Contextual imputation on time(first/last) features.

src/features/empatica_data_yield.py

@@ -21,9 +21,3 @@ def calculate_empatica_data_yield(features):
     features.drop(empatica_data_yield_cols, axis=1, inplace=True) # In case of if the advanced operations will later not be needed (e.g., weighted average)
 
     return features
-
-    
-
-
-
-

src/features/phone_calls/rapids/main.R

@@ -88,6 +88,14 @@ rapids_features <- function(sensor_data_files, time_segment, provider){
         features <- call_features_of_type(calls_of_type, features_type, call_type, time_segment, requested_features)
         call_features <- merge(call_features, features, all=TRUE)
     }
+
+    # Fill seleted columns with a high number
+    time_cols <- select(call_features, contains("timefirstcall") |  contains("timelastcall")) %>% 
+        colnames(.)
+
+    call_features <- call_features %>% 
+        mutate_at(., time_cols, ~replace(., is.na(.), 1000000))
+
     # Fill NA values with 0
     call_features <- call_features %>% mutate_all(~replace(., is.na(.), 0))
 

src/features/phone_messages/rapids/main.R

@@ -65,6 +65,13 @@ rapids_features <- function(sensor_data_files, time_segment, provider){
         features <- message_features_of_type(messages_of_type, message_type, time_segment, requested_features)
         messages_features <- merge(messages_features, features, all=TRUE)
     }
+    # Fill seleted columns with a high number
+    time_cols <- select(call_features, contains("timefirstmessages") |  contains("timelastmessages")) %>% 
+    colnames(.)
+
+    call_features <- call_features %>% 
+        mutate_at(., time_cols, ~replace(., is.na(.), 1000000))
+    
     # Fill NA values with 0
     messages_features <- messages_features %>% mutate_all(~replace(., is.na(.), 0))
     

src/features/phone_screen/rapids/main.py

@@ -63,6 +63,7 @@ def rapids_features(sensor_data_files, time_segment, provider, filter_data_by_se
 
         if not screen_features.empty:
             screen_features.fillna(value={feature_name: 0 for feature_name in screen_features.columns if not feature_name.startswith(("stdduration", "firstuseafter"))}, inplace=True)
+            screen_features["firstuseafter"] = screen_features["firstuseafter"].fillna(1000000)
             screen_features = screen_features.reset_index()
 
     return screen_features