    fig, axes = plt.subplots(\n",
    "        nrows=N,\n",
    "        ncols=2,\n",
    "        #sharey=True,\n",
    "        #sharex=True,\n",
    "        figsize=(8, 3*N)\n",
    "    )\n",
    "    for i in range(N):\n",
    "        axes[i,0].plot(normalizer(xy_data['x'][rows[i], :]), linewidth=linewidth)\n",
    "        axes[i,1].plot(normalizer(xy_data['y'][rows[i], :]), linewidth=linewidth)\n",
    "        if sim_xy_data is not None:\n",
    "            axes[i,0].plot(normalizer(sim_xy_data['x'][rows[i], :]), linewidth=linewidth)\n",
    "            axes[i,1].plot(normalizer(sim_xy_data['y'][rows[i], :]), linewidth=linewidth)\n",
    "        axes[i,0].set_ylabel('$x$ ($f$=%d)' % xy_data['f'][rows[i], 0])\n",
    "        axes[i,1].set_ylabel('$y$ ($f$=%d)' % xy_data['f'][rows[i], 0])\n",
    "    plt.suptitle(\"Stable-state XY-data plots for given frequencies\")\n",
    "    #plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
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     "text": [
      "Variables (rows x observations):  ('x', 'y', 's', 'f', 'v', 't', 'XResAmp', 'XResfFreq', 'YResAmp', 'YResfFreq')\n",
      "Resonnance frequencies: (7600, 8100)\n",
      "Resonnance amplitudes: (1.03, 1.10)\n",
      "T = 55.78\n",
      "t in [0.00, 55.78]\n",
      "f in [0.0, 10000.0]\n",
      "x shape: 101 x 100\n",
      "y shape: 101 x 100\n"
     ]
    },
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       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot freqency scans (mean +- variation)\n",
    "rows = [50, 65, 70, 75, 80, 85, 90, 100]\n",
    "for exp_no in range(5):\n",
    "    xy_data = read_xy('data/XYPost.mat', exp_no)\n",
    "    plot_std_freqscan(xy_data)\n",
    "    plot_xy(rows, xy_data)\n",
    "    plot_xyt(rows, xy_data)\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a name=\"frequency-response\"></a>\n",
    "## Frequency response\n",
    "\n",
    "Simulating the model takes requires considerable resources, thus we are dependent on finding a good set of first-guess parameters $\\mathbf{\\theta}$. We do this by minimizing the MSE of the freqency response.\n",
    "\n",
    "The frequency response is estimated by the implicit function\n",
    "\n",
    "\\begin{align}\n",
    "\\frac{\\gamma^2}{z^2} &= (\\omega^2 - \\alpha - \\frac{3}{4}\\beta z^2)^2 + (\\delta \\omega)^2 \\implies \\\\\n",
    "\\frac{z}{\\gamma} &= \\frac{1}{\\sqrt{(\\omega^2 - \\alpha - \\frac{3}{4}\\beta z^2)^2 + (\\delta \\omega)^2}} \\implies \\\\\n",
    "F &= G\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\" 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      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def right(gamma, alpha, beta, delta, z, omega):\n",
    "    denom = (omega**2 - alpha - (3/4)*beta*z**2)**2 + (delta*omega)**2\n",
    "    return gamma/np.sqrt(denom)\n",
    "\n",
    "gamma = 1\n",
    "alpha = 1\n",
    "beta_mul = 0.01\n",
    "delta = 0.1\n",
    "\n",
    "z, omega = np.meshgrid(\n",
    "    np.linspace(0, 15, 500),\n",
    "    np.linspace(0, 2, 500)\n",
    ")\n",
    "\n",
    "plt.figure()\n",
    "for beta in (-0.3, 0.0, 1, 4):\n",
    "    G = right(gamma, alpha, beta*beta_mul, delta, z, omega)\n",
    "    plt.contour(omega, z, (z-G), [0])\n",
    "    plt.xlabel(\"$\\omega$\")\n",
    "    plt.ylabel(\"$z$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def right(gamma, alpha, beta, delta, z, f):\n",
    "    omega = 2*np.pi*f\n",
    "    denom = (omega**2 - alpha - (3/4)*beta*z**2)**2 + (delta*omega)**2\n",
    "    return gamma/np.sqrt(denom)\n",
    "\n",
    "def get_pointmap(gamma, alpha, beta, delta, z, f):\n",
    "    fig = plt.figure()\n",
    "    G = right(gamma, alpha, beta, delta, z, f)\n",
    "    cs = plt.contour(f, z, (z-G), [0])\n",
    "    p = cs.collections[0].get_paths()[0]\n",
    "    v = p.vertices\n",
    "    plt.close(fig)\n",
    "    return v[:,0][::-1], v[:,1][::-1]\n",
    "\n",
    "def clip_pointmap(xs, ys):\n",
    "    # If softening spring, mirror the distribution across 0 and back\n",
    "    if skew(xs) > 0:\n",
    "        # Is order/direction different when softening?\n",
    "        raise NotImplementedError()\n",
    "        _xs, _ys = clip_pointmap(-1*xs, ys)\n",
    "        return -1*_xs, _ys\n",
    "    \n",
    "    # Find peak and continue s.t. x is monotonically increasing\n",
    "    indexes = []\n",
    "    N = len(xs)\n",
    "    max_x = xs[0] - 1e-9\n",
    "    for i in range(0, N):\n",
    "        if xs[i] > max_x:\n",
    "            indexes.append(i)\n",
    "            max_x = xs[i]\n",
    "    return xs[indexes], ys[indexes]\n",
    "\n",
    "def resample_pointmap(xs, ys, n):\n",
    "    lin = interp1d(xs, ys)\n",
    "    new_xs = np.linspace(xs[0], xs[-1], n)\n",
    "    return new_xs, lin(new_xs)\n",
    "\n",
    "def sample_frequency_response(n, gamma, alpha, beta, delta, z, f):\n",
    "    plt.ioff()\n",
    "    xs, ys = get_pointmap(gamma, alpha, beta, delta, zs, fs)\n",
    "    plt.ion()\n",
    "    xs, ys = clip_pointmap(xs, ys)\n",
    "    return resample_pointmap(xs, ys, n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, 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 * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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0JWWbG0LbT94dp3n91q67aCMdbpjSsYHPxmIMcxvAqAnNBCArvTwwm0y1unxd7Z7fq9l+YdkrNPPX0zvgsqA6ML8JgB6QgMB6Eo3j0uVsU4rth/y/F4pBRUy1mnApLQuqAyILsxvAqAnNBCArlJZ2yBjnS5NcKqub/b8fmt2VMpYpx+/sL4LqgOiC/ObAOgJDQSgq7Qv2rj1+a4JbO3XE+yK8wmBaMP8JgB6QgMB6CrDTp3/N2JJQZe8X/ruKhnr9L0Ja7vk/YBowvwmAHpCAwHoKjedOv9vZUFFl7xf5p4jMtbppnGpXfJ+QDRhfhMAPaGBAHSFypr3nP930vv5f5KUve+ojHX69tg1XfJ+QDRhfhMAPaGBAHSFxbkHunzBRk7JMRnrdMNTq7vsPYFowfwmAHpCAwHoCglvtZ3/92QXnf8nSdvKqmWs0/+MXtVl7wlEC+Y3AdATGghAV7jpmbbz/1YVds35f5K0vbwtAF47MqXL3hOIFsxvAqAnNBAArypOnf/3uS48/0+SdhyqlbFOV49Y2WXvCUQL5jcB0BMaCIBX7ef/3fbChi59392VdTLW6SuPr+jS9wWiAfObAOgJDQTAq4S3tspYp5Gu687/k6S9VSdkrNOVw5d36fsC0YD5TQD0hAYC4NV3Tp3/t7qo687/k6TSo/Uy1umLjy7r0vcFogHzmwDoCQ0EwItD1e+e/1fT0HXn/0lS+fGTMtap38PJXfq+QDRgfhMAPaGBAHixKKft/L+fTOza8/+k0xeXADgd85sA6AkNBMAL+2bb+X+jlhZ2+XtX1TXKWCdjncLhcJe/PxDJmN8EQE9oIABe9B+7RsY6rSmq7PL3Pl7f1BEAW1pDXf7+QCRjfhMAPaGBAFyo935F29Xn/0lSTUNzRwBsaG7t8vcHIhnzmwDoCQ0E4EK9k1cuY51ufb7r7v/7XvVNLR0BsL6ppVv2AUQq5jcB0BMaCMCFemxxvox1Snx7e7e8f2NLa0cA7I4jjEAkY34TAD2hgQBcqB8+t17GOi3ddrBb3r+lNdQRAI+daOqWfQCRivlNAPSEBgJwIapPNuvShLZwVlnb0C37CIfDHQGwqq6xW/YBRCrmNwHQExoIwIVYU1QpY536j13Trfu5bNhSGetUUdM9IROIVMxvAqAnNBCAC/HUsiIZ6/TP+Xndup9+DyfLWKcDx092636ASMP8JgB6QgMBuBC/eDFdxjrNyy7t1v188dFlMtap9Gh9t+4HiDTMbwKgJzQQgPPV0NzacWRub9WJbt3XVcOX98h+gEjD/CYAekIDAThfWXuPylina55M6fZbtH31iRUy1ml3ZW237geINMxvAqAnNBCA8zVpzW4Z6/TX1zd3+76uHrFSxjrtOEQABN6L+U0A9IQGAnC+7no1S8Y6TU/b2+37+sbIFBnrtL28utv3BUQS5jcB0BMaCMD5aA2FO87Lyz/Q/aHsm6NXyVinrWXHu31fQCRhfhMAPaGBAJyP7eXVMtbpyuHL1Rrq3vP/JOmGp1bLWKeckmPdvi8gkjC/CYCe0EAAzseMtL0y1mngq1k9sr/+Y9fIWKfsfUd7ZH9ApGB+EwA9oYEAnI/7Xt8iY50mrt7VI/u7eVyqjHXauOdIj+wPiBTMbwKgJzQQgM4Kh8O69tSijJ4KZN+bsFbGOqXvruqR/QGRgvlNAPSEBgLQWfuPnJCxTp9/eKkamlt7ZJ8/fG69jHVat/Nwj+wPiBTMbwKgJzQQgM6an10qY51+/mJ6j+3zthc2yFinNUWVPbZPIBIwvwmAntBAADrLvrlVxjqNTi7ssX0OmJQmY51SCip6bJ9AJGB+EwA9oYEAdNZ3x7edj7di+6Ee2+fPX0yXsU7L8ntun0AkYH4TAD2hgQB0RvXJZhnrZKxTVV1jj+33jpcyZKyT23qwx/YJRALmNwHQExoIQGek7qiUsU7fHrumR/f766kbZazT23nlPbpfIOiY3wRAT2ggAJ0xfuVOGev096TcHt3v71/JlLFOC3PKenS/QNAxvwmAntBAADqjPYjN3ri/R/c7aHqWjHWan13ao/sFgo75TQD0hAYC8EFaQ2FdOXy5jHXaXl7do/u+e8YmGeuUtKmkR/cLBB3zmwDoCQ0E4IMUHaqRsU5femyZWlpDPbrvwbOyZazT65k9e+QRCDrmNwHQExoIwAeZk1kiY51+PXVjj+/7r69vlrFOszL29fi+gSBjfhMAPaGBAHyQB+flyVinZ5bv6PF9D5mzRcY6TU/b2+P7BoKM+U0A9IQGAvBBbnomVcY6rS7q+btx/G1ujox1mrZ+T4/vGwgy5jcB0BMaCMC5HD3R1HEB6GMnmnp8/+1HH6esLe7xfQNBxvwmAHpCAwE4l1WFFTLW6aZxqb7sf+iCtgA4ac1uX/YPBBXzmwDoCQ0E4FzGLi+SsU7/mJ/ny/4T3tomY52eX7XLl/0DQcX8JgB6QgMBOJf2W7HNyfTnOnyPLsqXsU7jV+70Zf9AUDG/CYCe0EAAzqalNaQvPrpMxjrtOFTrSw2Jb2+XsU5jlxf5sn8gqJjfBEBPaCAAZ5N/oFrGOl01fLlCobAvNYxYUiBjncYkEwCB92J+EwA9oYEAnM3sjH0y1un3r2T6VsPopYUy1mmkK/CtBiCImN8EQE9oIABn034Nvgk+nn/31LK2RSiPv7PdtxqAIGJ+EwA9oYEAnM23nl4jY53W7jzsWw3jVuyQsU7DF+f7VgMQRMxvAqAnNBCAM6mqa+y4AHT1yWbf6ng2ZaeMdXp44TbfagCCiPlNAPSEBgJwJu0XgL5l/Fpf63hh1S4Z62Tf3OprHUDQML8JgJ7QQADOZPypr14fnOfPBaDbTU7dLWOd/unThaiBoGJ+R1kAnDRpkowx6tOnj+Lj45WVlXXO5x8/flz33XefPv3pT6t3797q16+fli5d2un90UAAzmTgq1ky1ml2xj5f65i6rljGOj2QlOtrHUDQML+jKAAmJSWpd+/emj59ugoKCjR48GD17dtXlZWVZ3x+U1OTrr32Wt16661KS0vTvn37tHbtWuXldf4vZRoIwL8Kh8P6yuMrZKzT1rLjvtYybf0eGev0v2/k+FoHEDTM7ygKgPHx8RoyZEjHz6FQSBdddJHGjBlzxudPmTJFl112mZqbL/wEbRoIwL/aV3VCxjr1ezhZTS0hX2uZkbZXxjrdN2eLr3UAQcP8jpIA2NTUpF69emnRokWnPX7XXXdpwIABZ3zNj370I/3ud7/T4MGD9alPfUpXXnmlRo0apdbW1rPup7GxUTU1NR1bWVlZzDcQgNMtzj0gY51un5TmdymavXG/jHW6d/Zmv0sBAoUAGCUBsLy8XHFxccrIyDjt8aFDhyo+Pv6Mr7niiivUp08f3X333dq8ebOSkpL0yU9+Uo8//vhZ95OYmKi4uLj3bbHcQABO9/g7bfffTXzb/4svz8kskbFOf5qZ7XcpQKAQAGM4APbr10+f/exnTzviN378eH36058+6344Agjgg/xscpqMdVqUc8DvUjRvU6mMdfrjjE1+lwIECgEwSgLghXwF/O1vf1u33HLLaY8lJycrLi5OTU1NndovDQTgvZpbQ+r3SLKMddpbdcLvcvTm5jIZ6zTw1XNfEQGINczvKAmAUtsikPvvv7/j51AopIsvvvisi0CGDRsmY4xCoXdP0n7uuef0mc98ptP7pIEAvFf+gWoZ6/TlxOUKh8N+l6NFOW3nI/522ka/SwEChfkdRQEwKSlJffr00cyZM1VYWKh77rlHffv2VUVFhSRp4MCBSkhI6Hh+aWmpPv7xj+v+++/Xzp075ZzTpz71KY0cObLT+6SBALzXa6cWXfz+lUy/S5EkvZNXLmOdfjU144OfDMQQ5ncUBUBJmjhxoi655BL17t1b8fHxysx895dw//79NWjQoNOen5GRoeuuu059+vTRZZdd9oGrgP8VDQTgvf45P0/GOo1bscPvUiRJydsOylinX05J97sUIFCY31EWAHsaDQTgvb43Ya2MdUopqPC7FEnSiu2HZKzTTyf7f0kaIEiY3wRAT2ggAO1qG5p1aYKTsU6VtQ1+lyNJWlVYIWOdBkzc4HcpQKAwvwmAntBAANqlF1fJWKfrx6z2u5QOqTsqZazTrc+v97sUIFCY3wRAT2ggAO1eTC2WsU5/fT04d93YsKstlP7g2XV+lwIECvObAOgJDQSg3b2zN8tYp5fWFvtdSof2o5LfHb/W71KAQGF+EwA9oYEAtPuf0atkrFPmniN+l9Iha+9RGet00zOpfpcCBArzmwDoCQ0EQJIqahpkrNPnEpxONLb4XU6HzfuPyVinbz29xu9SgEBhfhMAPaGBAEjvXm4laOfa5ZYeD9zCFCAImN8EQE9oIACSNHZ5kYx1emjBVr9LOU37remuG7XK71KAQGF+EwA9oYEASNLvX8mUsU6vZ+73u5TTFB6skbFO1zyZ4ncpQKAwvwmAntBAAMLhsL76xAoZ67StrNrvck6zs6JWxjp9fcRKv0sBAoX5TQD0hAYCUHq0XsY6ff7hpWps6fy9xHtC8eE6Gev05cTlfpcCBArzmwDoCQ0EIHnbQRnr9OMXgne3jf1HTshYp/9+bJnfpQCBwvwmAHpCAwF4alnbApCEt4K1AER69+jkFY8m+10KECjMbwKgJzQQgKAuAJGkg9UnO76eBvAu5jcB0BMaCIht710AsrXsuN/lvE9lbdsFqi9NcH6XAgQK85sA6AkNBMS2IC8AkaQjdY0y1slYp1Ao7Hc5QGAwvwmAntBAQGxrXwBy6/PBWwAiSdX1zR0BsLk15Hc5QGAwvwmAntBAQGx7+tQCEPtm8BaASFJdY0tHAGxoDt4RSsAvzG8CoCc0EBDbgrwARJJONrV2BMATjS1+lwMEBvObAOgJDQTErqAvAJGkppZQRwCsPtnsdzlAYDC/CYCe0EBA7Ar6AhBJCoXCHQHw6Ikmv8sBAoP5TQD0hAYCYlfQF4C0aw+Ah2sb/S4FCAzmNwHQExoIiF1BXwDS7vJhS2Ws06HqBr9LAQKD+U0A9IQGAmJX+wKQ1zYGcwFIuy88kixjncqO1ftdChAYzG8CoCc0EBCbwuGwvnZqAUheaTAXgLT70mPLZKxTyRECINCO+U0A9IQGAmJT+wKQy4ctDfz19a5KXC5jnfYcrvO7FCAwmN8EQE9oICA2tS8A+dFzwV4AIqnjSOWuilq/SwECg/lNAPSEBgJiU6QsAJGka55cKWOdig7xewpox/wmAHpCAwGxKVIWgEhS/KgUGeuUf6Da71KAwGB+EwA9oYGA2BNJC0Ak6foxqyOmVqCnML8JgJ7QQEDsKTsWOQtAJOnGp9sC4Ob9x/wuBQgM5jcB0BMaCIg9y/IPyVinH0bAAhBJ+s4zqTLWadO+o36XAgQG85sA6AkNBMSe8St2yFinf8zP87uUTrll/FoZ65RRfMTvUoDAYH4TAD2hgYDYc/eMTTLWaXraXr9L6ZTvT1gnY5027KryuxQgMJjfBEBPaCAg9lw3apWMdcraGxlfqf7oufUy1mntzsN+lwIEBvObAOgJDQTEliN1jTLWyVin2oZmv8vplJ9M3CBjnVYXVfhdChAYzG8CoCc0EBBb1u08LGOd+o9d43cpnXb7pDQZ67Ri+yG/SwECg/lNAPSEBgJiy4upxTLW6b7Xt/hdSqf94sV0Geu0LP+g36UAgcH8JgB6QgMBsWXInC0y1mnSmt1+l9Jpd76UIWOdlmwt97sUIDCY3wRAT2ggILbcdOqaeqk7Kv0updN+8/JGGeu0OPeA36UAgcH8JgB6QgMBseNEY4suTWhbAHK4ttHvcjqt/b7Fb20p87sUIDCY3wRAT2ggIHZk7zsqY52+MTLF71LOyx+mZ8lYp3nZpX6XAgQG85sA6AkNBMSOWRn7ZKzTH6Zn+V3KefnTzGwZ6/RGVonfpQCBwfwmAHpCAwGx46EFW2Ws0zPLd/hdynm5Z3ZbAHxt436/SwECg/lNAPSEBgJix/MKhW8AACAASURBVI9faLujRvK2yLqcyn2vt61cnpm+z+9SgMBgfhMAPaGBgNjQ3BpSv4eTZaxTyZF6v8s5L//7Ro6MdXplQ2TcuxjoCcxvAqAnNBAQGwrKa2Ss01WJyxUOh/0u57z8PSlXxjq9vG6P36UAgcH8JgB6QgMBsWF+dqmMdbrzpQy/Szlv/5ifJ2OdXkwt9rsUIDCY3wRAT2ggIDYkvr1dxjo98U6B36WcN/tm2+KViat3+V0KEBjMbwKgJzQQEBvumNJ2O7U3N0fexZSHLdwmY52eSyEAAu2Y3wRAT2ggIPqFQmFdOXy5jHUqOhR5/19/bHG+jHUavyKyLl8DdCfmNwHQExoIiH77qk7IWKd+jySruTXkdznn7fF32r6+fnpZkd+lAIHB/CYAekIDAdHPbT0oY51+MnGD36VckCeXFMhYp9HJhX6XAgQG85sA6AkNBES/p5cVyVinhLe2+l3KBRmdXChjnZ5cEnkLWIDuwvwmAHpCAwHR765Xs2Ss0+wIvZXa2OVtATbx7e1+lwIEBvObAOgJDQREv2tHpshYp837j/ldygUZv2KHjHV6bHG+36UAgcH8JgB6QgMB0a2ytkHGOl2a4FTf1OJ3ORfkuZRdMtZp2MJtfpcCBAbzmwDoCQ0ERLfUHZUy1ummcal+l3LBJq3ZLWOdHloQmecwAt2B+U0A9IQGAqLb5NS28HT/Gzl+l3LBXkwtlrFO/5if53cpQGAwvwmAntBAQHQbMmdLxN9H9+V1e2Ss09+Tcv0uBQgM5neUBcBJkybJGKM+ffooPj5eWVlZnXrd3LlzFRcXp9tvv/289kcDAdHtpmdSZazT2p2H/S7lgr26YW/EH8UEuhrzO4oCYFJSknr37q3p06eroKBAgwcPVt++fVVZWXnO1+3bt08XX3yxvvWtbxEAAXQ40diiSxOcjHU6XNvodzkXbGb6PhnrdN/rW/wuBQgM5ncUBcD4+HgNGTKk4+dQKKSLLrpIY8aMOetrWltbdf311+uVV17RoEGDCIAAOmzef0zGOn1jZIrfpXjy2sb9MtbpntnZfpcCBAbzO0oCYFNTk3r16qVFixad9vhdd92lAQMGnPV1w4cP109/+lNJIgACOM3sjLYjZ3+Y3rlTSYJqblaJjHX608xNfpcCBAbzO0oCYHl5ueLi4pSRkXHa40OHDlV8fPwZX7NhwwZdfPHFqqqqktS5ANjY2KiampqOraysLOYbCIhWCW9tlbFOY5cX+V2KJ/OyS6MiyAJdiQAYowGwtrZWl156qZKTkzse60wATExMVFxc3Pu2WG4gIFr9ZOIGGevkth70uxRP3tpSJmOdfv9Kpt+lAIFBAIySAHi+XwHn5uYqLi5OvXr16tg+9KEP6UMf+pB69eql4uIzX/KBI4BAbGhpDanfI8ky1mlf1Qm/y/Fkce4BGev0m5c3+l0KEBgEwCgJgFLbIpD777+/4+dQKKSLL774jItAGhoalJ+ff9p2++236+abb1Z+fr6ampo6tU8aCIhOOytqZazTfz+2TKFQ2O9yPFmytVzGOt35UsYHPxmIEczvKAqASUlJ6tOnj2bOnKnCwkLdc8896tu3ryoqKiRJAwcOVEJCwllfzyIQAO0W5rR9bfqLF9P9LsWzZfkHo+azAF2F+R1FAVCSJk6cqEsuuUS9e/dWfHy8MjPfPeelf//+GjRo0FlfSwAE0G6kK5CxTsMX5/tdimcrCypkrNPtk9L8LgUIDOZ3lAXAnkYDAdHpt9M2ylinpE0lfpfi2eqitgD4k4kb/C4FCAzmNwHQExoIiD7hcFhffWKFjHXaVlbtdzmerd15WMY6/ei59X6XAgQG85sA6AkNBESf8uMnZazT5cOWqqG51e9yPEvbXSVjnb4/YZ3fpQCBwfwmAHpCAwHRJ+XUOXM/eDY6AlNG8REZ63TL+LV+lwIEBvObAOgJDQREn+dSdslYpweScv0upUts2ndUxjp955lUv0sBAoP5TQD0hAYCos89s7NlrNO09Xv8LqVLbCk5JmOdbnx6td+lAIHB/CYAekIDAdHnxqdXy1in9OIqv0vpEnmlx2Ws0/VjCIBAO+Y3AdATGgiILtUnm2Wsk7FOx+s7d0egoMs/UC1jneJHpfhdChAYzG8CoCc0EBBdNu45EnVHy4oO1chYp2ueXOl3KUBgML8JgJ7QQEB0mbZ+j4x1+vOsbL9L6TK7Tt3X+KtPrPC7FCAwmN8EQE9oICC6/G1ujox1en7VLr9L6TJ7DtfJWKerEpf7XQoQGMxvAqAnNBAQXW4elypjndYUVfpdSpcpOVIvY52+9Ngyv0sBAoP5TQD0hAYCokddY4suTWhbAHK4ttHvcrpM2bG2ANjvkWS/SwECg/lNAPSEBgKiR/sFk68btcrvUrrUoeqGjlvbAWjD/CYAekIDAdHj1Q17ZazTn2Zu8ruULnW4trHj0jbhcNjvcoBAYH4TAD2hgYDo8UBSrox1ejZlp9+ldKljJ5o6AmBriAAISMxviQDoCQ0ERI/vjl8rY51WFVb4XUqXeu/FrZtaQn6XAwQC85sA6AkNBESH+qYWfe7UApDKmga/y+lSJxpbOgLgyaZWv8sBAoH5TQD0hAYCosPm/W0LQK4dGX23S2tobu0IgLUNzX6XAwQC85sA6AkNBESHGWltC0D+OCO6FoBIUnNrqCMAVtcTAAGJ+S0RAD2hgYDo8OC8PBnrNH5ldC0AkaRQKNwRAI/URc/1DQEvmN8EQE9oICA6/ODZdTLWaWVBdC0AaRet5zcCF4r5TQD0hAYCIl9Dc6suG7ZUxjodrD7pdznd4vMPR/fnA84X85sA6AkNBES+LSXHZKzTNU+ujNoLJV/xaLKMdSo9Wu93KUAgML8JgJ7QQEDkm5WxT8Y6DZqe5Xcp3ebK4ctlrNO+qhN+lwIEAvObAOgJDQREvqEL2haAjFuxw+9Sus2XE9sCYPHhOr9LAQKB+U0A9IQGAiLfD59bL2OdluUf8ruUbvP1EStlrNPOilq/SwECgflNAPSEBgIiW0Nzqy4/tQDkwPHoXSBx7cgUGetUUM7vKkBifksEQE9oICCy5ZYel7FOXx8RvQtAJOm6UatkrFP+gWq/SwECgflNAPSEBgIi22sb98tYp4GvRu8CEEm6fsxqGeuUW3rc71KAQGB+EwA9oYGAyGbf3CpjnZ5eVuR3Kd3q22PXyFinzfuP+l0KEAjMbwKgJzQQENlufb5tAUjytoN+l9KtbnomVcY6Ze0lAAIS81siAHpCAwGRq76ppeMOING8AESSvjt+rYx1Si+u8rsUIBCY3wRAT2ggIHJlFB+RsU7/M3qV36V0u/Z7Ha/fddjvUoBAYH4TAD2hgYDINXH1LhnrdN+cLX6X0u3av+pO3VHpdylAIDC/CYCe0EBA5PrD9CwZ6/Tqhr1+l9LtBkzcIGOdVhVW+F0KEAjMbwKgJzQQEJlCobC+8vgKGeu0tSz6L43ys8lpMtZp+fbovdsJcD6Y3wRAT2ggIDLtrqyVsU5XPJqs5taQ3+V0u19OSY+J1c5AZzG/CYCe0EBAZJqbVSJjne58KcPvUnrEr6ZmyFind/LK/S4FCATmNwHQExoIiEz/nJ8nY53GLo/uC0C3+920TBnrtCjngN+lAIHA/CYAekIDAZHppnFtF0ZeXRQbiyIGvtq24OXNzWV+lwIEAvObAOgJDQREnqMnmmSsk7FOx040+V1Oj/jjjE0y1mneplK/SwECgflNAPSEBgIiz6rCChnrdPO4VL9L6TF/npUtY53mZJb4XQoQCMxvAqAnNBAQeZ5aViRjnR5asNXvUnrMvbM3y1in2Rv3+10KEAjMbwKgJzQQEHnueCkj5r4OvW/OFhnrNCMt+i96DXQG85sA6AkNBESW5taQvvBIsox12l1Z53c5Peb/5ubIWKdp6/f4XQoQCMxvAqAnNBAQWfJKj8tYp68+sULhcNjvcnrMA0m5MtZp6rpiv0sBAoH5TQD0hAYCIssrG/bKWKe7Z2zyu5Qe1X7dw8mpu/0uBQgE5jcB0BMaCIgs973edi7cpDWxFYQS3toqY51eWLXL71KAQGB+EwA9oYGAyBEOhxU/KkXGOmXuOeJ3OT3q4YXbZKzTsyk7/S4FCATmNwHQExoIiBwHjp+UsU6XD1uqk02tfpfTo4YvzpexTuNW7PC7FCAQmN8EQE9oICByLM49IGOdBkzc4HcpPe6JdwpkrNNTy2Lj3sfAB2F+EwA9oYGAyPGPUwshRroCv0vpcSNdWwAcvbTQ71KAQGB+EwA9oYGAyBAKhXXtyLbz/9J2V/ldTo8bk9x295MRS2Iv/AJnwvwmAHpCAwGRIf9AtYx1+tJjy9TYElvn/0nSM8t3yFinxLe3+10KEAjMbwKgJzQQEBkmrdktY53+NDPb71J8MX7lThnr9OiifL9LAQKB+U0A9IQGAiLDL6eky1in1zP3+12KL55ftUvGOiW8tc3vUoBAYH4TAD2hgYDgq65v1ucSnIx1OnD8pN/l+KL9COjQBXl+lwIEAvObAOgJDQQE35Kt5TLW6bvj1/pdim9eWlssY50enEcABCTmt0QA9IQGAoIvli//0m7a+j0y1ulvc3P8LgUIBOY3AdATGggItli//Eu76Wl7ZazTkDlb/C4FCATmNwHQExoICLZYv/xLu9kZ+2Ss019e2+x3KUAgML+jLABOmjRJxhj16dNH8fHxysrKOutzX375Zd14443q27ev+vbtq1tuueWczz8TGggItli//Eu71zP3y1inwbNi+78D0I75HUUBMCkpSb1799b06dNVUFCgwYMHq2/fvqqsrDzj83/7299q8uTJys3NVVFRkf7whz/oE5/4hA4cONDpfdJAQLDF+uVf2iVtKpGxTnfP2OR3KUAgML+jKADGx8dryJAhHT+HQiFddNFFGjNmTKde39raqo9//OOaNWtWp/dJAwHBxeVf3rVgc5mMdbrr1fP7lgOIVszvKAmATU1N6tWrlxYtWnTa43fddZcGDBjQqfeora3VRz/6US1ZsuSsz2lsbFRNTU3HVlZWFvMNBAQVl39518KctgD4+1cy/S4FCAQCYJQEwPLycsXFxSkjI+O0x4cOHar4+PhOvcdf//pXXXbZZWpoaDjrcxITExUXF/e+LZYbCAgqLv/yrrfz2sLwr6du9LsUIBAIgARASdKYMWP0n//5n9q6des5n8cRQCAytHL5l9Ms3XZQxjrdMSXjg58MxAACYJQEQC9fAT/zzDP6xCc+oezs818dRwMBwbR252EZ6/TVJ1aoqSXkdzm+W5Z/SMY6/fzFdL9LAQKB+R0lAVBqWwRy//33d/wcCoV08cUXn3MRyNNPP63/+I//0MaNF/a1CA0EBNOQOVtkrNPwxfl+lxIIKQUVMtZpwKQ0v0sBAoH5HUUBMCkpSX369NHMmTNVWFioe+65R3379lVFRYUkaeDAgUpISOh4/lNPPaXevXvrzTff1KFDhzq2urq6Tu+TBgKCp7q+Wf0eSZaxTvkHqv0uJxDW7KiUsU4/fmG936UAgcD8jqIAKEkTJ07UJZdcot69eys+Pl6Zme+ueOvfv78GDRrU8bMx5owLOhITEzu9PxoICJ72u1784Nl1CofDfpcTCOtOfSX+w+cIgIDE/JaiLAD2NBoICJ6fTNwgY51e2bDX71ICI313lYx1+t4ELokDSMxviQDoCQ0EBMuOQ7Uy1unyYUt1pK7R73ICI3PPERnrdNO4VL9LAQKB+U0A9IQGAoLlySUFMtbpntnc8/a9svcdlbFO/ceu8bsUIBCY3wRAT2ggIDiaW0O65smVMtYppaDC73ICJafkmIx1uuGp1X6XAgQC85sA6AkNBATHylOXOrnmyRS1tHLtv/faVlYtY53+Z/Qqv0sBAoH5TQD0hAYCgmPwrGwZ6zRqaaHfpQTO9vK2APiNkSl+lwIEAvObAOgJDQQEQ1Vdoy4ftlTGOu2qqPW7nMBpXxxz9YiVfpcCBALzmwDoCQ0EBMNLa4u508U57K6sk7FOX3l8hd+lAIHA/CYAekIDAf6rb2rpWPwxb1Op3+UE0t6qEzLW6arhy/0uBQgE5jcB0BMaCPDf1HVtR/9ufHq1mln8cUalR+tlrNMXH13mdylAIDC/CYCe0ECAv040tujrI9qO/s3P5ujf2ZQfPyljnfo9nOx3KUAgML8JgJ7QQIC/Jq3ZLWOdvvNMKpd+OYeKmgYZ63TZsKV+lwIEAvObAOgJDQT4p7ahWV95fIWMdVqUc8DvcgKtqq5RxjoZ6xQOh/0uB/Ad85sA6AkNBPjn+VW7ZKzTzeNS1Roi1JzL8fqmjgDIkVKA+S0RAD2hgQB/VJ9s1lWJy2Ws0zt55X6XE3g1Dc0dAbCxpdXvcgDfMb8JgJ7QQIA/xq/cKWOdvjdhrUIc/ftA9U0tHQGwvqnF73IA3zG/CYCe0EBAz6uoadCVw9uO/iVvO+h3ORGhsaW1IwDWNDT7XQ7gO+Y3AdATGgjoWeFwWIOmZ7Xd9WPiBo7+dVJLa6gjAB6vb/K7HMB3zG8CoCc0ENCz5m0qbbue3SPJ3PP3PITD4Y4AWFXX6Hc5gO+Y3wRAT2ggoOccOH6y46vfl9YW+11OxLls2FIZ61RR0+B3KYDvmN8EQE9oIKBnhMNh/W5apox1+tnkNC77cgH6PZwsY53Kj5/0uxTAd8xvAqAnNBDQM2Zv3C9jna54NFl7Dtf5XU5E+uKjy2SsU+nRer9LAXzH/CYAekIDAd2v5Ei9vvRYW3h5dcNev8uJWFed+vp8b9UJv0sBfMf8JgB6QgMB3auusUW3Pr9exjrd8VIGq349aL9t3u5KjqACzG8CoCc0ENB9WlpDuuvVtku+XD1iJV9denT1iJUy1mnHIVZPA8xvAqAnNBDQPcLhsOybWzvO+8stPe53SRHvGyNTZKzT9vJqv0sBfMf8JgB6QgMB3WPi6l0y1ulzCU4rCyr8LicqfHP0KhnrtK2MAAgwvwmAntBAQNdbmFPWcdHiWRn7/C4natzw1GoZ65RTcszvUgDfMb8JgJ7QQEDXejuvXJ9/uO2CxaOXFvpdTlTpP3aNjHXK3nfU71IA3zG/CYCe0EBA15m2fk/Hkb+/zc1hxW8Xu3lcqox1ytxzxO9SAN8xvwmAntBAgHehUFijlhZ2hL/Et7cT/rrB9yaslbFO6bur/C4F8B3zmwDoCQ0EeNPUEtLfk3I7wt+UtcUKhwl/3eGHz7VdT3HdzsN+lwL4jvlNAPSEBgIuXPnxk7pjSoaMdbps2FK9ubnM75Ki2m0vbJCxTmt2VPpdCuA75jcB0BMaCLgwy/IPdtyZ4r8fW0Yo6QEDJqXJWKcULqsDML9FAPSEBgLOz8mmVg1buK3jK98BEzdoH/em7RE/fzFdxjotyz/kdymA75jfBEBPaCCg87L2HtUt49sWIlya4DQmuUhNLSG/y4oZd7zU9nX70m0H/S4F8B3zmwDoCQ0EfLCKmgb9bW5Ox1G/b4xMURorUXvcr6dulLFOb+eV+10K4DvmNwHQExoIOLumlpCmrivWfz+2rOOoX8Jb23T0RJPfpcWk37+SKWOdFuaw2AZgfhMAPaGBgPdrbg0paVOJvvX0mo6jfj+dnMY9aH02aHqWjHWan13qdymA75jfBEBPaCDgXU0tIc3JLOm456yxTtc8uVLzs0u5sHMA3D1jk4x1StpU4ncpgO+Y3wRAT2ggQDp6oklT1hbrm6NXvSf4pWja+j2qb2rxuzycMnhWtox1em3jfr9LAXzH/CYAekIDIZbllh7XA/Ny1e+R5NMWeLy6Ya8amlv9Lg//YsicLTLW6SuPr9DopYUqO1bvd0mAb5jfBEBPaCDEmoqaBr28bo9+dOq2Yu3bbS9s0LzsUoJfgGXtPapvj333vMzPJTjdO3uz0nZX8RU9Yg7zmwDoCQ2EWFBd36z52aX63bRMXZrwbujr93CyHkjKVU7JMe7fGyFaQ2GtKqzQ76Zlnhbgvzl6lZ5eVqTdlbV+lwj0COY3AdATGgjRqvRovV7dsFe/nrpRlw1belpY+MWL6Zq9cb+OcTmXiLarolaPLNqmLycuP+1/359M3KApa4u1lzu0IIoxvwmAntBAiBYnm1qVuqNSTy4p0PcnrDstEBjr9P0J6zRx9S6VHuW8sWjT0NyqpdsO6k8zN+nyfwn735uwVs8s36G80uN8TYyowvwmAHpCAyFSnWxqVfruKj2Xsku/nrpR/R5OPm3wfy7B6c6XMjRt/R6VHCH0xYojdY2avXG/fv9K5vvC4NeeWKEhc7Zo3qZSHaw+6XepgCfMbwKgJzQQIkE4HFbp0Xot2VquJ5cU6PZJae8b7sY6XT9mtR5asFXv5JXz9S5UXd+shTllunf2Zl05fPn7+qX/2DUauiBPCzaXqfRoPeeBIqIwvwmAntBACJr2sLcs/5DGr9ypP87YpKtHrHzf8DbW6bpRq3T/GzmanbFPew7XMcBxVs2tIW3ad1TjV+zQ7ZPS9LmE9/dT/KgU3TM7Wy+mFiu9uEp1jVwDEsHF/CYAekIDwU9H6hqVUXxEszL26ZFF23THlAxddYYjNcY6ff7hpbrthQ16ZNE2vbWFIzbwpvpks1YXVWhMcpF+NvnMR5QvTXC6eVyq7n8jR1PWFmvdzsOqqmv0u3RAEvNbIgB6QgOhuzU0t2pnRa1WbD+kKWuLNXRBnn7xYrq+9sSKMwa99suz/PiF9Rq6IE8z0vYqp+QY1+dDtzrZ1KqsvUc1dV2x/vr6Zl0/ZvVZ+/PqESv166kblfj2dr2euV9Ze4+qqq6RP0jQo5jfBEBPaCB41dIaUvnxk8rae1Rvbi7Tcym79I/5ebrjpQxdN2rVWYdo+3bj06t194xNempZkRbmlKnwYI2aWkJ+fyxAlbUNSt1RqUlrduu+OVv0nWdST7uO5L9uX3l8hX46OU0PzsvTC6t26e28cm0tO67q+ma/PwqiEPObAOgJDYRzaT4V7raUHNPSbQf16oa9Gr20UPe/kaNfvJiub45e9b5r7J1puypxuW57YYP+940cPZuyU2/nlSv/QDX32UXEqW9q0day45qfXapRSwt116tZuuGp1ecMhsY6fTlxuW59fr3unb1ZTy4p0Mz0fVpZUKHt5dU6dqKJo4c4b8xvAqAnNFDsaWkNqbK2QUWHarRhV5UW5RzQtPV7NDq5UA/Oy9PvX8nUD55dp6+fZeHF2c7P+/bYNfrttI2yb27VxNW7tDj3gHJLjzPcEBMamltVeLBGS7aW64VVbUfBfzklXdeOTOnU/4e++Ogy3TQuVb95eaMeSMrV08uKNCtjn5blH9Tm/cdUerRejS2cBoF3Mb8JgJ7QQJGtsaVVlbUN2lVRq037jmrF9kOat6lUU9cV66llRbJvbtXgWdn65ZR03TQuVV89x3l35wp3149ZrZ+/mK77Xt+iJ94p0Mvr9shtPaickmOqrGngArvAOZxobNGOQ7VaVVihGWl79eSSAt07e7N+MnGDrnmy839otX/NfPO4VP1qaoaGzNmixLe3a9Ka3Xojq0Qrth/S5v1HtbfqhKpPNvOHV5RjfhMAPaGB/BMKhVXX2KJD1Q3aXVmrnJJjWrfzsNzWg5qbVaKp64o1bsUOJb69XQ8k5eruGZv0yynp+v6Edbpu1Cpd8WjyeYe5914k+eoRK/Xd8Wv166kb9b9v5OiJdwo0OXW35meXau3Owyo8WKOjJ5oId0A3a2hu1d6qE0ovrtLCnDK9mFqs4Yvzdc/sbP10cpquH7P6fRc678x2+bCluubJFH1vwlrd8VKGBs/K1kMLtmp0cqFeTC3WG1klSt52UOm7q7S9vFplx+pV09DM/+cjBPObAOgJDdQ54XBY9U0tqqprVOnReu041BbY0nZXaWVBhRbnHtAbWSWatn6Pnl+1S6OTC/XIom36e1KuBs/K1m+nbdSASWm6ZfxaXTdqla4avvwDzxnq7HZpQttRgf5j1+j2SWkaND1Lf0/KVeLb2/XCql16beN+JW87qIziI9pVUasjdY1q5Rc8EFHC4bCO1zdpZ0Wt0ndXaXHuAb2yYa/GJBdp6II83T1jk26flKYbn16tLz22zNPvlM+d+p1y49Or9aPn1uvOlzL051nZemBe2++VcSt26KW1xZqTWaK388q1pqhSWXuPqqC8RiVH6nWkrlENza0cgexmzG8CoCeR2kDhcFjNrSHVNjSrqq5RB46f1J7DdSoor9GWkmPKKD6iNTsqtSz/oBbnHlDSphLNTN+nl9YW67mUXRqTXKTEt7fLvrlVf5ubo3tmZ2vgq1m646UM/WTiBt0yfq2uH7NaV49YqS8+6u2X6Qdtlw1bqq8+sUI3PLVaP3xuve6YkqE/zdykvyfl6rHF+Rq7vEhT1xVr7qm/1tN2V2lbWbVKj9ar+iR/rQN4v4bmVh2qblBBedu5vku2lmv2xv2auHqXRiwp0APzcvWnmZv0ixfT9d3xa3XtyBT1e+TCv1U42xHIrzy+QtePWa3vTVir2yel6bfTNurPs7L1t7k5Snhrm0YsKdD4FTv0YmqxZqbv07zsUi3ZWq7VRRXKKD6ivNLj2llRq9Kj9aqqa9SJxhb+gD0lUud3VyIAetBdDVR0qEaLcw9oXnapXs/cr+lpezV1XbEmrt6l8St2aExykZ54p0CPLNqmoQvy9Le5OfrLa5t194xN+v0rmbrjpQwNmJSmHz63XjePS9UNT63WN0am6CuPr9AVjyaf8Sr+PbVd8Wiyvj5ipW54qu2X2oBJafr11I3608xs/d+pX2pPLinQ+JU7NXVdsV7buF+Lcg5oZUGF0ovbwtuew3WqrG1QfVMLfyUDCIyG5rbzindX1mrz/mNK3VGpt/PK9Xrmfk1ZW6xnlu/Q8MX5emBerv48K1u/mpqh217YoO88k6prR6Z0+x/M7Vu/h5P15cTl+sbIFH17SH51aQAAEqpJREFU7Bp9f8I6DZiUpjtfytBdr2bpntltv4+HLsjTY4vzNWppocat2KFJa3Zr2vo9mr1xv+Zll2px7gEt335IqTsqlV5cpc37jyn/QLV2VdSq5Ei9DlU36NiJJp1obFFLa7AuT0UAJAB60l0NNH7lzh4NZf0eTtZVict17cgU3fDUat0yfq1ufX69fv5iun47baPunrFJ972+RQ8k5WrYwra/OscuL9ILq3Zp2vo9em3jfr25uUxu60GtKmwLarmlx7XjUNsvgcO1bX95crQNAM6tNRRWTUOzDlaf1O7KWuWWHlf6e06XmZNZopfX7dFzKW2nyzy2OF8PzsvTX1/frEHT276Jue2FDbp5XKquH7NaXx+x0tM5z125fS6h7SDAlxOX65onU3T9mNX6zjOp+v6EdfrxC+v1s8lp+tXUDA18NUt/mrlJf319s/5vbo6W5R/s8v/OBEACoCfd1UBvbSnT76Zl6g/TszR4VraGzGkLXw8t2KpHF+VrxJICPbWsSBNW7uz4i2xWxj7NzSrRW1vagtjKggqt23lYG/ccUU7JMW0vr9buyjqVHq1XZU2Dqk82q6G5lVAGADEgFArrZFOrjp1oUvnxkyo+XKf8A9XavP+o0nZXKaWgQu/klWvB5jK9tnG/pq3fo0lrdmvcih0atbQtaD60YKv+79RpP3+YnqXfvLxRP38xXbc+v17fHb9W33p6jeJHpehrT6zQlx5bdsZbBF7I9lzKri7/70EAjLIAOGnSJBlj1KdPH8XHxysrK+ucz58/f76uuOIK9enTR1dddZWWLl16XvujgQAAOLvWU8HzeH2TKmsaVHq0XsWH61R4sEZ5pce1aV9bAF1TVKll+Yf0Tl653txcprlZJZqVsU/T1u/R5v3Hurwu5ncUBcCkpCT17t1b06dPV0FBgQYPHqy+ffuqsrLyjM9PT09Xr169NHbsWBUWFurRRx/VRz7yEeXn53d6nzQQAACRh/kdRQEwPj5eQ4YM6fg5FArpoosu0pgxY874/DvvvFM//vGPT3vsuuuu07333tvpfdJAAABEHuZ3lATApqYm9erVS4sWLTrt8bvuuksDBgw442s++9nP6tlnnz3tseHDh+srX/lKp/dLAwEAEHmY31ESAMvLyxUXF6eMjIzTHh86dKji4+PP+JqPfOQjeuONN057bPLkyfrUpz511v00NjaqpqamYysrK4v5BgIAINIQAAmApz32QQEwMTFRcXFx79tiuYEAAIg0BMAoCYA99RUwRwABAIh8BMAoCYBS2yKQ+++/v+PnUCikiy+++JyLQG677bbTHvvmN7/JIhAAAKIc8zuKAmBSUpL69OmjmTNnqrCwUPfcc4/69u2riooKSdLAgQOVkJDQ8fz09HR9+MMf1rhx41RUVKTExEQuAwMAQAxgfkdRAJSkiRMn6pJLLlHv3r0VHx+vzMzMjn/r37+/Bg0adNrz58+fry984Qvq3bu3rrzySi4EDQBADGB+R1kA7Gk0EAAAkYf5TQD0hAYCACDyML8JgJ7QQAAARB7mNwHQExoIAIDIw/wmAHpCAwEAEHmY3wRAT6qrqxUXF6eysrLTLhDNxsbGxsbGFtyt/UYO1dXVfkcJ3xAAPWhvIDY2NjY2NrbI28rKyvyOEr4hAHoQCoVUVlam6urqbvvrJFqPLvL5In+L9s/I54v8Ldo/I5/vwrfq6mqVlZUpFAr5HSV8QwAMqJqa6D4/gc8X+aL9M/L5Il+0f0Y+H7wgAAZUtDc+ny/yRftn5PNFvmj/jHw+eEEADKhob3w+X+SL9s/I54t80f4Z+XzwggAYUI2NjUpMTFRjY6PfpXQLPl/ki/bPyOeLfNH+Gfl88IIACAAAEGMIgAAAADGGAAgAABBjCIAAAAAxhgAIAAAQYwiA3cQYc8bbztx3332SpIaGBt1333365Cc/qX//93/Xz3/+c1VUVJz2HiUlJbr11lv1sY99TP/f/9/evQdFVfZxAH+WOxuxXHaD4lYoGGFxaRDpws6EEd0kbaJBhnZyhqLJYiqFzMiJgtAuTlOBjIM2hkNqo+IQYIpMhVFGCkhIcbOLURYGiDgi8H3/cPa8HHZhfWde4Sz7/cz4B+d5eOTrjyO/PXvOg06H1atX49KlS7I5dXV1iIqKgpOTE+bNm4dt27bNVMRpM/b19WHVqlUIDQ2Fi4sLAgIC8Nxzz5n83kVzn19eXq6IjJZqqNfrTcaefvpp2RpKruF0+Xp6eqb81Um7du2S1lBy/UZHR/Hqq6/ixhtvhIuLC4KDg5GXl4fx8XFpzvj4OHJzc+Hr6wsXFxckJCTg559/lq3T19eHFStW4Nprr4VGo8HKlStx7tw52Zzm5mbcddddcHZ2hr+/PzZs2KCIjCMjI8jOzsbChQuhVqtx/fXXIz09HadPn5atY+574a233pr1jFdSQ4PBYPK133fffbJ1rLmGgPnzTAiBjRs3SnOUWkMAGBwcRFZWFgIDA+Hi4oK4uDgcPXpUGrf289BasQG8Ss6cOYPe3l7pz8GDByGEQF1dHQAgMzMTAQEBqK2tRWNjIxYvXow77rhD+vzR0VEsXLgQS5YswfHjx1FVVQWtVou1a9dKc7q7u6FWq/Hiiy+ira0NH3zwAezt7VFTUzPrGU+cOIHly5dj//796OzsRG1tLUJCQvDoo4/K1hBCYNu2bbJ1Lly4oIiMlmqo1+uRkZEhmzNxvyql13C6fKOjo7Kx3t5evP7663Bzc5P9p6vk+uXn58Pb2xuVlZXo6enB7t274ebmhvfff1+aU1hYCI1Gg3379qG5uRlLly7FTTfdJMuQlJSEiIgIfPvtt/j6668xf/58pKamSuMDAwPw8fFBWloaWltbUV5eDldXV5SUlMx6xv7+fixZsgQ7d+5Ee3s7GhoasGjRItx+++2ydYKCgpCXlyer49DQ0KxnvJIaGgwGJCUlyb72s2fPytax5hoCMDkXt27dCpVKha6uLmmOUmsIACkpKbjlllvw5ZdfoqOjA+vXr4e7uzt+//13ANZ/HlorNoAzJCsrC/PmzcP4+Dj6+/vh6OiI3bt3S+MnT56EEAINDQ0AgKqqKtjZ2cmuChYXF8Pd3R0XL14EAGRnZyM8PFz29zz++OMmr35nysSM5uzatQtOTk6yK2BCCOzdu3fKNZWUcXI+vV6PrKysKedbWw0t1S8yMhIrV66UHVNy/R588EGTr3f58uVIS0sDcPmqg6+vL95++21pvL+/H87OztJVzLa2Nggh8P3330tzqquroVKppKtoRUVF8PT0lGoKADk5OViwYMFVy2ZkKaM5R48ehRACv/zyi3QsKCgImzZtmvJzZivjleQzGAxITk6eco25WMPk5GTcc889smNKreHw8DDs7e1RWVkpOx4dHY1169bNifPQWrEBnAEXL16Et7c38vPzAQC1tbUQQuDff/+VzQsMDMR7770HAMjNzUVERIRsvLu7G0IIHDt2DABw9913mzQgW7duhbu7+9WKMqXJGc3ZsmULtFqt7JgQAjfccAO8vb0RExOD0tJSWQOilIzm8un1emi1Wnh7eyM8PBwvv/wyzp8/L41bUw0t1a+xsRFCCBw5ckR2XMn1y8/PR1BQEH766ScAQFNTE6677jqUlZUBALq6uiCEwPHjx2WfFx8fj+effx4AUFpaCg8PD9n4pUuXYG9vjz179gAA0tPTTRqQw4cPQwhhciXq/81SRnMOHjwIlUolu1odFBQEHx8feHl5ITIyEhs3bpS9UJutjFeSz2AwQKPRQKfTITQ0FJmZmfjnn3+k8blWwz///BMODg7YsWOH7LhSazg4OAghBA4dOiQ7fuedd0Kv18+J89BasQGcATt37oS9vb30SmXHjh1wcnIymRcTE4Ps7GwAQEZGBhITE2Xj58+fhxACVVVVAICQkBAUFBTI5nz++ecQQmB4ePhqRJnS5IyT/f333wgMDMQrr7wiO56Xl4f6+nocO3YMhYWFcHZ2lr31oZSM5vKVlJSgpqYGLS0tKCsrg5+fH5YtWyaNW1MNLdXvmWeeQVhYmMlxJddvbGwMOTk5UKlUcHBwgEqlkn0tR44cgRACf/zxh+zzHnvsMaSkpAC4/MM5NDTUZG2dToeioiIAwL333ounnnpKNv7jjz9CCIG2trb/dywZSxknu3DhAqKjo7FixQrZ8XfffRd1dXVobm5GcXExPDw88MILL0jjs5XxSvKVl5ejoqICLS0t2Lt3L8LCwhATE4PR0VEAc6+GGzZsgKenp+ztUUC5NQSAuLg46PV6nD59GqOjo/jkk09gZ2eH0NDQOXEeWis2gDMgMTERDz30kPTxXGwAJ2ecaGBgAIsWLUJSUhJGRkamXSc3Nxf+/v7Sx0rJOF0+I+OV3c7OTgDWVcPp8g0PD0Oj0eCdd96xuI6S6ldeXg5/f3+Ul5ejpaUF27dvh5eXFz7++GMAc6MBtJRxopGRETz88MOIioqy+LtVS0tL4eDgIP0KrtnK+L/kMzJeUTJecZpLNQSABQsWYNWqVRbXVUoNAaCzsxPx8fEQQsDe3h4xMTFIS0vDzTffPCfOQ2vFBvAqO3XqFOzs7LBv3z7p2Fx7C9hcRqPBwUHExcUhISHB5BWrOZWVlRBCSP9pKSHjdPkmGhoaghBCesDBWmpoKd/27dvh6OiIM2fOWFxLSfXz9/fHhx9+KDv2xhtvSPcEzYW3nixlNBoZGcEjjzyC2267Tfb26FRaW1shhEB7ezuA2ct4pfkm02q12Lx5M4C5U0MA+OqrryCEQFNTk8V1lVLDiYaGhqRGLyUlBQ888MCcOA+tFRvAq2z9+vXw9fWV3YthfAjks88+k461t7ebfQjkr7/+kuaUlJTA3d1d+uFq3N5hotTU1Bl/gMBcRuDylb/FixdDr9fL7o2bzptvvglPT0/pYyVknCrfZPX19RBCoLm5GYD11NBSPr1eb/L09lSUVD8vLy/p6oBRQUEBQkJCAPz3IZCJVzYHBgbM3nze2NgozTlw4IDZm88nXt1eu3btjNx8bikj8N/mLzw8/IqaeAAoKyuDnZ2d9INztjJeSb7JfvvtN6hUKlRUVACYGzU0MhgMJk9wT0UpNTTn7Nmz0Gg0KCkpmRPnobViA3gVjY2NITAwEDk5OSZjmZmZCAwMxOHDh9HY2Ii4uDjExcVJ48YtRBITE9HU1ISamhrodDqzW4isWbMGJ0+exEcffTSj28AAU2ccGBhAbGwsbr31VnR2dsq2JjDem7N//35s2bIFJ06cQEdHB4qKiqBWq/Haa68pJuNU+To7O5GXl4fGxkb09PSgoqICwcHBiI+Pl+ZYQw2n+x4FgI6ODqhUKlRXV5uMKb1+BoMBfn5+0vYae/bsgVarlW6zAC5vP+Hh4SHdQ5acnGx2+4moqCh89913qK+vR0hIiGz7if7+fvj4+CA9PR2tra349NNPoVarZ2T7CUsZR0ZGsHTpUvj7+6OpqUl2Hhqflvzmm2+wadMmNDU1oaurC2VlZdDpdHjiiSdmPaOlfOfOncPq1avR0NCAnp4eHDp0CNHR0QgJCZFeZAHWXUOjgYEBqNVqFBcXm6yh5BoCQE1NDaqrq9Hd3Y0vvvgCERERiI2NlZo1az8PrRUbwKvowIEDEEJIT3dNZNwI2tPTE2q1GsuWLUNvb69szqlTp3D//ffD1dUVWq0WL730ktlNhCMjI+Hk5ITg4OAZ3QgamDpjXV3dlJuX9vT0ALj8GH9kZCTc3NxwzTXXICIiAps3b8bY2JjJWrOVcap8v/76K+Lj4+Hl5QVnZ2fMnz8fa9asMbm3Suk1nO57FLj8CjogIMCkJoDy6zd589ng4GCsW7dOtk2EcQNaHx8fODs7IyEhweTfoq+vD6mpqXBzc4O7uzuefPLJaTeg9fPzQ2FhoSIyTreht3E/yx9++AGxsbHQaDRwcXFBWFgYCgoKZA3UbGW0lG94eBiJiYnQ6XRwdHREUFAQMjIyTDbVt+YaGpWUlMDV1dVkM31A2TUELj9kFhwcDCcnJ/j6+uLZZ5+V5bD289BasQEkIiIisjFsAImIiIhsDBtAIiIiIhvDBpCIiIjIxrABJCIiIrIxbACJiIiIbAwbQCIiIiIbwwaQiIiIyMawASQiIiKyMWwAiYiIiGwMG0AiIiIiG8MGkIiIiMjGsAEkIiIisjFsAImIiIhsDBtAIiIiIhvDBpCIiIjIxrABJCIiIrIxbACJiIiIbAwbQCIiIiIbwwaQiIiIyMawASQiIiKyMWwAiYiIiGwMG0AiIiIiG8MGkIiIiMjGsAEkIiIisjFsAImIiIhsDBtAIiIiIhvDBpCIiIjIxrABJCIiIrIxbACJiIiIbAwbQCIiIiIbwwaQiIiIyMb8B/u9RgfSimREAAAAAElFTkSuQmCC\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f7161a81128>]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f_resonance = 8e3\n",
    "omega_resonance = 2*np.pi*f_resonance\n",
    "\n",
    "gamma = 1e7\n",
    "alpha = omega_resonance**2\n",
    "beta = 2e8\n",
    "delta = 200\n",
    "\n",
    "zs, fs = np.meshgrid(\n",
    "    np.linspace(0, 1.2, 500),\n",
    "    np.linspace(7e3, 9e3, 500)\n",
    ")\n",
    "\n",
    "plt.figure()\n",
    "G = right(gamma, alpha, beta, delta, zs, fs)\n",
    "plt.contour(fs, zs, (zs-G), [0])\n",
    "plt.xlabel(\"$\\omega$\")\n",
    "plt.ylabel(\"$z$\")\n",
    "\n",
    "n = 100\n",
    "xs, ys = sample_frequency_response(n, gamma, alpha, beta, delta, zs, fs)\n",
    "plt.figure()\n",
    "plt.plot(xs, ys)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "@curry\n",
    "def frequency_objective(omega, p):\n",
    "    obj = 0.0\n",
    "    # Simulate and return MSE(xy_data, sim_xy_data)\n",
    "    return obj\n",
    "\n",
    "p0 = (0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1)\n",
    "bounds = [\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2)\n",
    "]\n",
    "#omegas = xy_data['f'][:,0].tolist()\n",
    "#solution = minimize(objective(omega), p0, method='SLSQP', bounds=bounds)\n",
    "#p = solution.x\n",
    "\n",
    "# Simulate with updated values\n",
    "#t, X, dt, pstep = model(T, t_trans, dt_per_period, x0, v0, omega, p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a name=\"model\"></a>\n",
    "## Model\n",
    "\n",
    "Model derived from Duffing equations:\n",
    "\n",
    "\\begin{align}\n",
    "m_1 \\ddot{y}_1 &= F_1 - \\dot{y}_1(c_1 + c_3) + \\dot{y}_2c_3 - y_1(k_1 + k_3) + y_2k_3 - \\alpha_1y_1^3 + \\alpha_3(y_2 - y_1)^3 \\\\\n",
    "m_2 \\ddot{y}_2 &= F_2 - \\dot{y}_2(c_2 + c_3) + \\dot{y}_1c_3 - x_2(k_2 + k_3) + y_1k_3 - \\alpha_2y_2^3 + \\alpha_3(y_2 - y_1)^3 \\\\\n",
    "\\end{align}\n",
    "\n",
    "where $F = Ce^{i\\omega t}$. Transform to first-order form by variable substitutions $x_3 = \\dot{y}_1, x_1 = y_1$ and $x_4 = \\dot{y}_2, x_2 = y_2$:\n",
    "\n",
    "\\begin{align}\n",
    "\\dot{x}_1 &= x_3 \\\\\n",
    "\\dot{x}_2 &= x_4 \\\\\n",
    "m_1\\dot{x}_3 &= F_1 - x_3(c_1 + c_3) + x_4c_3 - x_1(k_1 + k_3) + x_2k_3 - \\alpha_1x_1^3 + \\alpha_3(x_2 - x_1)^3 \\\\\n",
    "m_2\\dot{x}_4 &= F_2 - x_4(c_2 + c_3) + x_3c_3 - x_2(k_2 + k_3) + x_1k_3 - \\alpha_2x_2^3 + \\alpha_3(x_2 - x_1)^3 \\\\\n",
    "\\end{align}\n",
    "\n",
    "\n",
    "For some reason, this model doesn't work out when working backwards from resonnance frequencies. I may be missing something obvious, otherwise the fact that mass goes into the estimations may mess things up.\n",
    "\n",
    "\n",
    "### Transformed model\n",
    "\n",
    "Eliminate mass, + easier to reason about physical constants:\n",
    "\n",
    "\\begin{align}\n",
    "\\dot{x}_1 &= x_3 \\\\\n",
    "\\dot{x}_2 &= x_4 \\\\\n",
    "\\dot{x}_3 &= \\frac{1}{m_1}F_1 - x_3(c_1 + c_3) + x_4c_3 - x_1(k_1 + k_3) + x_2k_3 - \\alpha_1x_1^3 + \\alpha_3(x_2 - x_1)^3 \\\\\n",
    "\\dot{x}_4 &= \\frac{1}{m_2}F_2 - x_4(c_2 + c_3) + x_3c_3 - x_2(k_2 + k_3) + x_1k_3 - \\alpha_2x_2^3 + \\alpha_3(x_2 - x_1)^3 \\\\\n",
    "\\end{align}\n",
    "\n",
    "With the Jacobian $\\mathbf{J} = \\frac{\\partial \\mathbf{f}}{\\partial \\mathbf{X}}$\n",
    "\n",
    "\\begin{bmatrix}\n",
    "0 & 0 & 1 & 0 \\\\\n",
    "0 & 0 & 0 & 1 \\\\\n",
    "-k_1 - k_3 - 3\\alpha_1x_1^2 - 3\\alpha_3(x_2 - x_1)^2 & k_3 + 3\\alpha_3(x_2 - x_1)^2 & -c_1 - c_3 & c_3 \\\\\n",
    "k_3 - 3\\alpha_3(x_2 - x_1)^2 & -k_2 - k_3 - 3\\alpha_2x_2^2 + 3\\alpha_3(x_2 - x_1)^2 & c_3 & -c_2 - c_3\n",
    "\\end{bmatrix}\n",
    "\n",
    "Use the harmonic oscillator identities\n",
    "\n",
    "  * Undamped angular frequency:\n",
    "\n",
    "\\begin{align}\n",
    "\\omega_0 &= \\sqrt{\\frac{k}{m}}\n",
    "\\end{align}\n",
    "\n",
    "  * Damping ratio:\n",
    "\n",
    "\\begin{align}\n",
    "\\zeta &= \\frac{c}{2\\sqrt{mk}}\n",
    "\\end{align}\n",
    "\n",
    "  * Resonant freqency:\n",
    "\n",
    "\\begin{align}\n",
    "\\omega_r &= \\omega_0\\sqrt{1-2\\zeta^2}, \\zeta < \\frac{1}{\\sqrt{2}}\n",
    "\\end{align}\n",
    "\n",
    "and express the constants subject to estimation as\n",
    "\n",
    "\\begin{align}\n",
    "c_1 &= 2 \\zeta_1 \\omega_{0,1} \\\\\n",
    "c_2 &= 2 \\zeta_2 \\omega_{0,2} \\\\\n",
    "c_3 &= g_c(c_1, c_2) \\\\\n",
    "k_1 &= \\omega_{0,1}^2 \\\\\n",
    "k_2 &= \\omega_{0,2}^2 \\\\\n",
    "k_3 &= g_k(k_1, k_2) \\\\\n",
    "\\alpha_1 &= f_1(\\mathbf{X} ; \\theta) \\\\\n",
    "\\alpha_2 &= f_2(\\mathbf{X} ; \\theta) \\\\\n",
    "\\alpha_3 &= g_{\\alpha}(\\alpha_1, \\alpha_2)\n",
    "\\end{align}\n",
    "\n",
    "\n",
    "With the model expressed this way, things make sense and we get resonnance where it should be.\n",
    "\n",
    "\n",
    "### Notes on solvers\n",
    "\n",
    "  * We use SciPy's `solve_ivp` to simulate the system. Different methods (RK45, LSODA, Radeau) has been tested with no noticable differences.\n",
    "  * The standard `odeint` from SciPy is super shit. It easily diverges and is unstable. They claim to use the standard LSODA solver (same as `solve_ivp` with method='LSODA') but the results are entirely different.\n",
    "  * Once we hit the right parameters, the simulation is considerable slower because these are adaptive solvers.\n",
    "  * There is an ODE implementation from the [PyDSTool package](https://github.com/robclewley/pydstool) which compiles to C and is much much faster.\n",
    "  \n",
    "#### PyDSTool solver\n",
    "\n",
    "The model is implemented with this solver. It's slightly faster, but notoriously more complicated to use. Besides, it requires SciPy version `<1.0` which is not compatible with the rest of this code. Let's stick to scipy's modern solvers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "@curry\n",
    "def model1(omega, p, t, X):\n",
    "    x1, x2, xd1, xd2 = X\n",
    "    C1, C2, m1, m2, c1, c2, c3, k1, k2, k3, a1, a2, a3 = p\n",
    "    F1 = C1*np.cos(omega*t)\n",
    "    F2 = C2*np.cos(omega*t)\n",
    "    xdd1 = F1 - xd1*(c1 + c3) + xd2*c3 - x1*(k1 + k3) + x2*k3 - a1*x1**3 + a3*(x2 - x1)**3\n",
    "    xdd2 = F2 - xd2*(c2 + c3) + xd1*c3 - x2*(k2 + k3) + x1*k3 - a2*x2**3 + a3*(x2 - x1)**3\n",
    "    return xd1, xd2, m1*xdd1, m2*xdd2\n",
    "\n",
    "@curry\n",
    "def model2(omega, p, t, X):\n",
    "    x1, x2, xd1, xd2 = X\n",
    "    C1, C2, m1, m2, c1, c2, c3, k1, k2, k3, a1, a2, a3 = p\n",
    "    xdd1 = C1*np.cos(omega*t)/m1 - xd1*(c1 + c3) + xd2*c3 - x1*(k1 + k3) + x2*k3 - a1*x1**3 + a3*(x2 - x1)**3\n",
    "    xdd2 = C2*np.cos(omega*t)/m2 - xd2*(c2 + c3) + xd1*c3 - x2*(k2 + k3) + x1*k3 - a2*x2**3 + a3*(x2 - x1)**3\n",
    "    return xd1, xd2, xdd1, xdd2\n",
    "\n",
    "@curry\n",
    "def jacobian2(omega, p, t, X):\n",
    "    x1, x2, xd1, xd2 = X\n",
    "    C1, C2, m1, m2, c1, c2, c3, k1, k2, k3, a1, a2, a3 = p\n",
    "    return np.array([\n",
    "        [             0                   ,            0                      ,     1   ,   0   ],\n",
    "        [             0                   ,            0                      ,     0   ,   1   ],\n",
    "        [-k1-k3-3*a1*x1**2-3*a3*(x2-x1)**2,    k3+3*a3*(x2-x1)**2             ,  -c1-c3 ,   c3  ],\n",
    "        [    k3-3*a3*(x2-x1)**2           , -k2-k3-3*a2*x2**2+3*a3*(x2-x1)**2 ,     c3  , -c2-c3]\n",
    "    ])\n",
    "\n",
    "def odeint_integrate(model, jac, dt, T, X0, rtol, atol):\n",
    "    t = np.linspace(0, T, int(T/dt))\n",
    "    X = odeint(model, X0, t, Dfun=jac, tfirst=True, rtol=rtol, atol=atol)\n",
    "    return X.T\n",
    "\n",
    "def solve_ivp_integrate(model, jac, dt, T, X0, rtol, atol):\n",
    "    t = np.linspace(0, T, int(T/dt))\n",
    "    sol = solve_ivp(model, [0, T], X0, t_eval=t, jac=jac, method='Radau', first_step=dt, rtol=rtol, atol=atol)\n",
    "    return sol.y\n",
    "\n",
    "# Rely on the same functional signatures by mimicing the data structure of lab measurement.\n",
    "def simulate_xy_data(integrator, rows, xy_data, T, t_trans, t_scale, steps, x0, v0, p, progress=True):\n",
    "    sim_xy_data = {\n",
    "        'x': np.zeros((101, 100)),\n",
    "        'y': np.zeros((101, 100)),\n",
    "        'f': np.zeros((101, 100)),\n",
    "        'XResfFreq': xy_data['XResfFreq'],\n",
    "        'YResfFreq': xy_data['YResfFreq']\n",
    "    }\n",
    "    _rows = tqdm(rows) if progress else rows\n",
    "    for i in _rows:\n",
    "        f = xy_data['f'][i,0]\n",
    "        omega = 2*np.pi*f/t_scale\n",
    "        X = integrator(\n",
    "            model2(omega, p),\n",
    "            jacobian2(omega, p),\n",
    "            (T-t_trans)/steps,\n",
    "            T,\n",
    "            x0 + v0,\n",
    "            1e-3,\n",
    "            [1e-4, 1e-4, 1e-2, 1e-2]\n",
    "        )\n",
    "        x1, x2, xd1, xd2 = X\n",
    "        sim_xy_data['x'][i,:] = x1[-steps:]\n",
    "        sim_xy_data['y'][i,:] = x2[-steps:]\n",
    "        sim_xy_data['f'][i,:] = f\n",
    "    return sim_xy_data\n",
    "\n",
    "def simulate_experiment(xy_data, rows, zeta1, zeta2, gc, gk, ga, f1, f2, verbose=True):\n",
    "    # Amplitude at resonnance should be 1\n",
    "    # Aim for better numerical stability by setting C and m to approx. the same numeric precision\n",
    "    t_scale = 1\n",
    "    C1 = 1e7/t_scale\n",
    "    C2 = 1e7/t_scale\n",
    "    m1 = 1\n",
    "    m2 = 1\n",
    "\n",
    "    # Fetch resonnance frequencies from data\n",
    "    f_r1 = xy_data['XResfFreq']/t_scale\n",
    "    f_r2 = xy_data['YResfFreq']/t_scale\n",
    "    omega_r1 = 2*np.pi*f_r1\n",
    "    omega_r2 = 2*np.pi*f_r2\n",
    "    #omega_01 = omega_r1/(np.sqrt(1-2*zeta1**2))\n",
    "    #omega_02 = omega_r2/(np.sqrt(1-2*zeta2**2))\n",
    "\n",
    "    # Compute parameters from identities\n",
    "    #c1 = 2*zeta1*omega_01\n",
    "    #c2 = 2*zeta2*omega_02\n",
    "    c1 = 200\n",
    "    c2 = 200\n",
    "    c3 = gc(c1, c2)\n",
    "    k1 = omega_r1**2\n",
    "    k2 = omega_r2**2\n",
    "    k3 = gk(k1, k2)\n",
    "    #a1 = f1(k1, k2)\n",
    "    #a2 = f2(k1, k2)\n",
    "    #a3 = ga(k1, k2)\n",
    "    a1 = 1e8\n",
    "    a2 = 1e8\n",
    "    a3 = 0\n",
    "\n",
    "    p = (\n",
    "        C1, C2,\n",
    "        m1, m2,\n",
    "        c1, c2, c3,\n",
    "        k1, k2, k3,\n",
    "        a1, a2, a3\n",
    "    )\n",
    "\n",
    "    if verbose:\n",
    "        print(\"Parameters:\")\n",
    "        print(\"Omega_r 1 = %.3f\" % omega_r1)\n",
    "        print(\"Omega_r 2 = %.3f\" % omega_r2)\n",
    "        #print(\"Omega0 1 = %.3f\" % omega_01)\n",
    "        #print(\"Omega0 2 = %.3f\" % omega_02)\n",
    "        print(\"c1 = %.3f\" % c1)\n",
    "        print(\"c2 = %.3f\" % c2)\n",
    "        print(\"c3 = %.3f\" % c3)\n",
    "        print(\"k1 = %.3f\" % k1)\n",
    "        print(\"k2 = %.3f\" % k2)\n",
    "        print(\"k3 = %.3f\" % k3)\n",
    "        print(\"a1 = %.3f\" % a1)\n",
    "        print(\"a2 = %.3f\" % a2)\n",
    "        print(\"a3 = %.3f\" % a3)\n",
    "\n",
    "    # Start from any state, the system stabilize quickly\n",
    "    x0, v0 = (-0.002, 0.01), (-0.004, 0.03)\n",
    "    #x0, v0 = (0.0, 0.0), (0.0, 0.0)\n",
    "    \n",
    "    # Set transient period to 0.1 seconds and simulate 100 steps over 0.5 seconds\n",
    "    t_trans = 0.1*t_scale\n",
    "    T = t_trans + 0.5*t_scale\n",
    "    steps = 100\n",
    "\n",
    "    # Simulate mostly around resonnance\n",
    "    return simulate_xy_data(solve_ivp_integrate, rows, xy_data, T, t_trans, t_scale, steps, x0, v0, p, progress=verbose)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Harmonic oscillator\n",
    "\n",
    "Set $c_3 = k_3 = \\alpha_1 = \\alpha_2 = \\alpha_3 = 0$ for simulating a standard driven harmonic oscillator with no coupling between x- and y-components. Assume damping $\\zeta_1 = \\zeta_2 = 0.1$ and use resonnance frequencies from lab data to estimate parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "exp_no = 0\n",
    "print(\"Read data, experiment %d\" % exp_no)\n",
    "xy_data = read_xy('data/XYPost.mat', exp_no)\n",
    "\n",
    "def gc(c1, c2):\n",
    "    return 0.0\n",
    "\n",
    "def gk(k1, k2):\n",
    "    return 0.0\n",
    "\n",
    "def f1(k1, k2):\n",
    "    return 0.0\n",
    "\n",
    "def f2(k1, k2):\n",
    "    return 0.0\n",
    "\n",
    "def ga(k1, k2):\n",
    "    return 0.0\n",
    "\n",
    "rows = [50, 65, 70, 71, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 90, 100]\n",
    "zeta1 = 0.1\n",
    "zeta2 = 0.1\n",
    "xyhat_data = simulate_experiment(xy_data, rows, zeta1, zeta2, gc, gk, ga, f1, f2, verbose=True)\n",
    "\n",
    "plot_std_freqscan(xyhat_data)\n",
    "plot_xy(rows, xyhat_data)\n",
    "plot_xyt(rows, xy_data, sim_xy_data=xyhat_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### With duffing term\n",
    "\n",
    "The duffing term has to be pretty large to see any stiffening effect. Set $\\alpha_1 = 1500k_1$ and $\\alpha_2 = 1500k_2$ (still without coupling)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "exp_no = 0\n",
    "print(\"Read data, experiment %d\" % exp_no)\n",
    "xy_data = read_xy('data/XYPost.mat', exp_no)\n",
    "\n",
    "def gc(c1, c2):\n",
    "    return 0.0\n",
    "\n",
    "def gk(k1, k2):\n",
    "    return 0.0\n",
    "\n",
    "def f1(k1, k2):\n",
    "    return 1.5e3*k1\n",
    "\n",
    "def f2(k1, k2):\n",
    "    return 1.5e3*k2\n",
    "\n",
    "def ga(k1, k2):\n",
    "    return 0.0\n",
    "\n",
    "rows = [50, 65, 70, 75, 80, 85, 90, 100]\n",
    "zeta1 = 0.1\n",
    "zeta2 = 0.1\n",
    "xyhat_data = simulate_experiment(xy_data, rows, zeta1, zeta2, gc, gk, ga, f1, f2, verbose=True)\n",
    "\n",
    "plot_std_freqscan(xyhat_data)\n",
    "plot_xy(rows, xyhat_data)\n",
    "plot_xyt(rows, xy_data, sim_xy_data=xyhat_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### With coupling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "exp_no = 0\n",
    "print(\"Read data, experiment %d\" % exp_no)\n",
    "xy_data = read_xy('data/XYPost.mat', exp_no)\n",
    "\n",
    "def gc(c1, c2):\n",
    "    return 0.05*(c1 + c2)\n",
    "\n",
    "def gk(k1, k2):\n",
    "    return 0.05*(k1 + k2)\n",
    "\n",
    "def f1(k1, k2):\n",
    "    return 1.5e3*k1\n",
    "\n",
    "def f2(k1, k2):\n",
    "    return 1.5e3*k2\n",
    "\n",
    "def ga(k1, k2):\n",
    "    return 0.05*(a1 + a2)\n",
    "\n",
    "rows = [50, 65, 70, 75, 80, 85, 90, 100]\n",
    "zeta1 = 0.1\n",
    "zeta2 = 0.1\n",
    "xyhat_data = simulate_experiment(xy_data, rows, zeta1, zeta2, gc, gk, ga, f1, f2, verbose=True)\n",
    "\n",
    "plot_std_freqscan(xyhat_data)\n",
    "plot_xy(rows, xyhat_data)\n",
    "plot_xyt(rows, xy_data, sim_xy_data=xyhat_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a name=\"loss-function\"></a>\n",
    "## Loss function\n",
    "\n",
    "Given the two multivariate signals, one empirical and one simulated, we need a distance metric $d(\\mathbf{S}(\\omega), \\hat{\\mathbf{S}}(\\omega))$ that quantifies the error of our simulation.\n",
    "\n",
    "Consider first a single frequency $\\mathbf{S}(\\omega=x) \\in \\mathbb{R}^2$. Treat each component individually, perform autocorrelation do find the shift, then simply use mean squared error as the distance metric between the two common periods of $\\mathbf{S}$ and $\\hat{\\mathbf{S}}$. We extend this to the multivariate case by simply averaging the loss for each frequency.\n",
    "\n",
    "TODO: Assert that both components of $\\mathbf{S}(\\omega=x)$ have the same shift."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def normalize_signal(s):\n",
    "    return (s - np.mean(s)) / np.std(s)\n",
    "\n",
    "def autocorrelate_1d(s1, s2):\n",
    "    corr = np.correlate(s1, s2, mode='same') / (np.linalg.norm(s1)*np.linalg.norm(s2))\n",
    "    corr_half = corr[int(len(s1)/2):]\n",
    "    idx = np.argmax(corr_half)\n",
    "    return idx, corr_half[idx]\n",
    "\n",
    "def loss_1d(s1, s2, normalize=True):\n",
    "    assert len(s1) == len(s2)\n",
    "    N = len(s1)\n",
    "    if normalize:\n",
    "        _s1 = normalize_signal(s1)\n",
    "        _s2 = normalize_signal(s2)\n",
    "    else:\n",
    "        _s1 = s1\n",
    "        _s2 = s2\n",
    "    idx, coeff = autocorrelate_1d(_s1, _s2)\n",
    "    return idx, coeff, np.mean((_s1[idx:]-_s2[:N-idx])**2)\n",
    "\n",
    "def xy_loss(rows, xy_data, xyhat_data, normalize=True, verbose=False):\n",
    "    # Calculate correlation coefficients and MSE for both x and y for the specified set of rows\n",
    "    x_idxs, x_coeffs, x_mses = zip(*[loss_1d(xy_data['x'][i,:], xyhat_data['x'][i,:], normalize=normalize) for i in rows])\n",
    "    y_idxs, y_coeffs, y_mses = zip(*[loss_1d(xy_data['y'][i,:], xyhat_data['y'][i,:], normalize=normalize) for i in rows])\n",
    "    # Print some statistics\n",
    "    if verbose:\n",
    "        print('\\n'.join(map(\n",
    "            lambda var: \"%s: %.4f mean, %.4f std\" % (var[0], np.mean(var[1]), np.std(var[1])),\n",
    "            [\n",
    "                ('X idx', x_idxs),\n",
    "                ('Y idx', y_idxs),\n",
    "                ('X coeffs', x_coeffs),\n",
    "                ('Y coeffs', y_coeffs),\n",
    "                ('X MSEs', x_mses),\n",
    "                ('Y MSEs', y_mses)\n",
    "            ]\n",
    "        )))\n",
    "    # Return the sum of means of both components\n",
    "    return np.mean(x_mses) + np.mean(y_mses)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Loss function test\n",
    "\n",
    "Random signals and sines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# Test loss function\n",
    "t = np.linspace(0, 100, 100)\n",
    "s1 = {\n",
    "    'f': np.array([\n",
    "        np.ones((100,)),\n",
    "        2*np.ones((100,))\n",
    "    ]),\n",
    "    'x': np.array([\n",
    "        np.random.randn(100),\n",
    "        np.array([1*np.sin(i/np.pi) for i in t]),\n",
    "    ]),\n",
    "    'y': np.array([\n",
    "        np.random.randn(100),\n",
    "        np.array([1*np.cos(i/np.pi) for i in t]),\n",
    "    ])\n",
    "}\n",
    "s2 = {\n",
    "    'f': np.array([\n",
    "        np.ones((100,)),\n",
    "        2*np.ones((100,))\n",
    "    ]),\n",
    "    'x': np.array([\n",
    "        np.random.randn(100),\n",
    "        np.array([1*np.cos(i/np.pi) for i in t]),\n",
    "    ]),\n",
    "    'y': np.array([\n",
    "        np.random.randn(100),\n",
    "        np.array([1*np.sin(i/np.pi) for i in t]),\n",
    "    ])\n",
    "}\n",
    "\n",
    "plot_xyt([0,1], s1, sim_xy_data=s2)\n",
    "\n",
    "print(\"Loss: %.4f\\n\" % xy_loss([0], s1, s2, verbose=True))\n",
    "print(\"Loss: %.4f\\n\" % xy_loss([1], s1, s2, verbose=True))\n",
    "print(\"Loss: %.4f\" % xy_loss([0, 1], s1, s2, verbose=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Loss for model\n",
    "\n",
    "Plotting normalized signals."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "print(\"Loss: %.4f\\n\" % xy_loss(rows, xy_data, xyhat_data, verbose=True))\n",
    "plot_xyt(rows, xy_data, normalizer=normalize_signal, sim_xy_data=xyhat_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#C_grid = [1e1] # Amplitude of driving force (gamma)\n",
    "#c_grid = [1e2] # Damping (delta)\n",
    "#a_grid = [1e-1] # Non-linear restoring force (beta)\n",
    "#k_grid = [1e6] # Linear stiffness (alpha)\n",
    "\n",
    "#xy_data = read_xy('data/XYPost.mat', 0)\n",
    "#rows = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]\n",
    "#rows = [10, 65, 70, 75, 80, 85, 90]\n",
    "\n",
    "#losses = []\n",
    "#best_loss = 1e9\n",
    "#best_p = None\n",
    "#for c, a, k, C in tqdm.tqdm(itertools.product(*[c_grid, a_grid, k_grid, C_grid])):\n",
    "#    print(\"c1=c2=c3=%.4f, a1=a2=a3=%.4f, k1=k2=k3=%.4f, C1=C2=%.4f\" % (c, a, k, C))\n",
    "#    _damping = 0.001\n",
    "#    _omegar = 8e3\n",
    "#    _omega0 = _omegar/(np.sqrt(1-2*_damping**2))\n",
    "#    C = 1e5\n",
    "#    c2 = 2*_damping*_omega0\n",
    "#    k2 = _omega0**2\n",
    "#    a = 0.5\n",
    "#    p = (C, C, 0.03*c2, c2, 0.01*c2, 0.01*a, 0.9*a, 0.02*a, 0.5*k2, k2, 0.1*k2)\n",
    "#    #p = (C, C, c, c, c, a, a, a, k, k, k)\n",
    "#    xyhat_data = simulate_xy_data(rows, xy_data, p)\n",
    "#    loss = xy_loss(rows, xy_data, xyhat_data, verbose=True)\n",
    "#    losses.append(loss)\n",
    "#    if loss < best_loss:\n",
    "#        best_loss = loss\n",
    "#        best_p = p\n",
    "#    print(\"Loss: %.4f\\n\" % loss)\n",
    "#    plot_xyt(rows, xy_data, sim_xy_data=xyhat_data)\n",
    "#    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "@curry\n",
    "def objective(omega, p):\n",
    "    obj = 0.0\n",
    "    # Simulate and return MSE(xy_data, sim_xy_data)\n",
    "    return obj\n",
    "\n",
    "p0 = (0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1)\n",
    "bounds = [\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2),\n",
    "    (0.1, 0.2)\n",
    "]\n",
    "#omegas = xy_data['f'][:,0].tolist()\n",
    "#solution = minimize(objective(omega), p0, method='SLSQP', bounds=bounds)\n",
    "#p = solution.x\n",
    "\n",
    "# Simulate with updated values\n",
    "#t, X, dt, pstep = model(T, t_trans, dt_per_period, x0, v0, omega, p)"
   ]
  }
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