Index: trunk/SDToolBox/extract_waves.py
===================================================================
diff -u -r34 -r35
--- trunk/SDToolBox/extract_waves.py	(.../extract_waves.py)	(revision 34)
+++ trunk/SDToolBox/extract_waves.py	(.../extract_waves.py)	(revision 35)
@@ -116,7 +116,7 @@
                         reftime = case_dataset[self.__time_key].units.split(' ')
                         # This is an assumption that all the grids have
                         # the same scale in regards of time.
-                        cases_dict[self.__out_time_key].append(
+                        cases_dict[self.__out_time_key].extend(
                             [datetime.strptime(
                                 reftime[2]+' '+reftime[3],
                                 '%Y-%m-%d %H:%M:%S.%f')
Index: trunk/SDToolBox/data_acquisition.py
===================================================================
diff -u -r34 -r35
--- trunk/SDToolBox/data_acquisition.py	(.../data_acquisition.py)	(revision 34)
+++ trunk/SDToolBox/data_acquisition.py	(.../data_acquisition.py)	(revision 35)
@@ -258,12 +258,12 @@
 
     def __get_time_samples(self):
         time_array = self.__data_dict[self.var_time_key]
-        if not time_array or len(time_array) == 0:
+        if not time_array:
             return 0
-        return sum([len(time) for time in time_array])
+        return len(time_array)
 
     def __get_time_values(self):
-        return self.__data_dict[self.var_time_key][0]
+        return self.__data_dict[self.var_time_key]
 
     def __set_global_data(
             self, netcdf: Dataset, output_format: str, dataset_code: str):
@@ -389,9 +389,12 @@
         # resolution of one second
         time_variable.scale_factor = 1
         # NO scaling when scale_factor is already applied
-        time_variable[:] = [
-            time.total_seconds()
-            for time in time_delta_from_origin]
+        # time_variable[:] = [
+        #     time.total_seconds()
+        #     for time in time_delta_from_origin]
+        time_variable[:] = list(map(
+            lambda t: t.total_seconds(),
+            time_delta_from_origin))
 
         return netcdf