{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Integration with Python\n",
    "\n",
    "This cookbook explains you how to perform azimuthal integration using the python interpreter.\n",
    "It is divided in two parts, the first part uses purely python while the second will use some advanced feature of the Jupyter notebook.\n",
    "\n",
    "We will re-use the same files as is the other tutorials.\n",
    "\n",
    "## Performing azimuthal integration with pyFAI of a bunch of images\n",
    "\n",
    "To be able to perform the azimuthal integration of some images, one needs:\n",
    "\n",
    "* The diffraction images themselves, in this example they are stored as TIFF files\n",
    "* The geometry of the experimental setup as obtained from the calibration and stored as a PONI-file\n",
    "* other files like flat-field, dark current images or detector distortion file (spline-fle).\n",
    "\n",
    "Image file: http://www.silx.org/pub/pyFAI/cookbook/calibration/LaB6_29.4keV.tif\n",
    "\n",
    "Detector distortion file: http://www.silx.org/pub/pyFAI/cookbook/calibration/F_K4320T_Cam43_30012013_distorsion.spline\n",
    "\n",
    "The calibration has been performed in the previous cookbook. The geometry is saved in \"LaB6_29.4keV.poni\".\n",
    "\n",
    "### Basic usage of pyFAI\n",
    "To perform azimuthal averaging, one can use the pyFAI and FabIO libraries, the former to load the geometry and later to read the image:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mntdirect/_scisoft/users/jupyter/jupy35/lib/python3.5/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "image: <fabio.tifimage.TifImage object at 0x7fc810670e48>\n",
      "\n",
      "Integrator: \n",
      " Detector Detector\t Spline= /users/kieffer/workspace-400/pyFAI/doc/source/usage/cookbook/F_K4320T_Cam43_30012013_distorsion.spline\t PixelSize= 5.168e-05, 5.126e-05 m\n",
      "Wavelength= 4.217150e-11m\n",
      "SampleDetDist= 1.182208e-01m\tPONI= 5.394843e-02, 5.551600e-02m\trot1=0.006974  rot2= -0.003313  rot3= -0.000000 rad\n",
      "DirectBeamDist= 118.224mm\tCenter: x=1066.839, y=1036.336 pix\tTilt=0.442 deg  tiltPlanRotation= -154.594 deg\n"
     ]
    }
   ],
   "source": [
    "import pyFAI, fabio\n",
    "\n",
    "img = fabio.open(\"LaB6_29.4keV.tif\")\n",
    "print(\"image:\", img)\n",
    "\n",
    "ai = pyFAI.load(\"LaB6_29.4keV.poni\")\n",
    "print(\"\\nIntegrator: \\n\", ai)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Azimuthal averaging using pyFAI\n",
    "\n",
    "\n",
    "One needs first to retrieve the image as a numpy array. This allows to use other libraries than FabIO for image reading, for example HDF5.\n",
    "\n",
    "This shows how to perform the azimuthal integration of one image over 1000 bins:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "img_array: <class 'numpy.ndarray'> (2048, 2048) float32\n"
     ]
    }
   ],
   "source": [
    "img_array = img.data\n",
    "print(\"img_array:\", type(img_array), img_array.shape, img_array.dtype)\n",
    "\n",
    "res = ai.integrate1d(img_array, \n",
    "                     1000, \n",
    "                     unit=\"2th_deg\", \n",
    "                     filename=\"integrated.dat\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Note:* There are 2 mandatory parameters for this method, the 2D-numpy array with the image and the number of bins. We specified in addition the name of the file, where to save the data and the unit for performing the integration.\n",
    "\n",
    "There are many other options to integrate1d:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on method integrate1d in module pyFAI.azimuthalIntegrator:\n",
      "\n",
      "integrate1d(data, npt, filename=None, correctSolidAngle=True, variance=None, error_model=None, radial_range=None, azimuth_range=None, mask=None, dummy=None, delta_dummy=None, polarization_factor=None, dark=None, flat=None, method='csr', unit=q_nm^-1, safe=True, normalization_factor=1.0, block_size=32, profile=False, all=False, metadata=None) method of pyFAI.azimuthalIntegrator.AzimuthalIntegrator instance\n",
      "    Calculate the azimuthal integrated Saxs curve in q(nm^-1) by default\n",
      "    \n",
      "    Multi algorithm implementation (tries to be bullet proof), suitable for SAXS, WAXS, ... and much more\n",
      "    \n",
      "    \n",
      "    \n",
      "    :param data: 2D array from the Detector/CCD camera\n",
      "    :type data: ndarray\n",
      "    :param npt: number of points in the output pattern\n",
      "    :type npt: int\n",
      "    :param filename: output filename in 2/3 column ascii format\n",
      "    :type filename: str\n",
      "    :param correctSolidAngle: correct for solid angle of each pixel if True\n",
      "    :type correctSolidAngle: bool\n",
      "    :param variance: array containing the variance of the data. If not available, no error propagation is done\n",
      "    :type variance: ndarray\n",
      "    :param error_model: When the variance is unknown, an error model can be given: \"poisson\" (variance = I), \"azimuthal\" (variance = (I-<I>)^2)\n",
      "    :type error_model: str\n",
      "    :param radial_range: The lower and upper range of the radial unit. If not provided, range is simply (data.min(), data.max()). Values outside the range are ignored.\n",
      "    :type radial_range: (float, float), optional\n",
      "    :param azimuth_range: The lower and upper range of the azimuthal angle in degree. If not provided, range is simply (data.min(), data.max()). Values outside the range are ignored.\n",
      "    :type azimuth_range: (float, float), optional\n",
      "    :param mask: array (same size as image) with 1 for masked pixels, and 0 for valid pixels\n",
      "    :type mask: ndarray\n",
      "    :param dummy: value for dead/masked pixels\n",
      "    :type dummy: float\n",
      "    :param delta_dummy: precision for dummy value\n",
      "    :type delta_dummy: float\n",
      "    :param polarization_factor: polarization factor between -1 (vertical) and +1 (horizontal).\n",
      "           0 for circular polarization or random,\n",
      "           None for no correction,\n",
      "           True for using the former correction\n",
      "    :type polarization_factor: float\n",
      "    :param dark: dark noise image\n",
      "    :type dark: ndarray\n",
      "    :param flat: flat field image\n",
      "    :type flat: ndarray\n",
      "    :param method: can be \"numpy\", \"cython\", \"BBox\" or \"splitpixel\", \"lut\", \"csr\", \"nosplit_csr\", \"full_csr\", \"lut_ocl\" and \"csr_ocl\" if you want to go on GPU. To Specify the device: \"csr_ocl_1,2\"\n",
      "    :type method: str\n",
      "    :param unit: Output units, can be \"q_nm^-1\", \"q_A^-1\", \"2th_deg\", \"2th_rad\", \"r_mm\" for now\n",
      "    :type unit: pyFAI.units.Unit\n",
      "    :param safe: Do some extra checks to ensure LUT/CSR is still valid. False is faster.\n",
      "    :type safe: bool\n",
      "    :param normalization_factor: Value of a normalization monitor\n",
      "    :type normalization_factor: float\n",
      "    :param block_size: size of the block for OpenCL integration (unused?)\n",
      "    :param profile: set to True to enable profiling in OpenCL\n",
      "    :param all: if true return a dictionary with many more parameters (deprecated, please refer to the documentation of Integrate1dResult).\n",
      "    :type all: bool\n",
      "    :param metadata: JSON serializable object containing the metadata, usually a dictionary.\n",
      "    :return: q/2th/r bins center positions and regrouped intensity (and error array if variance or variance model provided), uneless all==True.\n",
      "    :rtype: Integrate1dResult, dict\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(ai.integrate1d)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The result file contains the integrated data with some headers as shown:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# == pyFAI calibration ==\n",
      "# Distance Sample to Detector: 0.118220810284 m\n",
      "# PONI: 5.395e-02, 5.552e-02 m\n",
      "# Rotations: 0.006974 -0.003313 -0.000000 rad\n",
      "#\n",
      "# == Fit2d calibration ==\n",
      "# Distance Sample-beamCenter: 118.224 mm\n",
      "# Center: x=1066.839, y=1036.336 pix\n",
      "# Tilt: 0.442 deg  TiltPlanRot: -154.594 deg\n",
      "#\n",
      "# Detector Detector\t Spline= /users/kieffer/workspace-400/pyFAI/doc/source/usage/cookbook/F_K4320T_Cam43_30012013_distorsion.spline\t PixelSize= 5.168e-05, 5.126e-05 m\n",
      "#    Detector has a mask: False\n",
      "#    Detector has a dark current: False\n",
      "#    detector has a flat field: False\n",
      "#\n",
      "# Wavelength: 4.21714957131e-11 m\n",
      "# Mask applied: False\n",
      "# Dark current applied: False\n",
      "# Flat field applied: False\n",
      "# Polarization factor: None\n",
      "# Normalization factor: 1.0\n",
      "# --> integrated.dat\n",
      "#       2th_deg             I\n",
      "1.668855e-02    2.503605e+00\n",
      "5.006564e-02    2.749244e+00\n",
      "8.344273e-02    2.114206e+00\n",
      "1.168198e-01    2.755390e+00\n",
      "1.501969e-01    2.890013e+00\n",
      "1.835740e-01    2.658021e+00\n",
      "2.169511e-01    2.523173e+00\n",
      "2.503282e-01    2.822044e+00\n",
      "2.837053e-01    2.732563e+00\n",
      "3.170824e-01    2.823707e+00\n",
      "3.504595e-01    2.872520e+00\n",
      "3.838366e-01    2.791172e+00\n",
      "4.172137e-01    3.029095e+00\n",
      "4.505907e-01    3.121556e+00\n",
      "4.839678e-01    3.091311e+00\n",
      "5.173449e-01    3.026508e+00\n",
      "5.507220e-01    3.019458e+00\n",
      "5.840991e-01    3.050202e+00\n",
      "6.174762e-01    2.866862e+00\n",
      "6.508533e-01    3.191242e+00\n",
      "6.842304e-01    3.102998e+00\n",
      "7.176075e-01    2.914966e+00\n",
      "7.509846e-01    3.085007e+00\n",
      "7.843617e-01    3.014659e+00\n",
      "8.177388e-01    2.898686e+00\n",
      "8.511159e-01    3.031742e+00\n",
      "8.844929e-01    3.119843e+00\n"
     ]
    }
   ],
   "source": [
    "with open(\"integrated.dat\") as f:\n",
    "    for i in range(50):\n",
    "        print(f.readline().strip())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Azimuthal regrouping using pyFAI\n",
    "\n",
    "This option is similar to the integration but perfroms N-integration on various azimuthal angle (chi) sections of the space. It is also named \"caking\" in Fit2D.\n",
    "\n",
    "The azimuthal regrouping of an image over 500 radial bins in 360 angular steps (of 1 degree) can be performed like this:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "res2 = ai.integrate2d(img_array, \n",
    "                      500, 360, \n",
    "                     unit=\"r_mm\", \n",
    "                     filename=\"integrated.edf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"{\\nEDF_DataBlockID\": \"0.Image.Psd\",\n",
      "  \"EDF_BinarySize\": \"720000\",\n",
      "  \"EDF_HeaderSize\": \"1536\",\n",
      "  \"ByteOrder\": \"LowByteFirst\",\n",
      "  \"DataType\": \"FloatValue\",\n",
      "  \"Dim_1\": \"500\",\n",
      "  \"Dim_2\": \"360\",\n",
      "  \"Image\": \"0\",\n",
      "  \"HeaderID\": \"EH:000000:000000:000000\",\n",
      "  \"Size\": \"720000\",\n",
      "  \"Engine\": \"Detector Detector Spline= /users/kieffer/workspace-400/pyFAI/doc/source/usage/cookbook/F_K4320T_Cam43_30012013_distorsion.spline PixelSize= 5.168e-05, 5.126e-05 m Wavelength= 4.217150e-11m SampleDetDist= 1.182208e-01m PONI= 5.394843e-02, 5.551600e-02m rot1=0.006974 rot2= -0.003313 rot3= -0.000000 rad DirectBeamDist= 118.224mm Center: x=1066.839, y=1036.336 pix Tilt=0.442 deg tiltPlanRotation= -154.594 deg\",\n",
      "  \"detector\": \"Detector\",\n",
      "  \"pixel1\": \"5.1679e-05\",\n",
      "  \"pixel2\": \"5.1265e-05\",\n",
      "  \"splineFile\": \"/users/kieffer/workspace-400/pyFAI/doc/source/usage/cookbook/F_K4320T_Cam43_30012013_distorsion.spline\",\n",
      "  \"dist\": \"0.118220810284\",\n",
      "  \"poni1\": \"0.05394843456\",\n",
      "  \"poni2\": \"0.0555160034482\",\n",
      "  \"rot1\": \"0.00697431586749\",\n",
      "  \"rot2\": \"-0.00331252162112\",\n",
      "  \"rot3\": \"-4.98632051492e-10\",\n",
      "  \"wavelength\": \"4.21714957131e-11\",\n",
      "  \"r_mm_min\": \"0.07826394721632823\",\n",
      "  \"r_mm_max\": \"78.18567447975511\",\n",
      "  \"chi_min\": \"-179.50000495946867\",\n",
      "  \"chi_max\": \"179.50000495946867\",\n",
      "  \"has_mask_applied\": \"False\",\n",
      "  \"has_dark_correction\": \"False\",\n",
      "  \"has_flat_correction\": \"False\",\n",
      "  \"polarization_factor\": \"None\",\n",
      "  \"normalization_factor\": \"1.0\"\n",
      "}\n",
      "cake: <class 'numpy.ndarray'> (360, 500) float32\n"
     ]
    }
   ],
   "source": [
    "cake = fabio.open(\"integrated.edf\")\n",
    "print(cake.header)\n",
    "print(\"cake:\", type(cake.data), cake.data.shape, cake.data.dtype)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From this it is trivial to perform a loop and integrate many images. \n",
    "\n",
    "*Attention:* The AzimuthalIntegrator object (called ai here) is rather large and costly to initialize. The best practice is to crate it once and to use it many times, like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob, os\n",
    "\n",
    "all_images = glob.glob(\"LaB6*.tif\")\n",
    "ai = pyFAI.load(\"LaB6_29.4keV.poni\")\n",
    "\n",
    "for one_image in all_images:\n",
    "    fimg = fabio.open(one_image)\n",
    "    dest = os.path.splitext(one_image)[0] + \".dat\"\n",
    "    ai.integrate1d(fimg.data, \n",
    "                   1000, \n",
    "                   unit=\"2th_deg\", \n",
    "                   filename=dest)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using some advanced feature of Jupyter Notebooks\n",
    "\n",
    "Jupyter notebooks offer some advanced visualization features, especially when used with *matplotlib* and *pyFAI*.\n",
    "Unfortunately, the example shown hereafter will not work properly in normal Python scipts.\n",
    "\n",
    "### Initialization of the notebook for matplotlib integration:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mntdirect/_scisoft/users/jupyter/jupy35/lib/python3.5/site-packages/IPython/core/magics/pylab.py:160: UserWarning: pylab import has clobbered these variables: ['f']\n",
      "`%matplotlib` prevents importing * from pylab and numpy\n",
      "  \"\\n`%matplotlib` prevents importing * from pylab and numpy\"\n"
     ]
    }
   ],
   "source": [
    "%pylab nbagg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyFAI.gui import jupyter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Visualzation of different types of results reviously calculated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
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       "    } 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",
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       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
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       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
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       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
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       "    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",
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       "    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",
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       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
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       "                // 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",
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       "\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 overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    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=\"639.8333142648146\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fc78ed65978>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jupyter.display(img.data, label=img.filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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 overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    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=\"639.8333142648146\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fc78ecbad30>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jupyter.plot1d(res)"
   ]
  },
  {
   "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 overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    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=\"639.8333142648146\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fc78ec76160>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jupyter.plot2d(res2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Side note.\n",
    "If you have tried to reproduce this, you may have noticed a couple of unconstiencies: \n",
    "\n",
    "* The image is called \"tif\" while the content is an \"edf\".\n",
    "* You did not get such a good calibration and your caked image has wavy lines\n",
    "\n",
    "The first issue maybe corrected in uploading a properly converted image. \n",
    "The second issue is related to the spline which is wrong (flipped up-down)\n",
    "\n",
    "## Conclusion\n",
    "\n",
    "This cookbook exapline the basic usage of pyFAI as a Python library for azimuthal integration and simple visualization in the Jupyter notebook."
   ]
  }
 ],
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