[pre-commit.ci] auto fixes from pre-commit.com hooks

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src/spikeinterface/preprocessing/inter_session_alignment/session_alignment.py

@@ -538,7 +538,7 @@ def _get_single_session_activity_histogram(
             bin_s=None,
             depth_smooth_um=None,
             scale_to_hz=False,
-            weight_with_amplitude=weight_with_amplitude
+            weight_with_amplitude=weight_with_amplitude,
         )
 
         # It is important that the passed histogram is scaled to firing rate in Hz
@@ -848,7 +848,7 @@ def get_shifts(signal1, signal2, windows):
         signa11_blanked[:first_idx] = 0
         signal2_blanked[:first_idx] = 0
 
-    if (last_idx := windows[-1][-1]) != signal1.size - 1:  #double check
+    if (last_idx := windows[-1][-1]) != signal1.size - 1:  # double check
         print("last idx", last_idx)
         signa11_blanked[last_idx:] = 0
         signal2_blanked[last_idx:] = 0
@@ -870,14 +870,17 @@ def get_shifts(signal1, signal2, windows):
         # shift the signal1, or use indexing
         signa11_blanked = alignment_utils.shift_array_fill_zeros(signa11_blanked, shift)
 
-    #    plt.plot(signa11_blanked)
-    #    plt.plot(signal2_blanked)
-    #    plt.show()
+        #    plt.plot(signa11_blanked)
+        #    plt.plot(signal2_blanked)
+        #    plt.show()
 
         window_corrs = np.empty(windows.shape[0])
         for i, idx in enumerate(windows):
 
-            window_corrs[i] = np.correlate(signa11_blanked[idx] - np.mean(signa11_blanked[idx]), signal2_blanked[idx] - np.mean(signal2_blanked[idx]))
+            window_corrs[i] = np.correlate(
+                signa11_blanked[idx] - np.mean(signa11_blanked[idx]),
+                signal2_blanked[idx] - np.mean(signal2_blanked[idx]),
+            )
 
         max_window = np.argmax(window_corrs)
 
@@ -962,25 +965,26 @@ def _compute_session_alignment(
             )
             shifted_histograms[ses_idx, :] = shifted_histogram
 
-
     nonrigid_session_offsets_matrix = np.empty((shifted_histograms.shape[0], shifted_histograms.shape[0]))
 
     windows = []
     for i in range(non_rigid_windows.shape[0]):
-        idxs =  np.arange(non_rigid_windows.shape[1])[non_rigid_windows[i, :].astype(bool)]
+        idxs = np.arange(non_rigid_windows.shape[1])[non_rigid_windows[i, :].astype(bool)]
         windows.append(idxs)
         # TODO: check assumptions these are always the same size
 
     windows = np.vstack(windows)
 
-#    import matplotlib.pyplot as plt
-#    plt.plot(non_rigid_windows.T)
-#    plt.show()
+    #    import matplotlib.pyplot as plt
+    #    plt.plot(non_rigid_windows.T)
+    #    plt.show()
 
     windows1 = windows[::2, :]
     windows2 = windows[1::2, :]
 
-    nonrigid_session_offsets_matrix = np.empty((shifted_histograms.shape[0], shifted_histograms.shape[0], non_rigid_windows.shape[0]))
+    nonrigid_session_offsets_matrix = np.empty(
+        (shifted_histograms.shape[0], shifted_histograms.shape[0], non_rigid_windows.shape[0])
+    )
 
     for i in range(shifted_histograms.shape[0]):
         for j in range(shifted_histograms.shape[0]):
@@ -990,13 +994,13 @@ def _compute_session_alignment(
             shifts = np.empty(shifts1.size + shifts2.size)
             # breakpoint()
             shifts[::2] = shifts1
-            shifts[1::2] = (shifts1[:-1] + shifts1[1:]) / 2# np.shifts2
-        #    breakpoint()
+            shifts[1::2] = (shifts1[:-1] + shifts1[1:]) / 2  # np.shifts2
+            #    breakpoint()
             nonrigid_session_offsets_matrix[i, j, :] = shifts
 
     # TODO: there are gaps in between rect, rect seems weird,  they are non-overlapping :S
 
-       #     breakpoint()
+    #     breakpoint()
     # Then compute the nonrigid shifts
     # nonrigid_session_offsets_matrix = alignment_utils.compute_histogram_crosscorrelation(
     #    shifted_histograms, non_rigid_windows, **compute_alignment_kwargs