{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e14673fa",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# Using Regions of interest (ROIs) in DeepOF - Explore spatial information"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3044fb9",
   "metadata": {},
   "source": [
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lucasmiranda42/deepof/blob/master/docs/source/tutorial_notebooks/deepof_supervised_tutorial.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a0170cc",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "##### What we'll cover:\n",
    "    \n",
    "* Create a project with ROIs\n",
    "* Vasic ROI functionality\n",
    "* Visualize information contained in specific ROIs\n",
    "* Extract information based on different ROIs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "764990b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # If using Google colab, uncomment and run this cell and the one below to set up the environment\n",
    "# # Note: because of how colab handles the installation of local packages, this cell will kill your runtime.\n",
    "# # This is not an error! Just continue with the cells below.\n",
    "# import os\n",
    "# !git clone -q https://github.com/mlfpm/deepof.git\n",
    "# !pip install -q -e deepof --progress-bar off\n",
    "# os.chdir(\"deepof\")\n",
    "# !curl --output tutorial_files.zip https://datashare.mpcdf.mpg.de/s/Hu1XjZkY9zml0mm/download\n",
    "# !unzip tutorial_files.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "50799c68",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import os\n",
    "# os.chdir(\"deepof\")\n",
    "# import os, warnings\n",
    "# warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6048415d",
   "metadata": {},
   "source": [
    "As usual, we import some packages and plotting gear. We'll use python's os library to handle paths, pickle to load saved objects, and the data entry API within DeepOF, located in deepof.data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d64823a2",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# Import basic stuff\n",
    "import os\n",
    "import pickle\n",
    "import deepof.data\n",
    "# import plotting gear\n",
    "import deepof.visuals\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "242a120d",
   "metadata": {},
   "source": [
    "### Creating a project with ROIs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d73cb96",
   "metadata": {},
   "source": [
    "All we have to do in the project definition to create a project with ROIs is to set the input argument “number_of_rois” to any number between 1 and 20. This will then let us draw our ROIs during project creation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d192d445",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mInfo! Set arena dimension to 380.0 mm!\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[38;5;208mThe sampling rate of some of your videos differ. The maximum difference is 20191204_Day2_SI_JB08_Test_54: 24.99 fps and 20191204_Day2_SI_JB08_Test_63: 24.994 fps! Proceed with cauthion\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "my_deepof_project_raw = deepof.data.Project(\n",
    "    project_path=os.path.join(\"tutorial_files\"),\n",
    "    video_path=os.path.join(\"tutorial_files/Videos/\"),\n",
    "    table_path=os.path.join(\"tutorial_files/Tables/\"),\n",
    "    project_name=\"deepof_tutorial_project\",\n",
    "    arena=\"circular-autodetect\",\n",
    "    animal_ids=[\"B\", \"W\"],\n",
    "    table_format=\"h5\",\n",
    "    video_format=\".mp4\",\n",
    "    exclude_bodyparts=[\"Tail_1\", \"Tail_2\", \"Tail_tip\"],\n",
    "    video_scale=\"380 mm\",\n",
    "    iterative_imputation=\"partial\",  # \"full\",\n",
    "    smooth_alpha=1,\n",
    "    exp_conditions=\"./tutorial_files/tutorial_exp_conditions.csv\", # path to exp conditions table\n",
    "    number_of_rois=3, # an optional input argument that allows you to draw up to 20 different regions of interest (ROI)s during project creation\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8b261ed",
   "metadata": {},
   "source": [
    "As we run our Tutorial scripts automatically for testing purposes and the create function opens a GUI which would interfere with that, the follwoing line of code it is commented out. To create your own project, you can simply remove the \"#\" at the front of the line and execute it. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "31066d31",
   "metadata": {},
   "outputs": [],
   "source": [
    "# my_deepof_project_with_rois = my_deepof_project_raw.create(force=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9f0aeb1",
   "metadata": {},
   "source": [
    "After the arenas are detected (which will take a short while with the automatic detection) one after another, three windows will plop up for you to click your three ROIs just as you would click a nanual polygonal arena (see Figure below). You will always have to click all of the ROIs for one video, then all ROIs for the next one and so on. And just as you can do with the arenas in manual mode, you can propagate single ROIs with the \"p\"-key. This means that the respective ROI will get copied for all following videos and you will not have to click it manually. However, this means that the ROI will be copied exactly from the previous video. If you have a ROI that may differ from video to video or if your videos are rather inconsistent, it may make more sense to manually click your ROIs for all videos. For this example case we click an upper half area, a lower half area and a central circular area (as in the Figure below)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ffa1ed7",
   "metadata": {},
   "source": [
    "![rois](./Assets/roi_GUI.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60b9158e",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Loading a previously initiated project"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cca81d38",
   "metadata": {},
   "source": [
    "You can now continue to use your own project or just load the larger deepof test project with 53 videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6382da27",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# Load a previously saved project\n",
    "my_deepof_project_with_rois = deepof.data.load_project(\"./tutorial_files/tutorial_project\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f47b171a",
   "metadata": {},
   "source": [
    "**NOTE** to better show how DeepOF deals with statistics, all results shown in the documentation version of this tutorial were obtained using the full SI dataset, containing a total of 53 animals. If you'd like to gain access to this dataset, check out the code availability statement of the main DeepOF paper."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10776701",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Basic ROI functionality"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32a53f46",
   "metadata": {},
   "source": [
    "For starters, let us have a look at our ROIs for our different experiment conditions. Setting a ROI number in plot_heatmaps will lead to this ROI getting applied to all experiments in the project. If a mouse is inside or outside of a ROI is determined via the position of the center of the mouse. And which mice are relevant for that evaluation is dermined via animals_in_roi."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0553a9a5",
   "metadata": {},
   "source": [
    "For this example with roi_number=1 and animals_in_roi=\"B\" we consider all instances during which mouse B (the black mouse) was inside of ROI 1 (the upper half of the arena) for nonstressed and stressed mice. The Respectively, the position of the white mouse does not matter here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "78d2f0cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33m\n",
      "Info! Selected range exceeds 250 samples and has been downsampled by a factor of approx. 5\n",
      "To avoid this, increase 'samples_max'. This will also result in increased computation time\u001b[0m\n",
      "\u001b[33m\n",
      "Info! Selected range exceeds 250 samples and has been downsampled by a factor of approx. 5\n",
      "To avoid this, increase 'samples_max'. This will also result in increased computation time\u001b[0m\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"notebook\")\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6))\n",
    "\n",
    "# Nose based plot\n",
    "deepof.visuals.plot_heatmaps(\n",
    "    my_deepof_project_with_rois, \n",
    "    [\"B_Center\"],\n",
    "    center=\"arena\", \n",
    "    exp_condition=\"CSDS\",\n",
    "    condition_value=\"Nonstressed\",\n",
    "    ax=ax1,\n",
    "    show=False,\n",
    "    display_arena=True,\n",
    "    experiment_id=\"average\",\n",
    "    # Time binning info\n",
    "    bin_index=2,  \n",
    "    bin_size=60,\n",
    "    samples_max=250, # we reduce the maximum number of samples per experiment to allow for a fatser function execution\n",
    "    # ROI arguments\n",
    "    roi_number=1,\n",
    "    animals_in_roi=\"B\",\n",
    ")\n",
    "\n",
    "# Center based plot\n",
    "deepof.visuals.plot_heatmaps(\n",
    "    my_deepof_project_with_rois,\n",
    "    [\"B_Center\"],\n",
    "    center=\"arena\", \n",
    "    exp_condition=\"CSDS\",\n",
    "    condition_value=\"Stressed\", \n",
    "    ax=ax2,\n",
    "    show=False,\n",
    "    display_arena=True,\n",
    "    experiment_id=\"average\",\n",
    "    # Time binning info\n",
    "    bin_index=2,  \n",
    "    bin_size=60,\n",
    "    samples_max=250,\n",
    "    # ROI arguments\n",
    "    roi_number=1,\n",
    "    animals_in_roi=\"B\",\n",
    ")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f00af427",
   "metadata": {},
   "source": [
    "As we can see, the average of our ROIs is a bit to the left of the average arena. This is what can happen if the ROIs are not all clicked individually for all videos as the arena itself is not at the exact same position in each video."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4516b37b",
   "metadata": {},
   "source": [
    "Next, just to understand the ROI funtionality a bit better, we will have a look at two special cases: \n",
    "* In the first case we extract the **nose positions** of the black mouse whilst this **black mouse was inside of ROI 3**. As we can see, some activity is detected outside of the ROI. This happens because the center position of the mouse is used to determine if the mouse is inside of the ROI. Hence, a Mouse standing just on the edge of a ROI and looking outside is still technically \"inside\" of that ROI.\n",
    "* In the second example we track the **center of the black mouse** for all frames during which the **white mouse is inside of ROI 3**. As this doesn't apply any restrictions to the position of the black mosue, we will see activity in the whole arena."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a6e005b8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33m\n",
      "Info! Selected range exceeds 250 samples and has been downsampled by a factor of approx. 5\n",
      "To avoid this, increase 'samples_max'. This will also result in increased computation time\u001b[0m\n",
      "\u001b[33m\n",
      "Info! Selected range exceeds 250 samples and has been downsampled by a factor of approx. 5\n",
      "To avoid this, increase 'samples_max'. This will also result in increased computation time\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"notebook\")\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6))\n",
    "\n",
    "# Nose based plot\n",
    "deepof.visuals.plot_heatmaps(\n",
    "    my_deepof_project_with_rois, \n",
    "    [\"B_Nose\"],\n",
    "    center=\"arena\", \n",
    "    exp_condition=\"CSDS\",\n",
    "    condition_value=\"Nonstressed\",\n",
    "    ax=ax1,\n",
    "    show=False,\n",
    "    display_arena=True,\n",
    "    experiment_id=\"average\",\n",
    "    # Time binning info\n",
    "    bin_index=2,  \n",
    "    bin_size=60,\n",
    "    samples_max=250,\n",
    "    # ROI arguments\n",
    "    roi_number=3,\n",
    "    animals_in_roi=\"B\",\n",
    ")\n",
    "\n",
    "# Center based plot\n",
    "deepof.visuals.plot_heatmaps(\n",
    "    my_deepof_project_with_rois,\n",
    "    [\"B_Center\"],\n",
    "    center=\"arena\", \n",
    "    exp_condition=\"CSDS\",\n",
    "    condition_value=\"Nonstressed\", \n",
    "    ax=ax2,\n",
    "    show=False,\n",
    "    display_arena=True,\n",
    "    experiment_id=\"average\",\n",
    "    # Time binning info\n",
    "    bin_index=2,  \n",
    "    bin_size=60,\n",
    "    samples_max=250,\n",
    "    # ROI arguments\n",
    "    roi_number=3,\n",
    "    animals_in_roi=\"W\",\n",
    ")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f5bbd89",
   "metadata": {},
   "source": [
    "Per default the position of the \"Center\"-bodypart of the mouse determines if it is inside of the ROI or outside of it. This can also be adjusted by using a different bodypart or a list of bodyparts instead. In case of a list a mouse will only count as \"inside\" of a ROI if all given bodyparts are inside of the ROI at the same time. If all (not excluded) bodyparts of the mouse should be counted, the keyword \"all\" can be used: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b22cc34c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33m\n",
      "Info! Selected range exceeds 250 samples and has been downsampled by a factor of approx. 5\n",
      "To avoid this, increase 'samples_max'. This will also result in increased computation time\u001b[0m\n",
      "\u001b[33m\n",
      "Info! Selected range exceeds 250 samples and has been downsampled by a factor of approx. 5\n",
      "To avoid this, increase 'samples_max'. This will also result in increased computation time\u001b[0m\n",
      "\u001b[33m\n",
      "Info! Selected range exceeds 250 samples and has been downsampled by a factor of approx. 5\n",
      "To avoid this, increase 'samples_max'. This will also result in increased computation time\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"notebook\")\n",
    "\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(12, 4))\n",
    "\n",
    "# Black mouse is in ROI if it's Center is inside of the ROI (default)\n",
    "deepof.visuals.plot_heatmaps(\n",
    "    my_deepof_project_with_rois, \n",
    "    [\"B_Center\"],\n",
    "    center=\"arena\", \n",
    "    exp_condition=\"CSDS\",\n",
    "    condition_value=\"Nonstressed\",\n",
    "    ax=ax1,\n",
    "    show=False,\n",
    "    display_arena=True,\n",
    "    experiment_id=\"average\",\n",
    "    # Time binning info\n",
    "    bin_index=2,  \n",
    "    bin_size=60,\n",
    "    samples_max=250,\n",
    "    # ROI arguments\n",
    "    roi_number=3,\n",
    "    animals_in_roi=\"B\",\n",
    "    in_roi_criterion=\"Center\",\n",
    ")\n",
    "\n",
    "# Black mouse is in ROI if it's Nose and ears is inside of the ROI\n",
    "deepof.visuals.plot_heatmaps(\n",
    "    my_deepof_project_with_rois, \n",
    "    [\"B_Center\"],\n",
    "    center=\"arena\", \n",
    "    exp_condition=\"CSDS\",\n",
    "    condition_value=\"Nonstressed\",\n",
    "    ax=ax2,\n",
    "    show=False,\n",
    "    display_arena=True,\n",
    "    experiment_id=\"average\",\n",
    "    # Time binning info\n",
    "    bin_index=2,  \n",
    "    bin_size=60,\n",
    "    samples_max=250,\n",
    "    # ROI arguments\n",
    "    roi_number=3,\n",
    "    animals_in_roi=\"B\",\n",
    "    in_roi_criterion=[\"Nose\",\"Left_ear\",\"Right_ear\"]\n",
    ")\n",
    "\n",
    "# Black mouse is in ROI if it's Nose is inside of the ROI\n",
    "deepof.visuals.plot_heatmaps(\n",
    "    my_deepof_project_with_rois, \n",
    "    [\"B_Center\"],\n",
    "    center=\"arena\", \n",
    "    exp_condition=\"CSDS\",\n",
    "    condition_value=\"Nonstressed\",\n",
    "    ax=ax3,\n",
    "    show=False,\n",
    "    display_arena=True,\n",
    "    experiment_id=\"average\",\n",
    "    # Time binning info\n",
    "    bin_index=2,  \n",
    "    bin_size=60,\n",
    "    samples_max=250,\n",
    "    # ROI arguments\n",
    "    roi_number=3,\n",
    "    animals_in_roi=\"B\",\n",
    "    in_roi_criterion=\"all\",\n",
    ")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac505206",
   "metadata": {},
   "source": [
    "Now, what we are seeing here is all the center positions of the black mouse dependent on if our selected bodyparts were inside the ROI. Respectively, the second plot covers a slightly larger area, as it includes cases where the black mouse stands outside of the ROI and just sticks it's head in, i.e. it'S Center is outside of the ROI. The third plot covers a slightly smaller area, as absolutely all bodyparts of the black mouse need to be inside of the ROI here."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc33f92c",
   "metadata": {},
   "source": [
    "The roi_functionality works similar for other visualization options, such as the skeleton animation. Here we animate all data for the first 20 seconds (as determined by bin_index and bin_size) during which the black mouse (\"B\") is in the top half of the arena, independent of the position of the white mouse (\"W\")."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "dcfb2eaa",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\">\n",
       "  Your browser does not support the video tag.\n",
       "</video>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython import display\n",
    "\n",
    "video = deepof.visuals.animate_skeleton(\n",
    "    my_deepof_project_with_rois,\n",
    "    experiment_id=\"20191204_Day2_SI_JB08_Test_54\",\n",
    "    bin_index=0,\n",
    "    bin_size=20,\n",
    "    sampling_rate=25,\n",
    "    dpi=60,\n",
    "    roi_number=1,\n",
    "    animals_in_roi=\"B\",\n",
    "    in_roi_criterion=\"Center\",\n",
    ")\n",
    "\n",
    "html = display.HTML(video)\n",
    "display.display(html)\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18013597",
   "metadata": {},
   "source": [
    "If we instead want that both mice are inside of the ROI, we can also simply set animals_in_roi using a list."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "915397cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\">\n",
       "  Your browser does not support the video tag.\n",
       "</video>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython import display\n",
    "\n",
    "video = deepof.visuals.animate_skeleton(\n",
    "    my_deepof_project_with_rois,\n",
    "    experiment_id=\"20191204_Day2_SI_JB08_Test_54\",\n",
    "    bin_index=0,\n",
    "    bin_size=20,\n",
    "    sampling_rate=25,\n",
    "    dpi=60,\n",
    "    roi_number=1,\n",
    "    animals_in_roi=[\"B\", \"W\"],\n",
    ")\n",
    "\n",
    "html = display.HTML(video)\n",
    "display.display(html)\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1984834c",
   "metadata": {},
   "source": [
    "### Plotting with ROIs "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ff7a25f",
   "metadata": {},
   "source": [
    "For most of the other plots we either need supervised or unsupervised annotations, so let's quickly compute just that"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d368119b",
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "data preprocessing            : 100%|██████████| 4/4 [00:41<00:00, 10.45s/step, step=Loading kinematics]\n",
      "supervised annotations        : 100%|██████████| 53/53 [01:28<00:00,  1.67s/table, step=post processing]   \n"
     ]
    }
   ],
   "source": [
    "supervised_annotation = my_deepof_project_with_rois.supervised_annotation()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bae60044",
   "metadata": {},
   "source": [
    "Now we can apply ROIs to Gant plots, Enrichment plots, and more."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9e98b211",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 8))\n",
    "\n",
    "deepof.visuals.plot_gantt(\n",
    "    my_deepof_project_with_rois,\n",
    "    \"20191204_Day2_SI_JB08_Test_54\",\n",
    "    supervised_annotations=supervised_annotation,\n",
    "    roi_number=1,\n",
    "    animals_in_roi=[\"B\",\"W\"],\n",
    ")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e950adab",
   "metadata": {},
   "source": [
    "This Gantt-plot is a lot more sparse than it's pendant in the supervised tutorial, which is expected, as we only include frames during which both mice are in the upper half of the arena."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6567189",
   "metadata": {},
   "source": [
    "Some plots like plot_enrichment have an additional roi setting specifically for supervised annotations. \n",
    "* **The roi_mode is always set to \"mousewise\" as a default**. This means that the ROIs behave exactly as in all examples before, occuring behaviors are only included if the animals given in animals_in_roi were inside of the ROI during that time. If no animals_in_roi input is explicietly given, all available animals need to be inside of the ROI.  \n",
    "* If the roi_mode is set to \"behaviorwise\" instead, the animals_in_roi input is ignored. Now all behaviors are included during which the mice taking part in that behavior were inside of the ROI. This means that for e.g. B_immobility it is only relevant that the black mouse was inside of the ROI during detection. For W_immobility only the white mouse needs to be inside of the ROI and for paired behaviors, such as W_B_following, both mice need to be inside of the ROI."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a1332213",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 10))\n",
    "\n",
    "deepof.visuals.plot_enrichment(\n",
    "    my_deepof_project_with_rois,\n",
    "    supervised_annotations=supervised_annotation,\n",
    "    add_stats=\"Mann-Whitney\",\n",
    "    plot_speed=False,\n",
    "    roi_number = 1,\n",
    "    roi_mode = \"mousewise\", \n",
    "    animals_in_roi=[\"B\",\"W\"],\n",
    "    ax = ax1,\n",
    ")\n",
    "\n",
    "deepof.visuals.plot_enrichment(\n",
    "    my_deepof_project_with_rois,\n",
    "    supervised_annotations=supervised_annotation,\n",
    "    add_stats=\"Mann-Whitney\",\n",
    "    plot_speed=False,\n",
    "    roi_number = 1,\n",
    "    roi_mode = \"behaviorwise\",\n",
    "    ax = ax2,\n",
    ")\n",
    "    \n",
    "plt.tight_layout()    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "450bdcc2",
   "metadata": {},
   "source": [
    "Other plot functions, such as plot_transitions, plot_stationary_entropy, plot_embeddings or plot_behavior_trends as well as export_annotated_video also support the roi functionality. Besides applying ROIs on the existing plotting functions, there is also specific ROI-related information that can be visualized."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3f6adf2",
   "metadata": {},
   "source": [
    "### ROI specific plots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d42904be",
   "metadata": {},
   "source": [
    "The function \"plot_mouse_roi_interaction\" allows the user to visualize the distances different mice from different ROIs have. It works analogously to plot_behavior_trends (see [Supervised tutorial](https://deepof.readthedocs.io/en/latest/tutorial_notebooks/deepof_supervised_tutorial.html)) by showing the average distance for chosen time bins of given mouse bodyparts to a given ROI. If more than one bodypart is given, the distance to the bodypart closest to the ROI is counted. With the call below we evaluate the distance of the nose of the black mouse to ROI 3 (the inner arena circle) for 20 time bins accross teh signal, compairing the CSDS conditions. Note that the distance is ignored if the mouse bodypart is inside of the ROI.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ad7a0c16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "deepof.visuals.plot_mouse_roi_interaction(\n",
    "    my_deepof_project_with_rois,\n",
    "    bodyparts = [\"B_Nose\"],\n",
    "    roi_number= 3,\n",
    "    N_time_bins=20,\n",
    "    mode=\"distance\",\n",
    "    exp_condition=\"CSDS\",\n",
    ")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "935e1be8",
   "metadata": {},
   "source": [
    "As we can see there is not much of a difference, only the nose of the black mouse might, on average, be slightly closer to the ROI (if the mouse is not inside the ROI). This seems odd at first, as we also know that the stressed mice in general avoid the middle of the arena. But there is an explanation for this. Now, if we switch to the \"field of view\" (i.e. \"fov\") mode and sleect an animal id instead, we can now visualize how long roi 3 was in the field of view of the black mouse for the stressed and non-stressed case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4afdc2c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'deepOF - fov-plot for roi 3'}, xlabel='Time Bins', ylabel='roi 3 is in view in % of mouse B'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deepof.visuals.plot_mouse_roi_interaction(\n",
    "    my_deepof_project_with_rois,\n",
    "    animal_id = \"B\",\n",
    "    roi_number= 3,\n",
    "    N_time_bins=20,\n",
    "    mode=\"fov\",\n",
    "    exp_condition=\"CSDS\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9aaef09",
   "metadata": {},
   "source": [
    "With this we now clearly see that the stressed mice were looking more often towards ROI 3, i.e. the center of the arena, especially towards the beginning of the experiment. This makes sense, as a stressed mouse might be more anxious about keeping an eye on the dominant mouse. The direction in which the mouse is looking is likely also the reason for the slight difference in nose distances."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5411eef6",
   "metadata": {},
   "source": [
    "Additionally, the plotted data can be returned directly by using the function return_mouse_roi_interaction. It uses mostly the same input options as the plot function and returns two tables per default"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f9ddd3aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "binned_effect_sizes_df, binned_group_df = deepof.visuals.return_mouse_roi_interaction(\n",
    "    my_deepof_project_with_rois,\n",
    "    animal_id = \"B\",\n",
    "    roi_number= 3,\n",
    "    N_time_bins=20,\n",
    "    mode=\"fov\",\n",
    "    exp_condition=\"CSDS\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "315f4643",
   "metadata": {},
   "source": [
    "binned_effect_sizes_df contains all plotted information including effect sizes. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "da4e857f",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time_bin</th>\n",
       "      <th>Absolute_Cohens_d</th>\n",
       "      <th>Effect_Size_Category</th>\n",
       "      <th>bin_means_Nonstressed</th>\n",
       "      <th>bin_sem_Nonstressed</th>\n",
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       "      <th>0</th>\n",
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       "      <td>0.020562</td>\n",
       "      <td>0.846828</td>\n",
       "      <td>0.019887</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1.641865</td>\n",
       "      <td>3</td>\n",
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       "      <td>0.791246</td>\n",
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       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1.555294</td>\n",
       "      <td>3</td>\n",
       "      <td>0.529122</td>\n",
       "      <td>0.026582</td>\n",
       "      <td>0.752996</td>\n",
       "      <td>0.029172</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>1.863716</td>\n",
       "      <td>3</td>\n",
       "      <td>0.471120</td>\n",
       "      <td>0.021082</td>\n",
       "      <td>0.723351</td>\n",
       "      <td>0.030317</td>\n",
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       "      <th>4</th>\n",
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       "      <td>0.897202</td>\n",
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       "      <td>0.026131</td>\n",
       "      <td>0.667511</td>\n",
       "      <td>0.033834</td>\n",
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       "      <th>5</th>\n",
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       "      <td>0.023123</td>\n",
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       "      <th>6</th>\n",
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       "      <td>1.995586</td>\n",
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       "      <td>0.407317</td>\n",
       "      <td>0.024271</td>\n",
       "      <td>0.673574</td>\n",
       "      <td>0.027347</td>\n",
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       "      <th>7</th>\n",
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       "      <td>1.040807</td>\n",
       "      <td>3</td>\n",
       "      <td>0.429874</td>\n",
       "      <td>0.035301</td>\n",
       "      <td>0.597100</td>\n",
       "      <td>0.026862</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>1.373401</td>\n",
       "      <td>3</td>\n",
       "      <td>0.418158</td>\n",
       "      <td>0.023645</td>\n",
       "      <td>0.613590</td>\n",
       "      <td>0.030877</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>1.180728</td>\n",
       "      <td>3</td>\n",
       "      <td>0.428277</td>\n",
       "      <td>0.030910</td>\n",
       "      <td>0.627180</td>\n",
       "      <td>0.034308</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>1.120252</td>\n",
       "      <td>3</td>\n",
       "      <td>0.400932</td>\n",
       "      <td>0.032131</td>\n",
       "      <td>0.594618</td>\n",
       "      <td>0.034868</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>0.859580</td>\n",
       "      <td>3</td>\n",
       "      <td>0.427903</td>\n",
       "      <td>0.036961</td>\n",
       "      <td>0.590536</td>\n",
       "      <td>0.036547</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>0.919912</td>\n",
       "      <td>3</td>\n",
       "      <td>0.425534</td>\n",
       "      <td>0.027857</td>\n",
       "      <td>0.574910</td>\n",
       "      <td>0.034599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>1.346581</td>\n",
       "      <td>3</td>\n",
       "      <td>0.407891</td>\n",
       "      <td>0.032162</td>\n",
       "      <td>0.645142</td>\n",
       "      <td>0.036020</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
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       "      <td>0.795597</td>\n",
       "      <td>2</td>\n",
       "      <td>0.451670</td>\n",
       "      <td>0.026151</td>\n",
       "      <td>0.603879</td>\n",
       "      <td>0.045010</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>1.127227</td>\n",
       "      <td>3</td>\n",
       "      <td>0.451806</td>\n",
       "      <td>0.034309</td>\n",
       "      <td>0.653350</td>\n",
       "      <td>0.035108</td>\n",
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       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>0.458690</td>\n",
       "      <td>1</td>\n",
       "      <td>0.464717</td>\n",
       "      <td>0.038098</td>\n",
       "      <td>0.557228</td>\n",
       "      <td>0.040140</td>\n",
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       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>1.025630</td>\n",
       "      <td>3</td>\n",
       "      <td>0.399075</td>\n",
       "      <td>0.036809</td>\n",
       "      <td>0.583382</td>\n",
       "      <td>0.033038</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>0.968263</td>\n",
       "      <td>3</td>\n",
       "      <td>0.439136</td>\n",
       "      <td>0.042203</td>\n",
       "      <td>0.615334</td>\n",
       "      <td>0.027506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>0.208054</td>\n",
       "      <td>1</td>\n",
       "      <td>0.495226</td>\n",
       "      <td>0.034547</td>\n",
       "      <td>0.533786</td>\n",
       "      <td>0.037289</td>\n",
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      ],
      "text/plain": [
       "    time_bin  Absolute_Cohens_d  Effect_Size_Category  bin_means_Nonstressed  \\\n",
       "0          0           2.147370                     3               0.623332   \n",
       "1          1           1.641865                     3               0.539462   \n",
       "2          2           1.555294                     3               0.529122   \n",
       "3          3           1.863716                     3               0.471120   \n",
       "4          4           0.897202                     3               0.527192   \n",
       "5          5           1.652882                     3               0.455210   \n",
       "6          6           1.995586                     3               0.407317   \n",
       "7          7           1.040807                     3               0.429874   \n",
       "8          8           1.373401                     3               0.418158   \n",
       "9          9           1.180728                     3               0.428277   \n",
       "10        10           1.120252                     3               0.400932   \n",
       "11        11           0.859580                     3               0.427903   \n",
       "12        12           0.919912                     3               0.425534   \n",
       "13        13           1.346581                     3               0.407891   \n",
       "14        14           0.795597                     2               0.451670   \n",
       "15        15           1.127227                     3               0.451806   \n",
       "16        16           0.458690                     1               0.464717   \n",
       "17        17           1.025630                     3               0.399075   \n",
       "18        18           0.968263                     3               0.439136   \n",
       "19        19           0.208054                     1               0.495226   \n",
       "\n",
       "    bin_sem_Nonstressed  bin_means_Stressed  bin_sem_Stressed  \n",
       "0              0.020562            0.846828          0.019887  \n",
       "1              0.018466            0.791246          0.037320  \n",
       "2              0.026582            0.752996          0.029172  \n",
       "3              0.021082            0.723351          0.030317  \n",
       "4              0.026131            0.667511          0.033834  \n",
       "5              0.028639            0.675814          0.023123  \n",
       "6              0.024271            0.673574          0.027347  \n",
       "7              0.035301            0.597100          0.026862  \n",
       "8              0.023645            0.613590          0.030877  \n",
       "9              0.030910            0.627180          0.034308  \n",
       "10             0.032131            0.594618          0.034868  \n",
       "11             0.036961            0.590536          0.036547  \n",
       "12             0.027857            0.574910          0.034599  \n",
       "13             0.032162            0.645142          0.036020  \n",
       "14             0.026151            0.603879          0.045010  \n",
       "15             0.034309            0.653350          0.035108  \n",
       "16             0.038098            0.557228          0.040140  \n",
       "17             0.036809            0.583382          0.033038  \n",
       "18             0.042203            0.615334          0.027506  \n",
       "19             0.034547            0.533786          0.037289  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "binned_effect_sizes_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9d04bde",
   "metadata": {},
   "source": [
    "And binned_group_df contains the group and binning information for all included experiments and experimental conditions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a7861773",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "      time_bin  bin_length exp_condition       fov\n",
       "0            0         730   Nonstressed  0.491108\n",
       "1            1         730   Nonstressed  0.522222\n",
       "2            2         730   Nonstressed  0.678977\n",
       "3            3         730   Nonstressed  0.627907\n",
       "4            4         730   Nonstressed  0.745554\n",
       "...        ...         ...           ...       ...\n",
       "1055        15         730      Stressed  0.807114\n",
       "1056        16         730      Stressed  0.683562\n",
       "1057        17         730      Stressed  0.567308\n",
       "1058        18         730      Stressed  0.484225\n",
       "1059        19         730      Stressed  0.834247\n",
       "\n",
       "[1060 rows x 4 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
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   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0fb40a8",
   "metadata": {},
   "source": [
    "Alternatively, raw data of only field of view or distance information can be directly retrieved for all experimental conditions, ignoring all binning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b89012c0",
   "metadata": {},
   "outputs": [
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       "</table>\n",
       "<p>15001 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       20191203_Day1_SI_JB08_Test_7  20191203_Day1_SI_JB08_Test_8  \\\n",
       "0                               1.0                           0.0   \n",
       "1                               1.0                           0.0   \n",
       "2                               1.0                           0.0   \n",
       "3                               1.0                           0.0   \n",
       "4                               1.0                           0.0   \n",
       "...                             ...                           ...   \n",
       "14996                           1.0                           0.0   \n",
       "14997                           1.0                           0.0   \n",
       "14998                           NaN                           NaN   \n",
       "14999                           NaN                           NaN   \n",
       "15000                           NaN                           NaN   \n",
       "\n",
       "       20191203_Day1_SI_JB08_Test_13  20191203_Day1_SI_JB08_Test_14  \\\n",
       "0                                1.0                            1.0   \n",
       "1                                1.0                            1.0   \n",
       "2                                1.0                            1.0   \n",
       "3                                1.0                            1.0   \n",
       "4                                1.0                            1.0   \n",
       "...                              ...                            ...   \n",
       "14996                            1.0                            NaN   \n",
       "14997                            NaN                            NaN   \n",
       "14998                            NaN                            NaN   \n",
       "14999                            NaN                            NaN   \n",
       "15000                            NaN                            NaN   \n",
       "\n",
       "       20191203_Day1_SI_JB08_Test_23  20191203_Day1_SI_JB08_Test_24  \\\n",
       "0                                1.0                            1.0   \n",
       "1                                1.0                            1.0   \n",
       "2                                1.0                            1.0   \n",
       "3                                1.0                            1.0   \n",
       "4                                1.0                            1.0   \n",
       "...                              ...                            ...   \n",
       "14996                            0.0                            0.0   \n",
       "14997                            NaN                            NaN   \n",
       "14998                            NaN                            NaN   \n",
       "14999                            NaN                            NaN   \n",
       "15000                            NaN                            NaN   \n",
       "\n",
       "       20191203_Day1_SI_JB08_Test_29  20191203_Day1_SI_JB08_Test_30  \\\n",
       "0                                1.0                            1.0   \n",
       "1                                1.0                            1.0   \n",
       "2                                1.0                            1.0   \n",
       "3                                1.0                            1.0   \n",
       "4                                1.0                            1.0   \n",
       "...                              ...                            ...   \n",
       "14996                            1.0                            0.0   \n",
       "14997                            1.0                            0.0   \n",
       "14998                            1.0                            0.0   \n",
       "14999                            1.0                            0.0   \n",
       "15000                            NaN                            NaN   \n",
       "\n",
       "       20191203_Day1_SI_JB08_Test_39  20191203_Day1_SI_JB08_Test_40  ...  \\\n",
       "0                                0.0                            0.0  ...   \n",
       "1                                0.0                            0.0  ...   \n",
       "2                                0.0                            0.0  ...   \n",
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       "4                                0.0                            0.0  ...   \n",
       "...                              ...                            ...  ...   \n",
       "14996                            0.0                            1.0  ...   \n",
       "14997                            NaN                            1.0  ...   \n",
       "14998                            NaN                            NaN  ...   \n",
       "14999                            NaN                            NaN  ...   \n",
       "15000                            NaN                            NaN  ...   \n",
       "\n",
       "       20191204_Day2_SI_JB08_Test_24  20191204_Day2_SI_JB08_Test_30  \\\n",
       "0                                1.0                            NaN   \n",
       "1                                1.0                            NaN   \n",
       "2                                1.0                            NaN   \n",
       "3                                1.0                            NaN   \n",
       "4                                1.0                            NaN   \n",
       "...                              ...                            ...   \n",
       "14996                            0.0                            0.0   \n",
       "14997                            0.0                            NaN   \n",
       "14998                            NaN                            NaN   \n",
       "14999                            NaN                            NaN   \n",
       "15000                            NaN                            NaN   \n",
       "\n",
       "       20191204_Day2_SI_JB08_Test_39  20191204_Day2_SI_JB08_Test_40  \\\n",
       "0                                1.0                            1.0   \n",
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       "4                                1.0                            1.0   \n",
       "...                              ...                            ...   \n",
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       "14997                            0.0                            NaN   \n",
       "14998                            0.0                            NaN   \n",
       "14999                            0.0                            NaN   \n",
       "15000                            NaN                            NaN   \n",
       "\n",
       "       20191204_Day2_SI_JB08_Test_45  20191204_Day2_SI_JB08_Test_46  \\\n",
       "0                                1.0                            1.0   \n",
       "1                                1.0                            1.0   \n",
       "2                                1.0                            1.0   \n",
       "3                                1.0                            1.0   \n",
       "4                                1.0                            1.0   \n",
       "...                              ...                            ...   \n",
       "14996                            0.0                            1.0   \n",
       "14997                            0.0                            1.0   \n",
       "14998                            0.0                            NaN   \n",
       "14999                            NaN                            NaN   \n",
       "15000                            NaN                            NaN   \n",
       "\n",
       "       20191204_Day2_SI_JB08_Test_55  20191204_Day2_SI_JB08_Test_56  \\\n",
       "0                                0.0                            1.0   \n",
       "1                                0.0                            1.0   \n",
       "2                                0.0                            1.0   \n",
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       "4                                0.0                            1.0   \n",
       "...                              ...                            ...   \n",
       "14996                            1.0                            1.0   \n",
       "14997                            1.0                            1.0   \n",
       "14998                            1.0                            NaN   \n",
       "14999                            NaN                            NaN   \n",
       "15000                            NaN                            NaN   \n",
       "\n",
       "       20191204_Day2_SI_JB08_Test_61  20191204_Day2_SI_JB08_Test_62  \n",
       "0                                1.0                            1.0  \n",
       "1                                1.0                            1.0  \n",
       "2                                1.0                            1.0  \n",
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       "4                                1.0                            1.0  \n",
       "...                              ...                            ...  \n",
       "14996                            0.0                            0.0  \n",
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       "14998                            0.0                            NaN  \n",
       "14999                            NaN                            NaN  \n",
       "15000                            NaN                            NaN  \n",
       "\n",
       "[15001 rows x 53 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deepof.visuals.return_mouse_roi_interaction(\n",
    "    my_deepof_project_with_rois,\n",
    "    animal_id = \"B\",\n",
    "    roi_number= 3,\n",
    "    N_time_bins=20,\n",
    "    mode=\"fov\",\n",
    "    exp_condition=\"CSDS\",\n",
    "    get_raw_data=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ba42806",
   "metadata": {},
   "source": [
    "Analogously ROIs can also be applied to other data sources."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b50ed316",
   "metadata": {},
   "source": [
    "### Extract data directly using ROIs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "201e9096",
   "metadata": {},
   "source": [
    "Plotting all of this may look nice, but maybe you want to create your own, even nicer plot. For this we have various ways to extract data directly after ROI application\n",
    "\n",
    "Extracting coordinates works exactly as described in the [preprocessing tutorial](https://deepof.readthedocs.io/en/latest/tutorial_notebooks/deepof_preprocessing_tutorial.html). It only requires the addition of the roi_number you want to use and the animals that should be inside of that ROI. Aditonally you can also set a in_roi_criterion just as you can for teh plots. All frames during which these conditions were not fulfilled will be set to NaN."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "117a12e0",
   "metadata": {},
   "outputs": [
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       "      <td>161.780679</td>\n",
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       "    <tr>\n",
       "      <th>00:00:00.080005333</th>\n",
       "      <td>178.695067</td>\n",
       "      <td>150.903525</td>\n",
       "      <td>178.133481</td>\n",
       "      <td>164.579831</td>\n",
       "      <td>160.236194</td>\n",
       "      <td>129.369839</td>\n",
       "      <td>162.932410</td>\n",
       "      <td>149.543005</td>\n",
       "      <td>166.288734</td>\n",
       "      <td>115.459213</td>\n",
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       "      <td>175.473650</td>\n",
       "      <td>127.391220</td>\n",
       "      <td>181.920601</td>\n",
       "      <td>137.218331</td>\n",
       "      <td>170.050867</td>\n",
       "      <td>140.762637</td>\n",
       "      <td>190.880247</td>\n",
       "      <td>157.459358</td>\n",
       "      <td>204.986693</td>\n",
       "      <td>161.780679</td>\n",
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       "    <tr>\n",
       "      <th>00:00:00.120008</th>\n",
       "      <td>177.009679</td>\n",
       "      <td>149.650528</td>\n",
       "      <td>175.106624</td>\n",
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       "      <td>163.807836</td>\n",
       "      <td>124.262824</td>\n",
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       "      <td>112.040097</td>\n",
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       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>00:09:59.799986665</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00:09:59.839989332</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00:09:59.879991999</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00:09:59.919994666</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00:09:59.959997333</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14999 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      B_Center             B_Left_bhip              \\\n",
       "                             x           y           x           y   \n",
       "00:00:00            178.695067  150.903525  178.133481  164.579831   \n",
       "00:00:00.040002666  178.695067  150.903525  178.133481  164.579831   \n",
       "00:00:00.080005333  178.695067  150.903525  178.133481  164.579831   \n",
       "00:00:00.120008     177.009679  149.650528  175.106624  163.666017   \n",
       "00:00:00.160010667  177.767518  147.833830  173.779126  162.437004   \n",
       "...                        ...         ...         ...         ...   \n",
       "00:09:59.799986665         NaN         NaN         NaN         NaN   \n",
       "00:09:59.839989332         NaN         NaN         NaN         NaN   \n",
       "00:09:59.879991999         NaN         NaN         NaN         NaN   \n",
       "00:09:59.919994666         NaN         NaN         NaN         NaN   \n",
       "00:09:59.959997333         NaN         NaN         NaN         NaN   \n",
       "\n",
       "                    B_Left_ear             B_Left_fhip              \\\n",
       "                             x           y           x           y   \n",
       "00:00:00            160.236194  129.369839  162.932410  149.543005   \n",
       "00:00:00.040002666  160.236194  129.369839  162.932410  149.543005   \n",
       "00:00:00.080005333  160.236194  129.369839  162.932410  149.543005   \n",
       "00:00:00.120008     163.807836  124.262824  161.761900  147.278549   \n",
       "00:00:00.160010667  167.520924  121.969513  163.445137  144.056996   \n",
       "...                        ...         ...         ...         ...   \n",
       "00:09:59.799986665         NaN         NaN         NaN         NaN   \n",
       "00:09:59.839989332         NaN         NaN         NaN         NaN   \n",
       "00:09:59.879991999         NaN         NaN         NaN         NaN   \n",
       "00:09:59.919994666         NaN         NaN         NaN         NaN   \n",
       "00:09:59.959997333         NaN         NaN         NaN         NaN   \n",
       "\n",
       "                        B_Nose              ... B_Right_ear              \\\n",
       "                             x           y  ...           x           y   \n",
       "00:00:00            166.288734  115.459213  ...  175.473650  127.391220   \n",
       "00:00:00.040002666  166.288734  115.459213  ...  175.473650  127.391220   \n",
       "00:00:00.080005333  166.288734  115.459213  ...  175.473650  127.391220   \n",
       "00:00:00.120008     174.192032  112.040097  ...  180.079795  125.958622   \n",
       "00:00:00.160010667  179.274246  108.299092  ...  183.599288  123.947488   \n",
       "...                        ...         ...  ...         ...         ...   \n",
       "00:09:59.799986665         NaN         NaN  ...         NaN         NaN   \n",
       "00:09:59.839989332         NaN         NaN  ...         NaN         NaN   \n",
       "00:09:59.879991999         NaN         NaN  ...         NaN         NaN   \n",
       "00:09:59.919994666         NaN         NaN  ...         NaN         NaN   \n",
       "00:09:59.959997333         NaN         NaN  ...         NaN         NaN   \n",
       "\n",
       "                   B_Right_fhip               B_Spine_1              \\\n",
       "                              x           y           x           y   \n",
       "00:00:00             181.920601  137.218331  170.050867  140.762637   \n",
       "00:00:00.040002666   181.920601  137.218331  170.050867  140.762637   \n",
       "00:00:00.080005333   181.920601  137.218331  170.050867  140.762637   \n",
       "00:00:00.120008      184.009635  136.824217  171.210362  138.769813   \n",
       "00:00:00.160010667   186.337662  135.377970  173.565589  136.397291   \n",
       "...                         ...         ...         ...         ...   \n",
       "00:09:59.799986665          NaN         NaN         NaN         NaN   \n",
       "00:09:59.839989332          NaN         NaN         NaN         NaN   \n",
       "00:09:59.879991999          NaN         NaN         NaN         NaN   \n",
       "00:09:59.919994666          NaN         NaN         NaN         NaN   \n",
       "00:09:59.959997333          NaN         NaN         NaN         NaN   \n",
       "\n",
       "                     B_Spine_2             B_Tail_base              \n",
       "                             x           y           x           y  \n",
       "00:00:00            190.880247  157.459358  204.986693  161.780679  \n",
       "00:00:00.040002666  190.880247  157.459358  204.986693  161.780679  \n",
       "00:00:00.080005333  190.880247  157.459358  204.986693  161.780679  \n",
       "00:00:00.120008     188.593896  157.714930  203.863200  162.280499  \n",
       "00:00:00.160010667  187.809489  157.195280  202.295015  162.775274  \n",
       "...                        ...         ...         ...         ...  \n",
       "00:09:59.799986665         NaN         NaN         NaN         NaN  \n",
       "00:09:59.839989332         NaN         NaN         NaN         NaN  \n",
       "00:09:59.879991999         NaN         NaN         NaN         NaN  \n",
       "00:09:59.919994666         NaN         NaN         NaN         NaN  \n",
       "00:09:59.959997333         NaN         NaN         NaN         NaN  \n",
       "\n",
       "[14999 rows x 22 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coords = my_deepof_project_with_rois.get_coords(roi_number=1, animals_in_roi=[\"B\",\"W\"], in_roi_criterion=\"Center\")\n",
    "coords.filter_id(\"B\")['20191204_Day2_SI_JB08_Test_54']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f77bd8b",
   "metadata": {},
   "source": [
    "For merging tables, one should take care to enter the correct arguments in both data retrival function calls. Otherwise missmatches can happen, as in this example, in which different roi numbers were used for the standard coords and distance tables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "630b926a",
   "metadata": {},
   "outputs": [
    {
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       "      <td>...</td>\n",
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       "      <th>00:09:59.799986665</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>239.351756</td>\n",
       "      <td>336.178223</td>\n",
       "      <td>369.570164</td>\n",
       "      <td>1236.107578</td>\n",
       "      <td>338.985792</td>\n",
       "      <td>306.291532</td>\n",
       "      <td>398.589194</td>\n",
       "      <td>1296.123237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00:09:59.839989332</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>225.022660</td>\n",
       "      <td>337.583006</td>\n",
       "      <td>356.664988</td>\n",
       "      <td>1202.726262</td>\n",
       "      <td>339.620050</td>\n",
       "      <td>307.614990</td>\n",
       "      <td>401.612088</td>\n",
       "      <td>1299.472646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00:09:59.879991999</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>254.932272</td>\n",
       "      <td>347.361879</td>\n",
       "      <td>366.539329</td>\n",
       "      <td>1240.353140</td>\n",
       "      <td>339.318562</td>\n",
       "      <td>307.496487</td>\n",
       "      <td>402.713953</td>\n",
       "      <td>1300.378284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00:09:59.919994666</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>254.932272</td>\n",
       "      <td>347.361879</td>\n",
       "      <td>366.539329</td>\n",
       "      <td>1240.353140</td>\n",
       "      <td>339.318562</td>\n",
       "      <td>307.496487</td>\n",
       "      <td>402.713953</td>\n",
       "      <td>1300.378284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>00:09:59.959997333</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>254.932272</td>\n",
       "      <td>347.361879</td>\n",
       "      <td>366.539329</td>\n",
       "      <td>1240.353140</td>\n",
       "      <td>339.318562</td>\n",
       "      <td>307.496487</td>\n",
       "      <td>402.713953</td>\n",
       "      <td>1300.378284</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14999 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    (B_Center, x)  (B_Center, y)  (B_Left_bhip, x)  \\\n",
       "00:00:00               178.695067     150.903525        178.133481   \n",
       "00:00:00.040002666     178.695067     150.903525        178.133481   \n",
       "00:00:00.080005333     178.695067     150.903525        178.133481   \n",
       "00:00:00.120008        177.009679     149.650528        175.106624   \n",
       "00:00:00.160010667     177.767518     147.833830        173.779126   \n",
       "...                           ...            ...               ...   \n",
       "00:09:59.799986665            NaN            NaN               NaN   \n",
       "00:09:59.839989332            NaN            NaN               NaN   \n",
       "00:09:59.879991999            NaN            NaN               NaN   \n",
       "00:09:59.919994666            NaN            NaN               NaN   \n",
       "00:09:59.959997333            NaN            NaN               NaN   \n",
       "\n",
       "                    (B_Left_bhip, y)  (B_Left_ear, x)  (B_Left_ear, y)  \\\n",
       "00:00:00                  164.579831       160.236194       129.369839   \n",
       "00:00:00.040002666        164.579831       160.236194       129.369839   \n",
       "00:00:00.080005333        164.579831       160.236194       129.369839   \n",
       "00:00:00.120008           163.666017       163.807836       124.262824   \n",
       "00:00:00.160010667        162.437004       167.520924       121.969513   \n",
       "...                              ...              ...              ...   \n",
       "00:09:59.799986665               NaN              NaN              NaN   \n",
       "00:09:59.839989332               NaN              NaN              NaN   \n",
       "00:09:59.879991999               NaN              NaN              NaN   \n",
       "00:09:59.919994666               NaN              NaN              NaN   \n",
       "00:09:59.959997333               NaN              NaN              NaN   \n",
       "\n",
       "                    (B_Left_fhip, x)  (B_Left_fhip, y)  (B_Nose, x)  \\\n",
       "00:00:00                  162.932410        149.543005   166.288734   \n",
       "00:00:00.040002666        162.932410        149.543005   166.288734   \n",
       "00:00:00.080005333        162.932410        149.543005   166.288734   \n",
       "00:00:00.120008           161.761900        147.278549   174.192032   \n",
       "00:00:00.160010667        163.445137        144.056996   179.274246   \n",
       "...                              ...               ...          ...   \n",
       "00:09:59.799986665               NaN               NaN          NaN   \n",
       "00:09:59.839989332               NaN               NaN          NaN   \n",
       "00:09:59.879991999               NaN               NaN          NaN   \n",
       "00:09:59.919994666               NaN               NaN          NaN   \n",
       "00:09:59.959997333               NaN               NaN          NaN   \n",
       "\n",
       "                    (B_Nose, y)  ...  (W_Tail_base, x)  (W_Tail_base, y)  \\\n",
       "00:00:00             115.459213  ...        284.276209         81.953327   \n",
       "00:00:00.040002666   115.459213  ...        284.276209         81.953327   \n",
       "00:00:00.080005333   115.459213  ...        284.276209         81.953327   \n",
       "00:00:00.120008      112.040097  ...        293.070473         82.577959   \n",
       "00:00:00.160010667   108.299092  ...        299.036433         86.246318   \n",
       "...                         ...  ...               ...               ...   \n",
       "00:09:59.799986665          NaN  ...               NaN               NaN   \n",
       "00:09:59.839989332          NaN  ...               NaN               NaN   \n",
       "00:09:59.879991999          NaN  ...               NaN               NaN   \n",
       "00:09:59.919994666          NaN  ...               NaN               NaN   \n",
       "00:09:59.959997333          NaN  ...               NaN               NaN   \n",
       "\n",
       "                    B_head_area  B_torso_area  B_back_area  B_full_area  \\\n",
       "00:00:00                    NaN           NaN          NaN          NaN   \n",
       "00:00:00.040002666          NaN           NaN          NaN          NaN   \n",
       "00:00:00.080005333          NaN           NaN          NaN          NaN   \n",
       "00:00:00.120008             NaN           NaN          NaN          NaN   \n",
       "00:00:00.160010667          NaN           NaN          NaN          NaN   \n",
       "...                         ...           ...          ...          ...   \n",
       "00:09:59.799986665   239.351756    336.178223   369.570164  1236.107578   \n",
       "00:09:59.839989332   225.022660    337.583006   356.664988  1202.726262   \n",
       "00:09:59.879991999   254.932272    347.361879   366.539329  1240.353140   \n",
       "00:09:59.919994666   254.932272    347.361879   366.539329  1240.353140   \n",
       "00:09:59.959997333   254.932272    347.361879   366.539329  1240.353140   \n",
       "\n",
       "                    W_head_area  W_torso_area  W_back_area  W_full_area  \n",
       "00:00:00                    NaN           NaN          NaN          NaN  \n",
       "00:00:00.040002666          NaN           NaN          NaN          NaN  \n",
       "00:00:00.080005333          NaN           NaN          NaN          NaN  \n",
       "00:00:00.120008             NaN           NaN          NaN          NaN  \n",
       "00:00:00.160010667          NaN           NaN          NaN          NaN  \n",
       "...                         ...           ...          ...          ...  \n",
       "00:09:59.799986665   338.985792    306.291532   398.589194  1296.123237  \n",
       "00:09:59.839989332   339.620050    307.614990   401.612088  1299.472646  \n",
       "00:09:59.879991999   339.318562    307.496487   402.713953  1300.378284  \n",
       "00:09:59.919994666   339.318562    307.496487   402.713953  1300.378284  \n",
       "00:09:59.959997333   339.318562    307.496487   402.713953  1300.378284  \n",
       "\n",
       "[14999 rows x 52 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_deepof_project_with_rois.get_coords(roi_number=1, animals_in_roi=[\"B\",\"W\"]).merge(my_deepof_project_with_rois.get_areas(roi_number=2, animals_in_roi=[\"B\",\"W\"]))['20191204_Day2_SI_JB08_Test_54']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9506c9b",
   "metadata": {},
   "source": [
    "Similarily, we can also count events using ROIs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "c76ac6e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>B_W_nose2nose</th>\n",
       "      <th>B_W_sidebyside</th>\n",
       "      <th>B_W_sidereside</th>\n",
       "      <th>B_W_nose2tail</th>\n",
       "      <th>W_B_nose2tail</th>\n",
       "      <th>B_W_nose2body</th>\n",
       "      <th>W_B_nose2body</th>\n",
       "      <th>B_W_following</th>\n",
       "      <th>W_B_following</th>\n",
       "      <th>B_climb-arena</th>\n",
       "      <th>...</th>\n",
       "      <th>W_moving</th>\n",
       "      <th>W_sniffing</th>\n",
       "      <th>B_missing</th>\n",
       "      <th>W_missing</th>\n",
       "      <th>B_distance</th>\n",
       "      <th>B_cum-distance</th>\n",
       "      <th>B_speed</th>\n",
       "      <th>W_distance</th>\n",
       "      <th>W_cum-distance</th>\n",
       "      <th>W_speed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_5</th>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_6</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
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       "      <td>3</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_7</th>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>6</td>\n",
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       "      <td>5</td>\n",
       "      <td>3</td>\n",
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       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_8</th>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
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       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
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       "      <td>14</td>\n",
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       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_13</th>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
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       "      <td>3</td>\n",
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       "      <td>0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>20191203_Day1_SI_JB08_Test_14</th>\n",
       "      <td>4</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_15</th>\n",
       "      <td>7</td>\n",
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       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_16</th>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_22</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_23</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_24</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_29</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_30</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_31</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_32</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_37</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>22</td>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_38</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_39</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_40</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>27</td>\n",
       "      <td>66</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_45</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_46</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_47</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_53</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_54</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_55</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191203_Day1_SI_JB08_Test_56</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_6</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_7</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_8</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_13</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_14</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_15</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>14</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_16</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_21</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_22</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_23</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_24</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>26</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_30</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>38</td>\n",
       "      <td>89</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_37</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>22</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_38</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_39</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_40</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_45</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_46</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_47</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_53</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>27</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_54</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>14</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_55</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_56</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_61</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>27</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_62</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>67</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_63</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>51</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20191204_Day2_SI_JB08_Test_64</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>53 rows × 33 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               B_W_nose2nose  B_W_sidebyside  B_W_sidereside  \\\n",
       "20191203_Day1_SI_JB08_Test_5               1               0               0   \n",
       "20191203_Day1_SI_JB08_Test_6               3               0               1   \n",
       "20191203_Day1_SI_JB08_Test_7               1               0               1   \n",
       "20191203_Day1_SI_JB08_Test_8               5               4               1   \n",
       "20191203_Day1_SI_JB08_Test_13              2               0               1   \n",
       "20191203_Day1_SI_JB08_Test_14              4               0               0   \n",
       "20191203_Day1_SI_JB08_Test_15              7               0               0   \n",
       "20191203_Day1_SI_JB08_Test_16              1               0               0   \n",
       "20191203_Day1_SI_JB08_Test_22              1               0               0   \n",
       "20191203_Day1_SI_JB08_Test_23              0               0               0   \n",
       "20191203_Day1_SI_JB08_Test_24              1               0               0   \n",
       "20191203_Day1_SI_JB08_Test_29              4               0               1   \n",
       "20191203_Day1_SI_JB08_Test_30              2               0               1   \n",
       "20191203_Day1_SI_JB08_Test_31              3               0               0   \n",
       "20191203_Day1_SI_JB08_Test_32              0               0               0   \n",
       "20191203_Day1_SI_JB08_Test_37              1               0               0   \n",
       "20191203_Day1_SI_JB08_Test_38              3               0               0   \n",
       "20191203_Day1_SI_JB08_Test_39              1               0               4   \n",
       "20191203_Day1_SI_JB08_Test_40              3               0               3   \n",
       "20191203_Day1_SI_JB08_Test_45              5               2               0   \n",
       "20191203_Day1_SI_JB08_Test_46              1               0               0   \n",
       "20191203_Day1_SI_JB08_Test_47              0               0               0   \n",
       "20191203_Day1_SI_JB08_Test_53              0               0               0   \n",
       "20191203_Day1_SI_JB08_Test_54              4               1               1   \n",
       "20191203_Day1_SI_JB08_Test_55              0               0               0   \n",
       "20191203_Day1_SI_JB08_Test_56              3               0               2   \n",
       "20191204_Day2_SI_JB08_Test_6               0               0               0   \n",
       "20191204_Day2_SI_JB08_Test_7               0               0               0   \n",
       "20191204_Day2_SI_JB08_Test_8               4               0               2   \n",
       "20191204_Day2_SI_JB08_Test_13              3               0               1   \n",
       "20191204_Day2_SI_JB08_Test_14              1               0               0   \n",
       "20191204_Day2_SI_JB08_Test_15              3               0               0   \n",
       "20191204_Day2_SI_JB08_Test_16              4               0               3   \n",
       "20191204_Day2_SI_JB08_Test_21              2               1               2   \n",
       "20191204_Day2_SI_JB08_Test_22              2               3               1   \n",
       "20191204_Day2_SI_JB08_Test_23              1               0               0   \n",
       "20191204_Day2_SI_JB08_Test_24              0               0               0   \n",
       "20191204_Day2_SI_JB08_Test_30              7               0               0   \n",
       "20191204_Day2_SI_JB08_Test_37              1               0               2   \n",
       "20191204_Day2_SI_JB08_Test_38              0               1               2   \n",
       "20191204_Day2_SI_JB08_Test_39              2               1               0   \n",
       "20191204_Day2_SI_JB08_Test_40              0               0               1   \n",
       "20191204_Day2_SI_JB08_Test_45              1               0               0   \n",
       "20191204_Day2_SI_JB08_Test_46              0               0               0   \n",
       "20191204_Day2_SI_JB08_Test_47              2               0               1   \n",
       "20191204_Day2_SI_JB08_Test_53              2               1               2   \n",
       "20191204_Day2_SI_JB08_Test_54              4               0               0   \n",
       "20191204_Day2_SI_JB08_Test_55              0               0               0   \n",
       "20191204_Day2_SI_JB08_Test_56              0               0               0   \n",
       "20191204_Day2_SI_JB08_Test_61              5               0               1   \n",
       "20191204_Day2_SI_JB08_Test_62              4               0               3   \n",
       "20191204_Day2_SI_JB08_Test_63              1               1               0   \n",
       "20191204_Day2_SI_JB08_Test_64              1               1               0   \n",
       "\n",
       "                               B_W_nose2tail  W_B_nose2tail  B_W_nose2body  \\\n",
       "20191203_Day1_SI_JB08_Test_5               0              0              0   \n",
       "20191203_Day1_SI_JB08_Test_6               0              2              3   \n",
       "20191203_Day1_SI_JB08_Test_7               6              1              3   \n",
       "20191203_Day1_SI_JB08_Test_8               8              1             10   \n",
       "20191203_Day1_SI_JB08_Test_13              0              1              4   \n",
       "20191203_Day1_SI_JB08_Test_14              3              0              9   \n",
       "20191203_Day1_SI_JB08_Test_15              0              2              6   \n",
       "20191203_Day1_SI_JB08_Test_16              0              2              1   \n",
       "20191203_Day1_SI_JB08_Test_22              0              0              0   \n",
       "20191203_Day1_SI_JB08_Test_23              7              0              9   \n",
       "20191203_Day1_SI_JB08_Test_24              6              0              8   \n",
       "20191203_Day1_SI_JB08_Test_29              8              6             12   \n",
       "20191203_Day1_SI_JB08_Test_30             16              0             11   \n",
       "20191203_Day1_SI_JB08_Test_31              0              1              2   \n",
       "20191203_Day1_SI_JB08_Test_32              0              0              0   \n",
       "20191203_Day1_SI_JB08_Test_37              0              0              0   \n",
       "20191203_Day1_SI_JB08_Test_38              0              1              1   \n",
       "20191203_Day1_SI_JB08_Test_39              6              4              6   \n",
       "20191203_Day1_SI_JB08_Test_40              4              5              7   \n",
       "20191203_Day1_SI_JB08_Test_45             14              1              9   \n",
       "20191203_Day1_SI_JB08_Test_46              6              0              7   \n",
       "20191203_Day1_SI_JB08_Test_47              0              0              0   \n",
       "20191203_Day1_SI_JB08_Test_53              0              0              0   \n",
       "20191203_Day1_SI_JB08_Test_54              7              0              5   \n",
       "20191203_Day1_SI_JB08_Test_55              8              0              6   \n",
       "20191203_Day1_SI_JB08_Test_56              7              2              8   \n",
       "20191204_Day2_SI_JB08_Test_6               4              0              4   \n",
       "20191204_Day2_SI_JB08_Test_7               0              0              0   \n",
       "20191204_Day2_SI_JB08_Test_8               0              3              5   \n",
       "20191204_Day2_SI_JB08_Test_13              0              1              2   \n",
       "20191204_Day2_SI_JB08_Test_14              0              0              1   \n",
       "20191204_Day2_SI_JB08_Test_15              5              0              9   \n",
       "20191204_Day2_SI_JB08_Test_16              5              2             11   \n",
       "20191204_Day2_SI_JB08_Test_21              8              3             10   \n",
       "20191204_Day2_SI_JB08_Test_22             12              0             14   \n",
       "20191204_Day2_SI_JB08_Test_23              0              0              1   \n",
       "20191204_Day2_SI_JB08_Test_24              0              0              0   \n",
       "20191204_Day2_SI_JB08_Test_30              0              0              3   \n",
       "20191204_Day2_SI_JB08_Test_37              7              3              7   \n",
       "20191204_Day2_SI_JB08_Test_38              6              1              9   \n",
       "20191204_Day2_SI_JB08_Test_39              4              1             11   \n",
       "20191204_Day2_SI_JB08_Test_40              0              0              0   \n",
       "20191204_Day2_SI_JB08_Test_45              0              0              0   \n",
       "20191204_Day2_SI_JB08_Test_46              0              0              1   \n",
       "20191204_Day2_SI_JB08_Test_47              1              0              3   \n",
       "20191204_Day2_SI_JB08_Test_53              4              1              8   \n",
       "20191204_Day2_SI_JB08_Test_54              5              0              8   \n",
       "20191204_Day2_SI_JB08_Test_55              0              0              0   \n",
       "20191204_Day2_SI_JB08_Test_56              0              0              0   \n",
       "20191204_Day2_SI_JB08_Test_61              1              1              5   \n",
       "20191204_Day2_SI_JB08_Test_62              1              1              4   \n",
       "20191204_Day2_SI_JB08_Test_63              7              0              9   \n",
       "20191204_Day2_SI_JB08_Test_64              4              1              4   \n",
       "\n",
       "                               W_B_nose2body  B_W_following  W_B_following  \\\n",
       "20191203_Day1_SI_JB08_Test_5               0              0              1   \n",
       "20191203_Day1_SI_JB08_Test_6               4              0              3   \n",
       "20191203_Day1_SI_JB08_Test_7               2              5              3   \n",
       "20191203_Day1_SI_JB08_Test_8               2              9              1   \n",
       "20191203_Day1_SI_JB08_Test_13              2              3              0   \n",
       "20191203_Day1_SI_JB08_Test_14              1              3              1   \n",
       "20191203_Day1_SI_JB08_Test_15              6              0              1   \n",
       "20191203_Day1_SI_JB08_Test_16              3              0              1   \n",
       "20191203_Day1_SI_JB08_Test_22              1              0              0   \n",
       "20191203_Day1_SI_JB08_Test_23              0              7              0   \n",
       "20191203_Day1_SI_JB08_Test_24              1              6              0   \n",
       "20191203_Day1_SI_JB08_Test_29             10              7              7   \n",
       "20191203_Day1_SI_JB08_Test_30              3             13              3   \n",
       "20191203_Day1_SI_JB08_Test_31              1              0              1   \n",
       "20191203_Day1_SI_JB08_Test_32              0              0              0   \n",
       "20191203_Day1_SI_JB08_Test_37              0              0              1   \n",
       "20191203_Day1_SI_JB08_Test_38              2              0              4   \n",
       "20191203_Day1_SI_JB08_Test_39              3              9              6   \n",
       "20191203_Day1_SI_JB08_Test_40              5              7              5   \n",
       "20191203_Day1_SI_JB08_Test_45              1             14              1   \n",
       "20191203_Day1_SI_JB08_Test_46              1             13              1   \n",
       "20191203_Day1_SI_JB08_Test_47              0              0              0   \n",
       "20191203_Day1_SI_JB08_Test_53              0              0              0   \n",
       "20191203_Day1_SI_JB08_Test_54              1              7              1   \n",
       "20191203_Day1_SI_JB08_Test_55              0              9              0   \n",
       "20191203_Day1_SI_JB08_Test_56              3              3              1   \n",
       "20191204_Day2_SI_JB08_Test_6               0              3              0   \n",
       "20191204_Day2_SI_JB08_Test_7               0              0              2   \n",
       "20191204_Day2_SI_JB08_Test_8               1              0              5   \n",
       "20191204_Day2_SI_JB08_Test_13              3              0              4   \n",
       "20191204_Day2_SI_JB08_Test_14              1              0              1   \n",
       "20191204_Day2_SI_JB08_Test_15              1             13              3   \n",
       "20191204_Day2_SI_JB08_Test_16              6              6              4   \n",
       "20191204_Day2_SI_JB08_Test_21              4             11              3   \n",
       "20191204_Day2_SI_JB08_Test_22              0             13              0   \n",
       "20191204_Day2_SI_JB08_Test_23              2              0              2   \n",
       "20191204_Day2_SI_JB08_Test_24              0              0              2   \n",
       "20191204_Day2_SI_JB08_Test_30              8              0              0   \n",
       "20191204_Day2_SI_JB08_Test_37              4              9              4   \n",
       "20191204_Day2_SI_JB08_Test_38              4              6              3   \n",
       "20191204_Day2_SI_JB08_Test_39              3              6              1   \n",
       "20191204_Day2_SI_JB08_Test_40              0              0              0   \n",
       "20191204_Day2_SI_JB08_Test_45              1              0              0   \n",
       "20191204_Day2_SI_JB08_Test_46              0              0              0   \n",
       "20191204_Day2_SI_JB08_Test_47              2              2              1   \n",
       "20191204_Day2_SI_JB08_Test_53              3              5              2   \n",
       "20191204_Day2_SI_JB08_Test_54              2              5              0   \n",
       "20191204_Day2_SI_JB08_Test_55              0              0              9   \n",
       "20191204_Day2_SI_JB08_Test_56              0              0              0   \n",
       "20191204_Day2_SI_JB08_Test_61              8              0              1   \n",
       "20191204_Day2_SI_JB08_Test_62              4              1              0   \n",
       "20191204_Day2_SI_JB08_Test_63              3              8              3   \n",
       "20191204_Day2_SI_JB08_Test_64              1              5              1   \n",
       "\n",
       "                               B_climb-arena  ...  W_moving  W_sniffing  \\\n",
       "20191203_Day1_SI_JB08_Test_5               0  ...        25          74   \n",
       "20191203_Day1_SI_JB08_Test_6               0  ...        14          31   \n",
       "20191203_Day1_SI_JB08_Test_7               0  ...        11          26   \n",
       "20191203_Day1_SI_JB08_Test_8               0  ...        14          34   \n",
       "20191203_Day1_SI_JB08_Test_13              0  ...        16          30   \n",
       "20191203_Day1_SI_JB08_Test_14              0  ...        22          48   \n",
       "20191203_Day1_SI_JB08_Test_15              0  ...        23          53   \n",
       "20191203_Day1_SI_JB08_Test_16              0  ...        25          59   \n",
       "20191203_Day1_SI_JB08_Test_22              0  ...        28          59   \n",
       "20191203_Day1_SI_JB08_Test_23              0  ...         8          21   \n",
       "20191203_Day1_SI_JB08_Test_24              0  ...         8          23   \n",
       "20191203_Day1_SI_JB08_Test_29              0  ...        15          47   \n",
       "20191203_Day1_SI_JB08_Test_30              0  ...        12          32   \n",
       "20191203_Day1_SI_JB08_Test_31              0  ...         7          16   \n",
       "20191203_Day1_SI_JB08_Test_32              0  ...         0           0   \n",
       "20191203_Day1_SI_JB08_Test_37              0  ...        22          53   \n",
       "20191203_Day1_SI_JB08_Test_38              0  ...        19          51   \n",
       "20191203_Day1_SI_JB08_Test_39              0  ...        12          49   \n",
       "20191203_Day1_SI_JB08_Test_40              0  ...        27          66   \n",
       "20191203_Day1_SI_JB08_Test_45              0  ...        11          31   \n",
       "20191203_Day1_SI_JB08_Test_46              0  ...        19          42   \n",
       "20191203_Day1_SI_JB08_Test_47              0  ...         7          12   \n",
       "20191203_Day1_SI_JB08_Test_53              0  ...        25          47   \n",
       "20191203_Day1_SI_JB08_Test_54              0  ...        19          43   \n",
       "20191203_Day1_SI_JB08_Test_55              0  ...        13          31   \n",
       "20191203_Day1_SI_JB08_Test_56              0  ...        16          51   \n",
       "20191204_Day2_SI_JB08_Test_6               0  ...        15          45   \n",
       "20191204_Day2_SI_JB08_Test_7               0  ...        12          22   \n",
       "20191204_Day2_SI_JB08_Test_8               0  ...        12          48   \n",
       "20191204_Day2_SI_JB08_Test_13              0  ...        15          37   \n",
       "20191204_Day2_SI_JB08_Test_14              0  ...        19          47   \n",
       "20191204_Day2_SI_JB08_Test_15              0  ...        14          32   \n",
       "20191204_Day2_SI_JB08_Test_16              0  ...        11          28   \n",
       "20191204_Day2_SI_JB08_Test_21              0  ...        11          32   \n",
       "20191204_Day2_SI_JB08_Test_22              0  ...        17          45   \n",
       "20191204_Day2_SI_JB08_Test_23              0  ...         8          12   \n",
       "20191204_Day2_SI_JB08_Test_24              0  ...        26          48   \n",
       "20191204_Day2_SI_JB08_Test_30              0  ...        38          89   \n",
       "20191204_Day2_SI_JB08_Test_37              0  ...        22          60   \n",
       "20191204_Day2_SI_JB08_Test_38              0  ...        15          32   \n",
       "20191204_Day2_SI_JB08_Test_39              0  ...        13          29   \n",
       "20191204_Day2_SI_JB08_Test_40              0  ...         3           6   \n",
       "20191204_Day2_SI_JB08_Test_45              0  ...        19          30   \n",
       "20191204_Day2_SI_JB08_Test_46              0  ...        13          26   \n",
       "20191204_Day2_SI_JB08_Test_47              0  ...         6          25   \n",
       "20191204_Day2_SI_JB08_Test_53              0  ...        27          68   \n",
       "20191204_Day2_SI_JB08_Test_54              0  ...        14          42   \n",
       "20191204_Day2_SI_JB08_Test_55              0  ...        11          24   \n",
       "20191204_Day2_SI_JB08_Test_56              0  ...        19          50   \n",
       "20191204_Day2_SI_JB08_Test_61              0  ...        27          65   \n",
       "20191204_Day2_SI_JB08_Test_62              0  ...        28          67   \n",
       "20191204_Day2_SI_JB08_Test_63              0  ...        15          51   \n",
       "20191204_Day2_SI_JB08_Test_64              0  ...        17          43   \n",
       "\n",
       "                               B_missing  W_missing  B_distance  \\\n",
       "20191203_Day1_SI_JB08_Test_5           0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_6           0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_7           0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_8           0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_13          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_14          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_15          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_16          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_22          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_23          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_24          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_29          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_30          0          1         NaN   \n",
       "20191203_Day1_SI_JB08_Test_31          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_32          0          0         0.0   \n",
       "20191203_Day1_SI_JB08_Test_37          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_38          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_39          0          1         NaN   \n",
       "20191203_Day1_SI_JB08_Test_40          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_45          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_46          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_47          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_53          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_54          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_55          0          0         NaN   \n",
       "20191203_Day1_SI_JB08_Test_56          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_6           0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_7           0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_8           0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_13          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_14          0          1         NaN   \n",
       "20191204_Day2_SI_JB08_Test_15          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_16          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_21          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_22          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_23          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_24          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_30          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_37          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_38          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_39          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_40          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_45          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_46          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_47          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_53          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_54          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_55          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_56          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_61          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_62          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_63          0          0         NaN   \n",
       "20191204_Day2_SI_JB08_Test_64          0          0         NaN   \n",
       "\n",
       "                               B_cum-distance  B_speed  W_distance  \\\n",
       "20191203_Day1_SI_JB08_Test_5              NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_6              NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_7              NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_8              NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_13             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_14             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_15             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_16             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_22             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_23             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_24             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_29             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_30             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_31             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_32             0.0      0.0         0.0   \n",
       "20191203_Day1_SI_JB08_Test_37             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_38             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_39             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_40             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_45             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_46             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_47             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_53             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_54             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_55             NaN      NaN         NaN   \n",
       "20191203_Day1_SI_JB08_Test_56             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_6              NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_7              NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_8              NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_13             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_14             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_15             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_16             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_21             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_22             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_23             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_24             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_30             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_37             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_38             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_39             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_40             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_45             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_46             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_47             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_53             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_54             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_55             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_56             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_61             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_62             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_63             NaN      NaN         NaN   \n",
       "20191204_Day2_SI_JB08_Test_64             NaN      NaN         NaN   \n",
       "\n",
       "                               W_cum-distance  W_speed  \n",
       "20191203_Day1_SI_JB08_Test_5              NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_6              NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_7              NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_8              NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_13             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_14             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_15             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_16             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_22             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_23             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_24             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_29             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_30             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_31             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_32             0.0      0.0  \n",
       "20191203_Day1_SI_JB08_Test_37             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_38             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_39             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_40             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_45             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_46             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_47             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_53             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_54             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_55             NaN      NaN  \n",
       "20191203_Day1_SI_JB08_Test_56             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_6              NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_7              NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_8              NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_13             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_14             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_15             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_16             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_21             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_22             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_23             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_24             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_30             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_37             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_38             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_39             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_40             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_45             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_46             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_47             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_53             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_54             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_55             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_56             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_61             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_62             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_63             NaN      NaN  \n",
       "20191204_Day2_SI_JB08_Test_64             NaN      NaN  \n",
       "\n",
       "[53 rows x 33 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deepof.visuals.count_all_events(\n",
    "    my_deepof_project_with_rois,\n",
    "    supervised_annotations=supervised_annotation,\n",
    "    bin_size=60,\n",
    "    bin_index=0,\n",
    "    counting_mode = \"Events\",\n",
    "    roi_number=1,\n",
    "    animals_in_roi=\"B\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c5291a1",
   "metadata": {},
   "source": [
    "### Wrapping up"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b567b11",
   "metadata": {},
   "source": [
    "Thank you for making it until the end. In general ROIs can be applied to most functions for which it makes sense. In future updates we are going to implement some options that will enable automatic ROI creations based on requirements such as \"the inner 70% of the area\". So stay tuned."
   ]
  }
 ],
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