Fix nans (#512)

* change index for start and stop task timestamp

* bug fix

* change delimter type

* increase end index by 2_This change was for Eric to fix the issue he encountered during interpolation._ 

Updates:
1. Made sure all exports use ";" as seperator.
2. Changed index of event markers by -2 before event start and +2 after event ended. 

* update v2 script

human_experiments/lab_software/tomcat-physio-data-extraction/utils/NIRS_filtering.py

@@ -79,7 +79,7 @@ def check_cv(
         list(zip(channels, cv_vals, channel_good_or_bad)),
         columns=["Channels", "coeff_of_var", "status"],
     )
-    df.to_csv(new_csv_file_path + "/" + "NIRS_channel_quality.csv", index=False)
+    df.to_csv(new_csv_file_path + "/" + "NIRS_channel_quality.csv", sep=";",index=False)
 
 
 def filter_NIRS(data):

human_experiments/lab_software/tomcat-physio-data-extraction/utils/create_time_distribution.py

@@ -22,7 +22,7 @@ def utc_time_ns(seconds):
 
 
 def create_time_distribution(data):
-    time_distribution_unix_list.append(temp)
+    # time_distribution_unix_list.append(temp)
     time_distribution_unix_list = data["time_stamps"]
 
     ctime_list = []

human_experiments/lab_software/tomcat-physio-data-extraction/utils/create_write_csv_file.py

@@ -21,7 +21,8 @@ def get_timestamps_from_dict(
     state_end = df_temp.index[
         iloc_idx_end
     ]  # reduce index by 1 as the index sometimes overflows
-    range_ = list(range(state_start, state_end))
+    state_start, state_end = state_start-1, state_end+2 # Increase start and stop state by 1 to avoid NaNs for data extrapolation script. 
+    range_ = list(range(state_start, state_end)) 
     state = [state] * len(range_)
     state = {i: x for i, x in enumerate(state, state_start)}
 
@@ -542,7 +543,7 @@ def dataframe_to_csv(
 
     # Save as CSV file
     if extract_csv == True:
-        df_original.to_csv(new_csv_file_path + ".csv", sep="\t", encoding="utf-8")
+        df_original.to_csv(new_csv_file_path + ".csv", sep=";", encoding="utf-8")
         print(
             colored("[INFO]", "green", attrs=["bold"]),
             colored("Sucessfully generated csv file at", "green", attrs=["bold"]),
@@ -552,7 +553,7 @@ def dataframe_to_csv(
         if bool(filter) == True and stream_type == "NIRS":
             df_final_filtered = filter_NIRS(df_final)
             df_final_filtered.to_csv(
-                new_csv_file_path + "_filtered" + ".csv", sep="\t", encoding="utf-8"
+                new_csv_file_path + "_filtered" + ".csv", sep=";", encoding="utf-8"
             )
             print(
                 colored("[INFO]", "green", attrs=["bold"]),
@@ -567,7 +568,7 @@ def dataframe_to_csv(
         if bool(filter) == True and stream_type == "EEG":
             df_final_filtered = filter_EEG(df_final)
             df_final_filtered.to_csv(
-                new_csv_file_path + "_filtered" + ".csv", sep="\t", encoding="utf-8"
+                new_csv_file_path + "_filtered" + ".csv", sep=";", encoding="utf-8"
             )
             print(
                 colored("[INFO]", "green", attrs=["bold"]),

human_experiments/lab_software/tomcat-physio-data-extraction_v2/utils/label_data.py

@@ -2,6 +2,7 @@ def update_state(block, state, start_time, end_time):
     try:
         start_index = block["unix_time"].searchsorted(start_time)
         end_index = block["unix_time"].searchsorted(end_time)
+        start_index, end_index = start_index-2, end_index+2
         block.loc[start_index:end_index, "event_type"] = state
     except KeyError as e:
         print(f"KeyError: {e} in update_state function")