Merge pull request #95 from MilagrosMarin/element-dlc-test

minor changes to standardize the elements
datajoint · Nov 7, 2023 · ded35b3 · ded35b3
2 parents 1314488 + b33ece9
commit ded35b3
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diff --git a/README.md b/README.md
@@ -18,21 +18,21 @@ tables that can be combined with other Elements to assemble a fully functional p
 
 ## Getting Started
 
-+ Please fork this repository
++ Please fork this repository.
 
-+ Clone the repository to your computer
++ Clone the repository to your computer.
 
   ```bash
   git clone https://github.com/<enter_github_username>/element-deeplabcut
   ```
 
-+ Install with `pip`
++ Install with `pip`:
 
   ```bash
   pip install -e .
   ```
 
-+ [Interactive tutorial on GitHub Codespaces](#interactive-tutorial)
++ [Interactive tutorial on GitHub Codespaces](https://github.com/datajoint/element-deeplabcut#interactive-tutorial)
 
 + [Documentation](https://datajoint.com/docs/elements/element-deeplabcut)
 

diff --git a/element_deeplabcut/__init__.py b/element_deeplabcut/__init__.py
@@ -18,4 +18,4 @@
     "DLC_PROCESSED_DATA_DIR", dj.config["custom"].get("dlc_processed_data_dir", "")
 )
 
-db_prefix = dj.config["custom"].get("database.prefix", "")
+db_prefix = dj.config["custom"].get("database.prefix", "")
diff --git a/notebooks/tutorial.ipynb b/notebooks/tutorial.ipynb
@@ -120,9 +120,12 @@
    "outputs": [],
    "source": [
     "import os\n",
-    "if os.path.basename(os.getcwd())=='notebooks': os.chdir('..')\n",
-    "assert os.path.basename(os.getcwd())=='element-deeplabcut', (\"Please move to the \"\n",
-    "                                                              + \"element directory\")"
+    "\n",
+    "if os.path.basename(os.getcwd()) == \"notebooks\":\n",
+    "    os.chdir(\"..\")\n",
+    "assert os.path.basename(os.getcwd()) == \"element-deeplabcut\", (\n",
+    "    \"Please move to the \" + \"element directory\"\n",
+    ")"
    ]
   },
   {
@@ -201,7 +204,7 @@
     }
    ],
    "source": [
-    "from tutorial_pipeline import lab, subject, session, train, model  "
+    "from tutorial_pipeline import lab, subject, session, train, model"
    ]
   },
   {
@@ -990,10 +993,10 @@
    ],
    "source": [
     "(\n",
-    "    dj.Diagram(subject) \n",
-    "    + dj.Diagram(lab) \n",
-    "    + dj.Diagram(session) \n",
-    "    + dj.Diagram(model) \n",
+    "    dj.Diagram(subject)\n",
+    "    + dj.Diagram(lab)\n",
+    "    + dj.Diagram(session)\n",
+    "    + dj.Diagram(model)\n",
     "    + dj.Diagram(train)\n",
     ")"
    ]
@@ -1274,7 +1277,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "config_file_rel = \"./example_data/inbox/from_top_tracking-DataJoint-2023-10-11/config.yaml\""
+    "config_file_rel = (\n",
+    "    \"./example_data/inbox/from_top_tracking-DataJoint-2023-10-11/config.yaml\"\n",
+    ")"
    ]
   },
   {
@@ -1358,11 +1363,13 @@
     }
    ],
    "source": [
-    "model.Model.insert_new_model(model_name='from_top_tracking_model_test',\n",
-    "                             dlc_config=config_file_rel,\n",
-    "                             shuffle=1,\n",
-    "                             trainingsetindex=0,\n",
-    "                             model_description='Model in example data: from_top_tracking model')"
+    "model.Model.insert_new_model(\n",
+    "    model_name=\"from_top_tracking_model_test\",\n",
+    "    dlc_config=config_file_rel,\n",
+    "    shuffle=1,\n",
+    "    trainingsetindex=0,\n",
+    "    model_description=\"Model in example data: from_top_tracking model\",\n",
+    ")"
    ]
   },
   {
@@ -1668,14 +1675,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#Definition of the dictionary named \"session_keys\"\n",
+    "# Definition of the dictionary named \"session_keys\"\n",
     "session_keys = [\n",
     "    dict(subject=\"subject6\", session_datetime=\"2021-06-02 14:04:22\"),\n",
     "    dict(subject=\"subject6\", session_datetime=\"2021-06-03 14:43:10\"),\n",
     "]\n",
     "\n",
-    "#Insert this dictionary in the Session table\n",
-    "session.Session.insert(session_keys, skip_duplicates=True)\n"
+    "# Insert this dictionary in the Session table\n",
+    "session.Session.insert(session_keys, skip_duplicates=True)"
    ]
   },
   {
@@ -1791,10 +1798,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "recording_key = {'subject': 'subject6',\n",
-    "       'session_datetime': '2021-06-02 14:04:22',\n",
-    "       'recording_id': '1'}\n",
-    "model.VideoRecording.insert1({**recording_key, 'device': 'Camera1'}, skip_duplicates=True)"
+    "recording_key = {\n",
+    "    \"subject\": \"subject6\",\n",
+    "    \"session_datetime\": \"2021-06-02 14:04:22\",\n",
+    "    \"recording_id\": \"1\",\n",
+    "}\n",
+    "model.VideoRecording.insert1(\n",
+    "    {**recording_key, \"device\": \"Camera1\"}, skip_duplicates=True\n",
+    ")"
    ]
   },
   {
@@ -1810,12 +1821,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "video_files = [\"./example_data/inbox/from_top_tracking-DataJoint-2023-10-11/videos/train1.mp4\"]\n",
+    "video_files = [\n",
+    "    \"./example_data/inbox/from_top_tracking-DataJoint-2023-10-11/videos/train1.mp4\"\n",
+    "]\n",
     "\n",
-    "model.VideoRecording.File.insert({\n",
-    "    **recording_key, \n",
-    "    'file_id': v_idx, \n",
-    "    'file_path': Path(f)} for v_idx, f in enumerate(video_files))"
+    "model.VideoRecording.File.insert(\n",
+    "    {**recording_key, \"file_id\": v_idx, \"file_path\": Path(f)}\n",
+    "    for v_idx, f in enumerate(video_files)\n",
+    ")"
    ]
   },
   {
@@ -2054,7 +2067,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "task_key = {**recording_key, 'model_name': 'from_top_tracking_model_test'}"
+    "task_key = {**recording_key, \"model_name\": \"from_top_tracking_model_test\"}"
    ]
   },
   {
@@ -2071,10 +2084,12 @@
    "outputs": [],
    "source": [
     "model.PoseEstimationTask.insert1(\n",
-    "    {**task_key,\n",
-    "     'task_mode': 'load',\n",
-    "     'pose_estimation_output_dir': './example_data/outbox/from_top_tracking-DataJoint-2023-10-11/videos/device_1_recording_1_model_from_top_tracking_100000_maxiters'\n",
-    "     })"
+    "    {\n",
+    "        **task_key,\n",
+    "        \"task_mode\": \"load\",\n",
+    "        \"pose_estimation_output_dir\": \"./example_data/outbox/from_top_tracking-DataJoint-2023-10-11/videos/device_1_recording_1_model_from_top_tracking_100000_maxiters\",\n",
+    "    }\n",
+    ")"
    ]
   },
   {
@@ -2471,7 +2486,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df = (model.PoseEstimation.BodyPartPosition & task_key).fetch(format='frame').reset_index()"
+    "df = (\n",
+    "    (model.PoseEstimation.BodyPartPosition & task_key)\n",
+    "    .fetch(format=\"frame\")\n",
+    "    .reset_index()\n",
+    ")"
    ]
   },
   {
@@ -2836,7 +2855,7 @@
     }
    ],
    "source": [
-    "df = df.explode(['frame_index', 'x_pos', 'y_pos', 'likelihood']).reset_index()\n",
+    "df = df.explode([\"frame_index\", \"x_pos\", \"y_pos\", \"likelihood\"]).reset_index()\n",
     "df"
    ]
   },
@@ -2871,8 +2890,8 @@
    "source": [
     "import matplotlib.pyplot as plt\n",
     "\n",
-    "head_data = df[df['body_part'] == 'head']\n",
-    "tail_data = df[df['body_part'] == 'tailbase']"
+    "head_data = df[df[\"body_part\"] == \"head\"]\n",
+    "tail_data = df[df[\"body_part\"] == \"tailbase\"]"
    ]
   },
   {
@@ -2892,18 +2911,18 @@
     }
    ],
    "source": [
-    "fig, axs = plt.subplots(2,1, figsize=(12, 4))\n",
+    "fig, axs = plt.subplots(2, 1, figsize=(12, 4))\n",
     "\n",
-    "axs[0].set_title('x position - Head pose estimation')\n",
-    "axs[0].plot(head_data['x_pos'], label='x_pos')\n",
-    "axs[0].set_xlabel('time (frames)')\n",
-    "axs[0].set_ylabel('pos (pixels)')\n",
+    "axs[0].set_title(\"x position - Head pose estimation\")\n",
+    "axs[0].plot(head_data[\"x_pos\"], label=\"x_pos\")\n",
+    "axs[0].set_xlabel(\"time (frames)\")\n",
+    "axs[0].set_ylabel(\"pos (pixels)\")\n",
     "axs[0].legend()\n",
     "\n",
-    "axs[1].set_title('y position - Head pose estimation')\n",
-    "axs[1].plot(head_data['y_pos'], label='y_pos')\n",
-    "axs[1].set_xlabel('time (frames)')\n",
-    "axs[1].set_ylabel('pos (pixels)')\n",
+    "axs[1].set_title(\"y position - Head pose estimation\")\n",
+    "axs[1].plot(head_data[\"y_pos\"], label=\"y_pos\")\n",
+    "axs[1].set_xlabel(\"time (frames)\")\n",
+    "axs[1].set_ylabel(\"pos (pixels)\")\n",
     "axs[1].legend()\n",
     "\n",
     "plt.tight_layout()\n",
@@ -2927,17 +2946,17 @@
     }
    ],
    "source": [
-    "fig, axs = plt.subplots(2,1, figsize=(12, 4))\n",
-    "axs[0].set_title('x position - Tailbase pose estimation')\n",
-    "axs[0].plot(head_data['x_pos'], label='x_pos',color='orange')\n",
-    "axs[0].set_xlabel('time (frames)')\n",
-    "axs[0].set_ylabel('pos (pixels)')\n",
+    "fig, axs = plt.subplots(2, 1, figsize=(12, 4))\n",
+    "axs[0].set_title(\"x position - Tailbase pose estimation\")\n",
+    "axs[0].plot(head_data[\"x_pos\"], label=\"x_pos\", color=\"orange\")\n",
+    "axs[0].set_xlabel(\"time (frames)\")\n",
+    "axs[0].set_ylabel(\"pos (pixels)\")\n",
     "axs[0].legend()\n",
     "\n",
-    "axs[1].set_title('y position - Tailbase pose estimation')\n",
-    "axs[1].plot(head_data['y_pos'], label='y_pos',color='orange')\n",
-    "axs[1].set_xlabel('time (frames)')\n",
-    "axs[1].set_ylabel('pos (pixels)')\n",
+    "axs[1].set_title(\"y position - Tailbase pose estimation\")\n",
+    "axs[1].plot(head_data[\"y_pos\"], label=\"y_pos\", color=\"orange\")\n",
+    "axs[1].set_xlabel(\"time (frames)\")\n",
+    "axs[1].set_ylabel(\"pos (pixels)\")\n",
     "axs[1].legend()\n",
     "\n",
     "plt.tight_layout()\n",
@@ -2968,18 +2987,18 @@
     }
    ],
    "source": [
-    "fig, axs = plt.subplots(2,1, figsize=(6,10))\n",
+    "fig, axs = plt.subplots(2, 1, figsize=(6, 10))\n",
     "\n",
-    "axs[0].set_title('Head pose estimation')\n",
-    "axs[0].plot(head_data['x_pos'], head_data['y_pos'],label='head',color='blue')\n",
-    "axs[0].set_xlabel('x position (pixels)')\n",
-    "axs[0].set_ylabel('y position (pixels)')\n",
+    "axs[0].set_title(\"Head pose estimation\")\n",
+    "axs[0].plot(head_data[\"x_pos\"], head_data[\"y_pos\"], label=\"head\", color=\"blue\")\n",
+    "axs[0].set_xlabel(\"x position (pixels)\")\n",
+    "axs[0].set_ylabel(\"y position (pixels)\")\n",
     "axs[0].legend()\n",
     "\n",
-    "axs[1].set_title('Tailbase pose estimation')\n",
-    "axs[1].plot(tail_data['x_pos'], tail_data['y_pos'], label='tailbase',color='orange')\n",
-    "axs[1].set_xlabel('x position (pixels)')\n",
-    "axs[1].set_ylabel('y position (pixels)')\n",
+    "axs[1].set_title(\"Tailbase pose estimation\")\n",
+    "axs[1].plot(tail_data[\"x_pos\"], tail_data[\"y_pos\"], label=\"tailbase\", color=\"orange\")\n",
+    "axs[1].set_xlabel(\"x position (pixels)\")\n",
+    "axs[1].set_ylabel(\"y position (pixels)\")\n",
     "axs[1].legend()\n",
     "\n",
     "plt.tight_layout()\n",