Add "corr_method" param to heatmap_features_correlations.py

config.yaml

@@ -208,6 +208,7 @@ HEATMAP_FEATURES_CORRELATIONS:
   PHONE_FEATURES: [accelerometer, activity_recognition, applications_foreground, battery, calls_incoming, calls_missed, calls_outgoing, conversation, light, location_doryab, messages_received, messages_sent, screen]
   FITBIT_FEATURES: [fitbit_heartrate, fitbit_step, fitbit_sleep]
   CORR_THRESHOLD: 0.1
+  CORR_METHOD: "pearson" # choose from {"pearson", "kendall", "spearman"}
 
 HISTOGRAM_VALID_SENSED_HOURS:
   PLOT: False

rules/reports.snakefile

@@ -4,7 +4,8 @@ rule heatmap_features_correlations:
         phone_valid_sensed_days = expand("data/interim/{pid}/phone_valid_sensed_days_{{min_valid_hours_per_day}}h.csv", pid=config["PIDS"])
     params:
         min_rows_ratio = config["HEATMAP_FEATURES_CORRELATIONS"]["MIN_ROWS_RATIO"],
-        corr_threshold = config["HEATMAP_FEATURES_CORRELATIONS"]["CORR_THRESHOLD"] #0.75
+        corr_threshold = config["HEATMAP_FEATURES_CORRELATIONS"]["CORR_THRESHOLD"],
+        corr_method = config["HEATMAP_FEATURES_CORRELATIONS"]["CORR_METHOD"]
     output:
         "reports/data_exploration/{min_valid_hours_per_day}h/heatmap_features_correlations.html"
     script:

src/visualization/heatmap_features_correlations.py

@@ -50,7 +50,7 @@ features = features.loc[features.index.intersection(selected_participants_and_da
 
 # get correlation matrix
 features = features.astype(float)
-corr_matrix = features.corr(min_periods=min_rows_ratio * features.shape[0])
+corr_matrix = features.corr(method=snakemake.params["corr_method"], min_periods=min_rows_ratio * features.shape[0])
 
 # replace correlation coefficients less than corr_threshold with NA
 corr_matrix[(corr_matrix > -corr_threshold) & (corr_matrix < corr_threshold)] = np.nan