{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from glob import glob\n",
    "import pandas as pd\n",
    "import os\n",
    "from skimage.io import imread\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sample</th>\n",
       "      <th>frame</th>\n",
       "      <th>frame_id</th>\n",
       "      <th>path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MI5</td>\n",
       "      <td>0</td>\n",
       "      <td>MI5_0_00</td>\n",
       "      <td>[../data/MI5_0_00_1500.rec.8bit.tif, ../data/M...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MI5</td>\n",
       "      <td>1</td>\n",
       "      <td>MI5_1_00</td>\n",
       "      <td>[../data/MI5_1_00_1500.rec.8bit.tif, ../data/M...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MI5</td>\n",
       "      <td>1</td>\n",
       "      <td>MI5_1_01</td>\n",
       "      <td>[../data/MI5_1_01_1500.rec.8bit.tif, ../data/M...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MI5</td>\n",
       "      <td>1</td>\n",
       "      <td>MI5_1_02</td>\n",
       "      <td>[../data/MI5_1_02_1500.rec.8bit.tif, ../data/M...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MI7</td>\n",
       "      <td>0</td>\n",
       "      <td>MI7_0_00</td>\n",
       "      <td>[../data/MI7_0_00_1300.rec.8bit.tif, ../data/M...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>MI7</td>\n",
       "      <td>1</td>\n",
       "      <td>MI7_1_00</td>\n",
       "      <td>[../data/MI7_1_00_1300.rec.8bit.tif, ../data/M...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MI7</td>\n",
       "      <td>1</td>\n",
       "      <td>MI7_1_01</td>\n",
       "      <td>[../data/MI7_1_01_1300.rec.8bit.tif, ../data/M...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MI7</td>\n",
       "      <td>1</td>\n",
       "      <td>MI7_1_02</td>\n",
       "      <td>[../data/MI7_1_02_1300.rec.8bit.tif, ../data/M...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  sample  frame  frame_id                                               path\n",
       "0    MI5      0  MI5_0_00  [../data/MI5_0_00_1500.rec.8bit.tif, ../data/M...\n",
       "1    MI5      1  MI5_1_00  [../data/MI5_1_00_1500.rec.8bit.tif, ../data/M...\n",
       "2    MI5      1  MI5_1_01  [../data/MI5_1_01_1500.rec.8bit.tif, ../data/M...\n",
       "3    MI5      1  MI5_1_02  [../data/MI5_1_02_1500.rec.8bit.tif, ../data/M...\n",
       "4    MI7      0  MI7_0_00  [../data/MI7_0_00_1300.rec.8bit.tif, ../data/M...\n",
       "5    MI7      1  MI7_1_00  [../data/MI7_1_00_1300.rec.8bit.tif, ../data/M...\n",
       "6    MI7      1  MI7_1_01  [../data/MI7_1_01_1300.rec.8bit.tif, ../data/M...\n",
       "7    MI7      1  MI7_1_02  [../data/MI7_1_02_1300.rec.8bit.tif, ../data/M..."
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_images = glob(os.path.join('..', 'data', '*.tif'))\n",
    "img_df = pd.DataFrame([dict(path = c_file) for c_file in all_images])\n",
    "img_df['basename'] = img_df['path'].map(lambda x: os.path.basename(x).split('.')[0])\n",
    "img_df['frame_id'] = img_df['basename'].map(lambda x: '_'.join(x.split('_')[0:-1]))\n",
    "img_df['sample'] = img_df['basename'].map(lambda x: x.split('_')[0])\n",
    "img_df['slice'] = img_df['basename'].map(lambda x: int(x.split('_')[3]))\n",
    "img_df['frame'] = img_df['basename'].map(lambda x: int(x.split('_')[1]))\n",
    "# group by prefix\n",
    "img_3d_df = img_df.sort_values(['sample', 'frame_id', 'slice']).groupby(['sample', 'frame', 'frame_id'])['path'].apply(list).reset_index()\n",
    "img_3d_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from skimage.filters import threshold_minimum\n",
    "from skimage.morphology.convex_hull import convex_hull_image\n",
    "from skimage.morphology import binary_closing, binary_opening, disk, label\n",
    "from skimage.measure import regionprops\n",
    "\n",
    "from skimage.color import label2rgb\n",
    "from scipy import ndimage as ndi\n",
    "\n",
    "def threshold_slice_2d(raw_slice):\n",
    "    in_slice = ndi.median_filter(raw_slice, [7, 7])\n",
    "    # basic threshold\n",
    "    thresh_min = threshold_minimum(in_slice)\n",
    "    # make solid component\n",
    "    solid_part = binary_closing(in_slice>thresh_min, disk(4))\n",
    "    solid_part = ndi.binary_fill_holes(solid_part)\n",
    "    # calculate porous component inside solid\n",
    "    porous_part = (in_slice < thresh_min)*solid_part\n",
    "    #porous_part = binary_opening(porous_part, disk(2))\n",
    "    porous_part = binary_closing(porous_part, disk(2))\n",
    "    # create label by combining\n",
    "    label_slice = solid_part.astype(np.uint8).clip(0,1)\n",
    "    label_slice += (porous_part).astype(np.uint8).clip(0,1)\n",
    "    return label_slice, thresh_min\n",
    "\n",
    "def paths_to_vol(in_paths):\n",
    "    return np.stack([threshold_slice_2d(imread(x))[0] for x in in_paths],0)\n",
    "def paths_to_raw_vol(in_paths):\n",
    "    return np.stack([imread(x) for x in in_paths], 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipywidgets as ipw\n",
    "import ipyvolume as p3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MI5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mader/anaconda/envs/qbi2018/lib/python3.6/site-packages/ipyvolume/serialize.py:66: RuntimeWarning: invalid value encountered in true_divide\n",
      "  gradient = gradient / np.sqrt(gradient[0]**2 + gradient[1]**2 + gradient[2]**2)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b565107fb7e3481c9aa367a5398e830e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>VBox</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "VBox(children=(Figure(camera_center=[0.0, 0.0, 0.0], data_max=255.0, height=500, matrix_projection=[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], matrix_world=[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], style={'axes': {'visible': True, 'label': {'color': 'black'}, 'ticklabel': {'color': 'black'}, 'color': 'black'}, 'box': {'visible': True}, 'background-color': 'white'}, tf=TransferFunction(rgba=array([[0.        , 0.        , 0.        , 0.        ],\n",
       "       [0.00392157, 0.00392157, 0.00392157, 0.        ],\n",
       "       [0.00784314, 0.00784314, 0.00784314, 0.        ],\n",
       "       ...,\n",
       "       [0.99215686, 0.99215686, 0.99215686, 0.49372549],\n",
       "       [0.99607843, 0.99607843, 0.99607843, 0.49686275],\n",
       "       [1.        , 1.        , 1.        , 0.5       ]])), volume_data=array([[[ 76.,  84.,  88., ...,  81.,  83.,  85.],\n",
       "        [ 72.,  78.,  85., ...,  76.,  78.,  80.],\n",
       "        [ 74.,  79.,  86., ...,  73.,  79.,  83.],\n",
       "        ...,\n",
       "        [ 73.,  82.,  93., ...,  74.,  74.,  74.],\n",
       "        [ 93., 103., 110., ...,  74.,  73.,  72.],\n",
       "        [ 97., 104., 104., ...,  82.,  76.,  72.]],\n",
       "\n",
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       "        ...,\n",
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       "\n",
       "       [[ 82.,  87.,  85., ..., 109., 109.,  89.],\n",
       "        [ 73.,  81.,  84., ..., 118., 101.,  71.],\n",
       "        [ 69.,  69.,  76., ..., 105.,  72.,  46.],\n",
       "        ...,\n",
       "        [ 95.,  87.,  77., ...,  83.,  87.,  92.],\n",
       "        [ 85.,  76.,  71., ...,  78.,  82.,  87.],\n",
       "        [ 81.,  78.,  78., ...,  76.,  79.,  90.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[ 81.,  81.,  80., ...,  90.,  91.,  95.],\n",
       "        [ 72.,  75.,  72., ...,  93.,  96.,  99.],\n",
       "        [ 74.,  77.,  74., ..., 100., 100.,  98.],\n",
       "        ...,\n",
       "        [ 75.,  81.,  88., ...,  84.,  81.,  74.],\n",
       "        [ 79.,  85.,  88., ...,  84.,  84.,  77.],\n",
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       "\n",
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       "        [ 69.,  71.,  80., ...,  89.,  85.,  85.],\n",
       "        [ 67.,  75.,  85., ...,  90.,  87.,  87.]],\n",
       "\n",
       "       [[ 76.,  79.,  83., ...,  89.,  96.,  99.],\n",
       "        [ 71.,  72.,  78., ...,  94.,  98.,  94.],\n",
       "        [ 73.,  64.,  63., ..., 101.,  94.,  84.],\n",
       "        ...,\n",
       "        [ 88.,  84.,  80., ...,  85.,  93., 102.],\n",
       "        [ 90.,  86.,  80., ...,  81.,  85.,  97.],\n",
       "        [ 83.,  78.,  69., ...,  85.,  83.,  91.]]], dtype=float32), width=400, xlim=[0.0, 1.0], ylim=[0.0, 1.0], zlim=[0.0, 1.0]), HBox(children=(FloatSlider(value=0.5, description='ambient', max=1.0, step=0.001), FloatSlider(value=0.8, description='diffuse', max=1.0, step=0.001))), HBox(children=(FloatSlider(value=0.5, description='specular', max=1.0, step=0.001), FloatSlider(value=5.0, description='specular exp', max=10.0, step=0.001)))))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mader/anaconda/envs/qbi2018/lib/python3.6/site-packages/ipyvolume/serialize.py:66: RuntimeWarning: invalid value encountered in true_divide\n",
      "  gradient = gradient / np.sqrt(gradient[0]**2 + gradient[1]**2 + gradient[2]**2)\n"
     ]
    }
   ],
   "source": [
    "_, c_row = next(img_3d_df.query('sample == \"MI5\"').iterrows())\n",
    "n_vol = paths_to_raw_vol(c_row['path'])\n",
    "fig = p3.figure()\n",
    "# create a custom LUT\n",
    "temp_tf = plt.cm.gray(np.linspace(0, 1, 256))\n",
    "temp_tf[:,3] = np.linspace(-.3, 0.5, 256).clip(0, 1) # make transparency more aggressive\n",
    "tf = p3.transferfunction.TransferFunction(rgba = temp_tf)\n",
    "p3.volshow(n_vol.astype(np.float32), \n",
    "           lighting = True, \n",
    "           max_opacity=0.5, \n",
    "           tf = tf, \n",
    "           controls = True)\n",
    "\n",
    "p3.show()\n",
    "p3.save('mi5_raw.html')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mader/anaconda/envs/qbi2018/lib/python3.6/site-packages/ipyvolume/serialize.py:66: RuntimeWarning: invalid value encountered in true_divide\n",
      "  gradient = gradient / np.sqrt(gradient[0]**2 + gradient[1]**2 + gradient[2]**2)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
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       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>VBox</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "VBox(children=(VBox(children=(HBox(children=(Label(value='levels:'), FloatSlider(value=0.1, max=1.0, step=0.001), FloatSlider(value=0.5, max=1.0, step=0.001), FloatSlider(value=0.9, max=1.0, step=0.001))), HBox(children=(Label(value='opacities:'), FloatSlider(value=0.01, max=0.2, step=0.001), FloatSlider(value=0.05, max=0.2, step=0.001), FloatSlider(value=0.05, max=0.2, step=0.001))))), Figure(ambient_coefficient=1.0, camera_center=[0.0, 0.0, 0.0], data_max=2.0, diffuse_coefficient=0.0, height=500, matrix_projection=[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], matrix_world=[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], specular_coefficient=0.0, style={'axes': {'visible': True, 'label': {'color': 'black'}, 'ticklabel': {'color': 'black'}, 'color': 'black'}, 'box': {'visible': True}, 'background-color': 'white'}, tf=TransferFunctionWidgetJs3(level3=0.9), volume_data=array([[[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
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       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0]],\n",
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       "\n",
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       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0]],\n",
       "\n",
       "       [[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0]],\n",
       "\n",
       "       [[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0]]], dtype=uint8), width=400, xlim=[0.0, 1.0], ylim=[0.0, 1.0], zlim=[0.0, 1.0])))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_vol = paths_to_vol(c_row['path'])\n",
    "p3.quickvolshow(n_vol)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MI7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mader/anaconda/envs/qbi2018/lib/python3.6/site-packages/ipyvolume/serialize.py:66: RuntimeWarning: invalid value encountered in true_divide\n",
      "  gradient = gradient / np.sqrt(gradient[0]**2 + gradient[1]**2 + gradient[2]**2)\n"
     ]
    },
    {
     "data": {
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       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>VBox</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "VBox(children=(VBox(children=(HBox(children=(Label(value='levels:'), FloatSlider(value=0.1, max=1.0, step=0.001), FloatSlider(value=0.5, max=1.0, step=0.001), FloatSlider(value=0.9, max=1.0, step=0.001))), HBox(children=(Label(value='opacities:'), FloatSlider(value=0.01, max=0.2, step=0.001), FloatSlider(value=0.05, max=0.2, step=0.001), FloatSlider(value=0.05, max=0.2, step=0.001))))), Figure(camera_center=[0.0, 0.0, 0.0], data_max=2.0, height=500, matrix_projection=[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], matrix_world=[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], style={'axes': {'visible': True, 'label': {'color': 'black'}, 'ticklabel': {'color': 'black'}, 'color': 'black'}, 'box': {'visible': True}, 'background-color': 'white'}, tf=TransferFunctionWidgetJs3(level3=0.9), volume_data=array([[[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
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       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
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       "\n",
       "       [[0, 0, 0, ..., 0, 0, 0],\n",
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       "        ...,\n",
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       "\n",
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       "        ...,\n",
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       "\n",
       "       ...,\n",
       "\n",
       "       [[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
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       "        ...,\n",
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       "\n",
       "       [[0, 0, 0, ..., 0, 0, 0],\n",
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       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0]],\n",
       "\n",
       "       [[0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        ...,\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0],\n",
       "        [0, 0, 0, ..., 0, 0, 0]]], dtype=uint8), width=400, xlim=[0.0, 1.0], ylim=[0.0, 1.0], zlim=[0.0, 1.0]), HBox(children=(FloatSlider(value=0.5, description='ambient', max=1.0, step=0.001), FloatSlider(value=0.8, description='diffuse', max=1.0, step=0.001))), HBox(children=(FloatSlider(value=0.5, description='specular', max=1.0, step=0.001), FloatSlider(value=5.0, description='specular exp', max=10.0, step=0.001)))))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, c_row = next(img_3d_df.query('sample == \"MI7\"').iterrows())\n",
    "n_vol = paths_to_vol(c_row['path'])\n",
    "p3.quickvolshow(n_vol, lighting=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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