@@ -76,7 +76,7 @@ def compute_monopolar_triangulation(
7676 assert feature in ["ptp" , "energy" , "peak_voltage" ], f"{ feature } is not a valid feature"
7777
7878 contact_locations = sorting_analyzer_or_templates .get_channel_locations ()
79-
79+
8080 if sorting_analyzer_or_templates .sparsity is None :
8181 sparsity = compute_sparsity (sorting_analyzer_or_templates , method = "radius" , radius_um = radius_um )
8282 else :
@@ -167,7 +167,7 @@ def compute_center_of_mass(
167167 )
168168 else :
169169 sparsity = sorting_analyzer_or_templates .sparsity
170-
170+
171171 templates = get_dense_templates_array (
172172 sorting_analyzer_or_templates , return_scaled = get_return_scaled (sorting_analyzer_or_templates )
173173 )
@@ -658,7 +658,6 @@ def get_convolution_weights(
658658 enforce_decrease_shells = numba .jit (enforce_decrease_shells_data , nopython = True )
659659
660660
661-
662661def compute_location_max_channel (
663662 templates_or_sorting_analyzer : SortingAnalyzer | Templates ,
664663 unit_ids = None ,
@@ -691,10 +690,7 @@ def compute_location_max_channel(
691690 2d
692691 """
693692 extremum_channels_index = get_template_extremum_channel (
694- templates_or_sorting_analyzer ,
695- peak_sign = peak_sign ,
696- mode = mode ,
697- outputs = "index"
693+ templates_or_sorting_analyzer , peak_sign = peak_sign , mode = mode , outputs = "index"
698694 )
699695 contact_locations = templates_or_sorting_analyzer .get_channel_locations ()
700696 if unit_ids is None :
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