flake

Author: mayofaulkner

brainbox/behavior/training.py

@@ -430,15 +430,13 @@ def compute_performance(trials, signed_contrast=None, block=None, prob_right=Fal
 
     contrasts, n_contrasts = np.unique(signed_contrast[block_idx], return_counts=True)
 
-    rightward = trials.choice == -1
-    # Calculate the proportion rightward for each contrast type
-    performance = np.vectorize(lambda x: np.mean(rightward[(x == signed_contrast) &
-                                                                 block_idx]))(contrasts)
-
     if not prob_right:
         correct = trials.feedbackType == 1
-        performance = np.vectorize(lambda x: np.mean(correct[(x == signed_contrast) &
-                                                               block_idx]))(contrasts)
+        performance = np.vectorize(lambda x: np.mean(correct[(x == signed_contrast) & block_idx]))(contrasts)
+    else:
+        rightward = trials.choice == -1
+        # Calculate the proportion rightward for each contrast type
+        performance = np.vectorize(lambda x: np.mean(rightward[(x == signed_contrast) & block_idx]))(contrasts)
 
     return performance, contrasts, n_contrasts
 

brainbox/task/trials.py

@@ -328,5 +328,3 @@ def filter_trials(trials, event_raster, event, contrast=(1, 0.5, 0.25, 0.125, 0.
         raster, psth = filter_correct_incorrect_left_right(trials, event_raster, event, contrast, order)
 
     return raster, psth
-
-

brainbox/tests/test_trials.py

@@ -167,4 +167,4 @@ def test_get_event_aligned_rasters(self):
         raster, t = get_event_aligned_raster(spikes, use_trials)
         assert (raster.shape[0] == len(use_trials))
         assert (all(np.isnan(raster[0:2, :]).ravel()))
-        assert (all(np.isnan(raster[-5:, :]).ravel()))
+        assert (all(np.isnan(raster[-5:, :]).ravel()))