Error with recording kp

bazilinskyy · Jan 2, 2025 · 7846509 · 7846509
1 parent 8b652bf
commit 7846509
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Showing 2 changed files with 18 additions and 18 deletions.
diff --git a/trust/analysis/heroku.py b/trust/analysis/heroku.py
@@ -625,7 +625,7 @@ def process_kp(self, filter_length=True):
                                             rt_data.append(row[j])
                                             # record raw value for pp
                                             for rt_bin in range(self.res, video_len + self.res, self.res):
-                                                if rt_bin - self.res < row[0] <= rt_bin:
+                                                if rt_bin - self.res < row[j] <= rt_bin:
                                                     pp_kp.loc[rt_bin, [self.heroku_data.index[row_index]]] = 1
                         # if all data for one video was found, divide them in bins
                         kp = []
@@ -650,7 +650,7 @@ def process_kp(self, filter_length=True):
                         video_kp.append(kp)
                         # store raw data from repetition
                         # todo: fix extra [] added to results
-                        video_kp_raw.append(pp_kp.values.tolist()[0])
+                        video_kp_raw.append(pp_kp.values.tolist())
                         break
             # calculate mean keypresses from all repetitions
             kp_mean = [*map(mean, zip(*video_kp))]

diff --git a/trust/run.py b/trust/run.py
@@ -21,10 +21,10 @@
 # CALC_COORDS = False  # extract points from heroku data
 # UPDATE_MAPPING = True  # update mapping with keypress data
 # SHOW_OUTPUT = True  # should figures be plotted
-# SHOW_OUTPUT_KP = False  # should figures with keypress data be plotted-
-# SHOW_OUTPUT_ST = False  # should figures with stimulus data to be plotted
-# SHOW_OUTPUT_PP = False  # should figures with info about participants
-# SHOW_OUTPUT_ET = False  # should figures for eye tracking
+# SHOW_OUTPUT_KP = False  # should figures with keypress data be plotted
+# SHOW_OUTPUT_ST = False  # should figures with stimulus data be plotted
+# SHOW_OUTPUT_PP = False  # should figures with info about participants be plotted
+# SHOW_OUTPUT_ET = False  # should figures for eye tracking be plotted
 
 # for debugging, skip processing
 SAVE_P = False  # save pickle files with data
@@ -217,28 +217,28 @@
                 #     ttest_signals.append({'signal_1': df.loc['video_' + str(ids[0])]['kp'],
                 #                           'signal_2': df.loc['video_' + str(stim)]['kp'],
                 #                           'paired': True})
-                ttest_signals = [{'signal_1': df.loc['video_' + str(ids[0])]['kp_raw'],  # 0 and 1 = within
-                                  'signal_2': df.loc['video_' + str(ids[1])]['kp_raw'],
+                ttest_signals = [{'signal_1': df.loc['video_' + str(ids[0])]['kp_raw'][0],  # 0 and 1 = within
+                                  'signal_2': df.loc['video_' + str(ids[1])]['kp_raw'][0],
                                   'label': 'ttest(0, 1)',
                                   'paired': True},
-                                 {'signal_1': df.loc['video_' + str(ids[0])]['kp_raw'],  # 0 and 2 = between
-                                  'signal_2': df.loc['video_' + str(ids[2])]['kp_raw'],
+                                 {'signal_1': df.loc['video_' + str(ids[0])]['kp_raw'][0],  # 0 and 2 = between
+                                  'signal_2': df.loc['video_' + str(ids[2])]['kp_raw'][0],
                                   'label': 'ttest(0, 2)',
                                   'paired': False},
-                                 {'signal_1': df.loc['video_' + str(ids[0])]['kp_raw'],  # 0 and 3 = between
-                                  'signal_2': df.loc['video_' + str(ids[3])]['kp_raw'],
+                                 {'signal_1': df.loc['video_' + str(ids[0])]['kp_raw'][0],  # 0 and 3 = between
+                                  'signal_2': df.loc['video_' + str(ids[3])]['kp_raw'][0],
                                   'label': 'ttest(0, 3)',
                                   'paired': False},
-                                 {'signal_1': df.loc['video_' + str(ids[1])]['kp_raw'],  # 1 and 2 = between
-                                  'signal_2': df.loc['video_' + str(ids[2])]['kp_raw'],
+                                 {'signal_1': df.loc['video_' + str(ids[1])]['kp_raw'][0],  # 1 and 2 = between
+                                  'signal_2': df.loc['video_' + str(ids[2])]['kp_raw'][0],
                                   'label': 'ttest(1, 2)',
                                   'paired': False},
-                                 {'signal_1': df.loc['video_' + str(ids[2])]['kp_raw'],  # 2 and 3 = within
-                                  'signal_2': df.loc['video_' + str(ids[3])]['kp_raw'],
+                                 {'signal_1': df.loc['video_' + str(ids[2])]['kp_raw'][0],  # 2 and 3 = within
+                                  'signal_2': df.loc['video_' + str(ids[3])]['kp_raw'][0],
                                   'label': 'ttest(2, 3)',
                                   'paired': True},
-                                 {'signal_1': df.loc['video_' + str(ids[1])]['kp_raw'],  # 1 and 3 = between
-                                  'signal_2': df.loc['video_' + str(ids[3])]['kp_raw'],
+                                 {'signal_1': df.loc['video_' + str(ids[1])]['kp_raw'][0],  # 1 and 3 = between
+                                  'signal_2': df.loc['video_' + str(ids[3])]['kp_raw'][0],
                                   'label': 'ttest(1, 3)',
                                   'paired': False}]
                 # signal_1 = signal_type = list of int, eg: [1,1,0,0]