cuda docs

docs/_build/html/doctrees/nbsphinx/nb/advanced_outlier_correction.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "527ac24c",
+   "metadata": {},
+   "source": [
+    "# Advanced outlier correction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ab923d86",
+   "metadata": {},
+   "source": [
+    "Here, we perform location- and movement-based outlier correction that allows different heuristic outlier criteria \n",
+    "for different animals or body-parts. For example, we will correct some outlier body-parts with a heuristic criteria of 4x above the mean movement, and other body-parts with a heuristic critera of 2x above the mean movement. For a scematic describing movement and location-based outlier correcttion, click [HERE](https://github.com/sgoldenlab/simba/blob/master/misc/Outlier_settings.pdf). Use SimBA version > 1.71.4."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "2737ca8c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from simba.outlier_tools.outlier_corrector_movement_advanced import OutlierCorrecterMovementAdvanced\n",
+    "from simba.outlier_tools.outlier_corrector_location_advanced import OutlierCorrecterLocationAdvanced"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "558f834b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# DEFINITIONS\n",
+    "\n",
+    "# The path to your SimBA project project_config.ini file.\n",
+    "CONFIG_PATH='/Users/simon/Desktop/envs/troubleshooting/two_black_animals_14bp/project_folder/project_config.ini'\n",
+    "\n",
+    "#The directory containing the pose-estimation data to detect outliers within.\n",
+    "INPUT_DIR='/Users/simon/Desktop/envs/troubleshooting/two_black_animals_14bp/project_folder/csv/input_csv'\n",
+    "\n",
+    "#If you provide one heuristic multiplier criterion per animal, set type to \"animal\". If you have \n",
+    "# one heuristic multiplier criterion per body part, set type to \"body-part\".\n",
+    "TYPE='animal'\n",
+    "\n",
+    "#If you want to calculate the aggregate animal sizes using the mean or median euclidean lengths in the video. \n",
+    "AGG_METHOD='mean'\n",
+    "\n",
+    "#The body-parts for each animals that you wish to use to calculate the aggregate size of the animals in the videos\n",
+    "CRITERION_BODY_PARTS={'Simon': ['Nose_1', 'Tail_base_1'], 'JJ': ['Nose_2', 'Tail_base_2']}\n",
+    "\n",
+    "# The multiplier criterion for animal.  Here we use one multipler per animal. If you want to use different multiplers for each body-part\n",
+    "# then provide a nested dictyionary, e.g., below. If you are using a nested dictionary and provide different multiplier per body-part, \n",
+    "# remember to set type = 'body-part.'\n",
+    "#SETTINGS = {'Simon': {'Ear_left_1': 1.1, \n",
+    "#                           'Ear_right_1': 5.1, \n",
+    "#                          'Nose_1': 2.1, \n",
+    "#                          'Center_1': 1.5, \n",
+    "#                          'Lat_left_1': 3.1,\n",
+    "#                          'Lat_right_1': 1.9, \n",
+    "#                          'Tail_base_1': 2.3, \n",
+    "#                          'Tail_end_1': 1.4},\n",
+    "#                'JJ': {'Ear_left_2': 1.2, \n",
+    "#                       'Ear_right_2': 1.2, \n",
+    "#                       'Nose_2': 2, \n",
+    "#                       'Center_2': 4.1, \n",
+    "#                       'Lat_left_2': 9,\n",
+    "#                       'Lat_right_2': 1.2, \n",
+    "#                       'Tail_base_2': 1.6, \n",
+    "#                       'Tail_end_2': 2.2}}\n",
+    "SETTINGS={'Simon': 2.1, 'JJ': 3.2}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "bd3325d4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing video Together_1. Video 1/1...\n",
+      "SIMBA COMPLETE: Movement outliers complete for video Together_1. (elapsed time: 0.9181s) \tcomplete\n",
+      "SIMBA COMPLETE: Movement outlier log saved at /Users/simon/Desktop/envs/troubleshooting/two_black_animals_14bp/project_folder/logs/movement_outliers_20230811132623.csv \tcomplete\n",
+      "SIMBA COMPLETE: 1 video(s) corrected for movement outliers. Saved in /Users/simon/Desktop/envs/troubleshooting/two_black_animals_14bp/project_folder/csv/outlier_corrected_movement \tcomplete\n"
+     ]
+    }
+   ],
+   "source": [
+    "#We initialize the advanced outlier movement corrector and run it. The redults will be saved in the \n",
+    "# project_folder/csv/outlier_corrected_movement directory of the SimBA project.\n",
+    "movement_outlier_corrector = OutlierCorrecterMovementAdvanced(config_path=CONFIG_PATH,\n",
+    "                                                              input_dir=INPUT_DIR,\n",
+    "                                                              criterion_body_parts=CRITERION_BODY_PARTS,\n",
+    "                                                              type=TYPE,\n",
+    "                                                              agg_method=AGG_METHOD,\n",
+    "                                                              settings=SETTINGS)\n",
+    "movement_outlier_corrector.run()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "be82c93c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Next, we want to perform location outlier correction. We will perform location outlier correction on the files that \n",
+    "# was processed by the movement outlier corrector above, so we change the input directory to the folder that contains\n",
+    "# those files:\n",
+    "INPUT_DIR='/Users/simon/Desktop/envs/troubleshooting/two_black_animals_14bp/project_folder/csv/outlier_corrected_movement'\n",
+    "\n",
+    "# This time, we will also change the ``settings``, so rather than providing one multiplier per animal, we now provide \n",
+    "# one multiplier per body-part:\n",
+    "SETTINGS = {'Simon': {'Ear_left_1': 1.1, \n",
+    "                      'Ear_right_1': 5.1, \n",
+    "                      'Nose_1': 2.1, \n",
+    "                      'Center_1': 1.5, \n",
+    "                      'Lat_left_1': 3.1,\n",
+    "                      'Lat_right_1': 1.9, \n",
+    "                      'Tail_base_1': 2.3, \n",
+    "                      'Tail_end_1': 1.4},\n",
+    "               'JJ': {'Ear_left_2': 1.2, \n",
+    "                      'Ear_right_2': 1.2, \n",
+    "                      'Nose_2': 2, \n",
+    "                      'Center_2': 4.1, \n",
+    "                      'Lat_left_2': 9,\n",
+    "                      'Lat_right_2': 1.2, \n",
+    "                      'Tail_base_2': 1.6, \n",
+    "                      'Tail_end_2': 2.2}}\n",
+    "TYPE='body-parts'\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "ce9cf9b4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processing video Together_1. Video 1/1...\n",
+      "SIMBA COMPLETE: Location outliers complete for video Together_1. (elapsed time: 1.327s) \tcomplete\n",
+      "SIMBA COMPLETE: Location outlier log saved at /Users/simon/Desktop/envs/troubleshooting/two_black_animals_14bp/project_folder/logs/location_outliers_20230811132629.csv \tcomplete\n",
+      "SIMBA COMPLETE: 1 video(s) corrected for location outliers. Saved in /Users/simon/Desktop/envs/troubleshooting/two_black_animals_14bp/project_folder/csv/outlier_corrected_movement_location \tcomplete\n"
+     ]
+    }
+   ],
+   "source": [
+    "#We initialize the advanced outlier location corrector and run it. The redults will be saved in the \n",
+    "# project_folder/csv/outlier_corrected_movement directory of the SimBA project.\n",
+    "location_outlier_corrector = OutlierCorrecterLocationAdvanced(config_path=CONFIG_PATH,\n",
+    "                                                              input_dir=INPUT_DIR,\n",
+    "                                                              criterion_body_parts=CRITERION_BODY_PARTS,\n",
+    "                                                              type=TYPE,\n",
+    "                                                              agg_method=AGG_METHOD,\n",
+    "                                                              settings=SETTINGS)\n",
+    "location_outlier_corrector.run()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2793415d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
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