fix deprecated np.float and np.int

Author: mikejhuang

allensdk/brain_observatory/behavior/data_objects/stimuli/stimulus_templates.py

@@ -76,7 +76,7 @@ def _exclude_unseen_pixels(self, arr: np.ndarray):
         """After warping, some pixels are not visible on the screen.
         This sets those pixels to nan to make downstream analysis easier."""
         mask = self._monitor.get_mask()
-        arr = arr.astype(np.float)
+        arr = arr.astype('float')
         arr *= mask
         arr[mask == 0] = np.nan
         return arr

allensdk/brain_observatory/behavior/dprime.py

@@ -15,7 +15,7 @@ def get_go_responses(hit=None, miss=None, aborted=None):
 
     # Go responses are nan when catch (aborted are masked out); 0 for miss, 1 for hit
     # This allows pd.Series.rolling to ignore non-go trial data
-    go_responses = np.empty_like(hit, dtype=np.float)
+    go_responses = np.empty_like(hit, dtype='float')
     go_responses.fill(float('nan'))
     go_responses[hit] = 1
     go_responses[miss] = 0
@@ -44,7 +44,7 @@ def get_catch_responses(correct_reject=None, false_alarm=None, aborted=None):
 
     # Catch responses are nan when go (aborted are masked out); 0 for correct-rejection, 1 for false-alarm
     # This allows pd.Series.rolling to ignore non-catch trial data
-    catch_responses = np.empty_like(correct_reject, dtype=np.float)
+    catch_responses = np.empty_like(correct_reject, dtype='float')
     catch_responses.fill(float('nan'))
     catch_responses[false_alarm] = 1
     catch_responses[correct_reject] = 0

allensdk/brain_observatory/behavior/swdb/summary_figures.py

@@ -381,7 +381,7 @@ def plot_max_proj_and_roi_masks(session, save_dir=None):
     ax[2].set_title(str(session.metadata['ophys_experiment_id']))
 
     tmp = session.segmentation_mask_image.data.copy()
-    mask = np.empty(session.segmentation_mask_image.data.shape, dtype=np.float)
+    mask = np.empty(session.segmentation_mask_image.data.shape, dtype='float')
     mask[:] = np.nan
     mask[tmp > 0] = 1
     cax = ax[2].imshow(mask, cmap='hsv', alpha=0.4, vmin=0, vmax=1)

allensdk/brain_observatory/chisquare_categorical.py

@@ -84,8 +84,8 @@ def stim_table_to_categories(stim_table,
 
     category = 0
     sweep_categories = -1*np.ones((num_sweeps,))
-    curr_combination = np.zeros((num_params,),dtype=np.int)
-    options_per_column = np.array(options_per_column).astype(np.int)
+    curr_combination = np.zeros((num_params,),dtype='int')
+    options_per_column = np.array(options_per_column).astype('int')
     all_tried = False
     while not all_tried:
 

allensdk/brain_observatory/stimulus_info.py

@@ -518,9 +518,6 @@ def lsn_image_to_screen(self, img, stimulus_type, origin='lower', background_col
 
     def natural_scene_image_to_screen(self, img, origin='lower', translation=(0,0)):
 
-        # assert img.dtype == np.float32
-        # img = img.astype(np.uint8)
-
         full_image = np.full((self.n_pixels_r, self.n_pixels_c), 127, dtype=np.uint8)
         mr, mc = natural_scene_coordinate_to_monitor_coordinate((0, 0), (self.n_pixels_r, self.n_pixels_c))
         Mr, Mc = natural_scene_coordinate_to_monitor_coordinate((img.shape[0], img.shape[1]), (self.n_pixels_r, self.n_pixels_c))
@@ -756,7 +753,7 @@ def warp_stimulus_coords(vertices,
     distance = float(distance)
     mon_res_x, mon_res_y = float(mon_res[0]), float(mon_res[1])
 
-    vertices = vertices.astype(np.float)
+    vertices = vertices.astype('float')
 
     # from pixels (-1920/2 -> 1920/2) to stimulus space (-0.5->0.5)
     vertices[:, 0] = vertices[:, 0] / mon_res_x