WIP

src/spikeinterface/postprocessing/template_similarity.py

@@ -232,9 +232,9 @@ def _compute_similarity_matrix_numba(templates_array, other_templates_array, num
 
         if same_array:
             # optimisation when array are the same because of symetry in shift
-            shift_loop = range(-num_shifts, 1)
+            shift_loop = list(range(-num_shifts, 1))
         else:
-            shift_loop = range(-num_shifts, num_shifts + 1)
+            shift_loop = list(range(-num_shifts, num_shifts + 1))
 
         if method == "l1":
             metric = 0
@@ -243,15 +243,17 @@ def _compute_similarity_matrix_numba(templates_array, other_templates_array, num
         elif method == "cosine":
             metric = 2
 
-        for count, shift in enumerate(shift_loop):
+        for count in range(len(shift_loop)):
+            shift = shift_loop[count]
             src_sliced_templates = templates_array[:, num_shifts : num_samples - num_shifts]
             tgt_sliced_templates = other_templates_array[:, num_shifts + shift : num_samples - num_shifts + shift]
             for i in numba.prange(num_templates):
                 src_template = src_sliced_templates[i]
                 overlapping_templates = np.flatnonzero(np.sum(mask[i], 1))
                 tgt_templates = tgt_sliced_templates[overlapping_templates]
-                for gcount, j in enumerate(overlapping_templates):
+                for gcount in range(len(overlapping_templates)):
 
+                    j = overlapping_templates[gcount]
                     # symmetric values are handled later
                     if same_array and j < i:
                         # no need exhaustive looping when same template