From c5a20f6a5a8c7364f0f0a11cca3cd458b53b91ce Mon Sep 17 00:00:00 2001 From: Samuel Garcia Date: Mon, 17 Aug 2026 15:44:02 +0200 Subject: [PATCH] fix create analyzer main_channel_indices for benchmarks --- src/spikeinterface/benchmark/benchmark_base.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/src/spikeinterface/benchmark/benchmark_base.py b/src/spikeinterface/benchmark/benchmark_base.py index d7e72cbf1f..47ec6a70cd 100644 --- a/src/spikeinterface/benchmark/benchmark_base.py +++ b/src/spikeinterface/benchmark/benchmark_base.py @@ -131,7 +131,7 @@ def create(cls, study_folder, datasets={}, cases={}, levels=None): unit_ids = gt_sorting.unit_ids gt_unit_locations = gt_sorting.get_property("gt_unit_locations") channel_locations = rec.get_channel_locations() - max_channel_indices = np.argmin( + main_channel_indices = np.argmin( np.linalg.norm( gt_unit_locations[:, np.newaxis, :2] - channel_locations[np.newaxis, :], axis=2 ), @@ -142,7 +142,7 @@ def create(cls, study_folder, datasets={}, cases={}, levels=None): channel_locations[:, np.newaxis] - channel_locations[np.newaxis, :], axis=2 ) for unit_ind, unit_id in enumerate(unit_ids): - chan_ind = max_channel_indices[unit_ind] + chan_ind = main_channel_indices[unit_ind] (chan_inds,) = np.nonzero(distances[chan_ind, :] <= radius_um) mask[unit_ind, chan_inds] = True sparsity = ChannelSparsity(mask, unit_ids, channel_ids) @@ -156,6 +156,7 @@ def create(cls, study_folder, datasets={}, cases={}, levels=None): rec, sparse=sparse, sparsity=sparsity, + main_channel_indices=main_channel_indices, format="binary_folder", folder=local_analyzer_folder, )