refactor(script): Add time-domain feature extraction functionality called ExtractTimeFeatures function returning features in {dictionary} that later called in build_features.py. This function will be called for each individual .csv. Each returning value later appended in build_features.py.

This function approach rather than just assigning class ensure the flexibility and enhance maintainability.

code/src/features/time_domain_features.py

@@ -36,6 +36,13 @@ class FeatureExtractor:
             result += f"{feature}: {value:.4f}\n"
         return result
 
+def ExtractTimeFeatures(object):
+    data = pd.read_csv(object, skiprows=1)
+    extractor = FeatureExtractor(data.iloc[:, 1].values) # Assuming the data is in the second column
+    features = extractor.features
+    return features
+    # Save features to a file
+    # np.savez(output_file, **features)
 # Usage
 # Assume you have a CSV file with numerical data in the first column
 # Create an instance of the class and pass the path to your CSV file