Merge branch 'main' into fix_ryan_error_lfp

Author: h-mayorquin

.github/scripts/test_kilosort4_ci.py

@@ -112,6 +112,10 @@
     PARAMS_TO_TEST_DICT.update({"cluster_neighbors": 11})
     PARAMETERS_NOT_AFFECTING_RESULTS.append("cluster_neighbors")
 
+if parse(kilosort.__version__) >= parse("4.0.37"):
+    PARAMS_TO_TEST_DICT.update({"max_cluster_subset": 20})
+    PARAMETERS_NOT_AFFECTING_RESULTS.append("max_cluster_subset")
+
 
 PARAMS_TO_TEST = list(PARAMS_TO_TEST_DICT.keys())
 
@@ -254,6 +258,8 @@ def test_initialize_ops_arguments(self):
             "device",
             "save_preprocessed_copy",
         ]
+        if parse(kilosort.__version__) >= parse("4.0.37"):
+            expected_arguments += ["gui_mode"]
 
         self._check_arguments(
             initialize_ops,

src/spikeinterface/extractors/phykilosortextractors.py

@@ -15,7 +15,7 @@ class BasePhyKilosortSortingExtractor(BaseSorting):
     Parameters
     ----------
     folder_path : str or Path
-        Path to the output Phy folder (containing the params.py)
+        Path to the output Phy/Kilosort folder (containing the params.py)
     exclude_cluster_groups : list or str, default: None
         Cluster groups to exclude (e.g. "noise" or ["noise", "mua"]).
     keep_good_only : bool, default: True
@@ -248,7 +248,7 @@ class KiloSortSortingExtractor(BasePhyKilosortSortingExtractor):
     Parameters
     ----------
     folder_path : str or Path
-        Path to the output Phy folder (containing the params.py).
+        Path to the output Kilosort folder (containing the params.py).
     keep_good_only : bool, default: True
         Whether to only keep good units.
         If True, only Kilosort-labeled 'good' units are returned.

src/spikeinterface/sorters/external/kilosort4.py

@@ -438,7 +438,9 @@ def _setup_json_probe_map(cls, recording, sorter_output_folder):
         chanMap = np.arange(n_chan)
         xc = positions[:, 0]
         yc = positions[:, 1]
-        kcoords = groups.astype(float)
+        unique_groups = set(groups)
+        group_map = {group: idx for idx, group in enumerate(unique_groups)}
+        kcoords = np.array([group_map[group] for group in groups], dtype=int)
 
         probe = {
             "chanMap": chanMap,