create_features update

create_features.py

@@ -214,34 +214,15 @@ def arg_parser():
     return win_size
 
 if __name__ == '__main__':
-    # window_sizes = [5, 7, 10, 12]
-    # window_sizes = [15, 17, 20]
-    window_sizes = arg_parser()
-    print(window_sizes)
-
+    # TODO
+    window_sizes = [5, 7, 10, 12, 15, 17, 20, 22, 25, 27, 30]
     window_shifts = [0.2, 0.5, 1.0]
     fs = IMU_FS
-    subjects = ['S'+str(i).zfill(2) for i in range(12,31)] # mars13
-    # subjects = ['S'+str(i).zfill(2) for i in range(21,31)] # mars13
-    conditions = ['M', 'R'] + ['L'+str(i) for i in range(0,4)]
-    # conditions = ['R'] + ['L'+str(i) for i in range(0,4)]
-
-    window_size = WINDOW_SIZE
-    window_shift = WINDOW_SHIFT
-
-    tlx_df = pd.read_csv('seated_nasa_tlx.csv', index_col=[0]).T
+    subjects = ['Pilot'+str(i).zfill(2) for i in range(2,4)] # mars13
 
     for window_shift in window_shifts:
         for window_size in window_sizes:
-            func = partial(map_imu_tsfresh_subject,
-                           tlx_df=tlx_df,
-                           conditions=conditions,
+            for subject in subjects:
+                map_imu_tsfresh_subject(subject,
                            window_size=window_size,
                            window_shift=window_shift)
-            # gen = map(func, subjects)
-            # for i, x in enumerate(gen):
-            #     print(i/len(subjects)*100)
-            with Pool(cpu_count()) as p:
-                p.map(func, subjects)
-
-    print("completed for window sizes: ", window_sizes)

regress_rr.py

@@ -589,7 +589,7 @@ def load_and_sync_xsens(subject, sens_list:list=['imu', 'bvp']):
 
     return xsens_df
 
-def load_tsfresh(xsens_df, project_dir,
+def load_tsfresh(xsens_df, home_dir,
                  sens_list:list=['imu', 'bvp'],
                  window_size=12, window_shift=0.2, fs=IMU_FS,
                  overwrite=False, data_cols=None):
@@ -607,13 +607,16 @@ def load_tsfresh(xsens_df, project_dir,
     pd.DataFrame
     """
 
-    # raise NotImplementedError("To be implemented")
+    raise NotImplementedError("To be implemented")
+
+    # make home directory
 
     assert data_cols is not None, "invalid selection for data columns"
     pkl_file = join(project_dir, 'tsfresh.pkl')
     if exists(pkl_file) and not overwrite:
         return pd.read_pickle(pkl_file)
 
+    ipdb.set_trace()
     x_df, y_df = get_df_windows(xsens_df,
                                 df_win_task,
                                 window_size=window_size,