Merge branch 'main' into mpl_cmap

src/spikeinterface/sorters/internal/spyking_circus2.py

@@ -45,18 +45,19 @@ class Spykingcircus2Sorter(ComponentsBasedSorter):
             "select_per_channel": False,
             "seed": 42,
         },
-        "drift_correction": {"preset": "nonrigid_fast_and_accurate"},
+        "apply_motion_correction": True,
+        "motion_correction": {"preset": "nonrigid_fast_and_accurate"},
         "merging": {
             "minimum_spikes": 10,
             "corr_diff_thresh": 0.5,
             "template_metric": "cosine",
             "censor_correlograms_ms": 0.4,
-            "num_channels": 5,
+            "num_channels": None,
         },
         "clustering": {"legacy": True},
-        "matching": {"method": "circus-omp-svd"},
+        "matching": {"method": "wobble"},
         "apply_preprocessing": True,
-        "matched_filtering": False,
+        "matched_filtering": True,
         "cache_preprocessing": {"mode": "memory", "memory_limit": 0.5, "delete_cache": True},
         "multi_units_only": False,
         "job_kwargs": {"n_jobs": 0.8},
@@ -121,6 +122,7 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
         ms_before = params["general"].get("ms_before", 2)
         ms_after = params["general"].get("ms_after", 2)
         radius_um = params["general"].get("radius_um", 100)
+        exclude_sweep_ms = params["detection"].get("exclude_sweep_ms", max(ms_before, ms_after) / 2)
 
         ## First, we are filtering the data
         filtering_params = params["filtering"].copy()
@@ -133,15 +135,17 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
             recording_f.annotate(is_filtered=True)
 
         valid_geometry = check_probe_for_drift_correction(recording_f)
-        if params["drift_correction"] is not None:
+        if params["apply_motion_correction"]:
             if not valid_geometry:
-                print("Geometry of the probe does not allow 1D drift correction")
+                if verbose:
+                    print("Geometry of the probe does not allow 1D drift correction")
                 motion_folder = None
             else:
-                print("Motion correction activated (probe geometry compatible)")
+                if verbose:
+                    print("Motion correction activated (probe geometry compatible)")
                 motion_folder = sorter_output_folder / "motion"
-                params["drift_correction"].update({"folder": motion_folder})
-                recording_f = correct_motion(recording_f, **params["drift_correction"])
+                params["motion_correction"].update({"folder": motion_folder})
+                recording_f = correct_motion(recording_f, **params["motion_correction"])
         else:
             motion_folder = None
 
@@ -163,7 +167,7 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
         detection_params.update(job_kwargs)
 
         detection_params["radius_um"] = detection_params.get("radius_um", 50)
-        detection_params["exclude_sweep_ms"] = detection_params.get("exclude_sweep_ms", 0.5)
+        detection_params["exclude_sweep_ms"] = exclude_sweep_ms
         detection_params["noise_levels"] = noise_levels
 
         fs = recording_w.get_sampling_frequency()
@@ -212,6 +216,8 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
             clustering_params["waveforms"]["ms_after"] = ms_after
             clustering_params["job_kwargs"] = job_kwargs
             clustering_params["noise_levels"] = noise_levels
+            clustering_params["ms_before"] = exclude_sweep_ms
+            clustering_params["ms_after"] = exclude_sweep_ms
             clustering_params["tmp_folder"] = sorter_output_folder / "clustering"
 
             legacy = clustering_params.get("legacy", True)
@@ -275,12 +281,10 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
             matching_params["templates"] = templates
             matching_job_params = job_kwargs.copy()
 
-            if matching_method == "circus-omp-svd":
-
-                for value in ["chunk_size", "chunk_memory", "total_memory", "chunk_duration"]:
-                    if value in matching_job_params:
-                        matching_job_params[value] = None
-                matching_job_params["chunk_duration"] = "100ms"
+            for value in ["chunk_size", "chunk_memory", "total_memory", "chunk_duration"]:
+                if value in matching_job_params:
+                    matching_job_params[value] = None
+            matching_job_params["chunk_duration"] = "100ms"
 
             spikes = find_spikes_from_templates(
                 recording_w, matching_method, method_kwargs=matching_params, **matching_job_params
@@ -308,7 +312,7 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
         merging_params = params["merging"].copy()
 
         if len(merging_params) > 0:
-            if params["drift_correction"] and motion_folder is not None:
+            if params["motion_correction"] and motion_folder is not None:
                 from spikeinterface.preprocessing.motion import load_motion_info
 
                 motion_info = load_motion_info(motion_folder)

src/spikeinterface/sortingcomponents/clustering/circus.py

@@ -58,8 +58,8 @@ class CircusClustering:
         },
         "radius_um": 100,
         "n_svd": [5, 2],
-        "ms_before": 2,
-        "ms_after": 2,
+        "ms_before": 0.5,
+        "ms_after": 0.5,
         "noise_levels": None,
         "tmp_folder": None,
         "job_kwargs": {},

src/spikeinterface/widgets/tests/test_widgets.py

@@ -286,6 +286,16 @@ def test_plot_unit_templates(self):
                         backend=backend,
                         **self.backend_kwargs[backend],
                     )
+                    # test with templates
+                    templates_ext = self.sorting_analyzer_dense.get_extension("templates")
+                    templates = templates_ext.get_data(outputs="Templates")
+                    sw.plot_unit_templates(
+                        templates,
+                        sparsity=self.sparsity_strict,
+                        unit_ids=unit_ids,
+                        backend=backend,
+                        **self.backend_kwargs[backend],
+                    )
                 else:
                     # sortingview doesn't support more than 2 shadings
                     with self.assertRaises(AssertionError):

src/spikeinterface/widgets/unit_depths.py

@@ -35,7 +35,7 @@ def __init__(
         unit_ids = sorting_analyzer.sorting.unit_ids
 
         if unit_colors is None:
-            unit_colors = get_unit_colors(sorting_analyzer.sorting)
+            unit_colors = get_unit_colors(sorting_analyzer)
 
         colors = [unit_colors[unit_id] for unit_id in unit_ids]
 

src/spikeinterface/widgets/unit_summary.py

@@ -48,7 +48,7 @@ def __init__(
         sorting_analyzer = self.ensure_sorting_analyzer(sorting_analyzer)
 
         if unit_colors is None:
-            unit_colors = get_unit_colors(sorting_analyzer.sorting)
+            unit_colors = get_unit_colors(sorting_analyzer)
 
         plot_data = dict(
             sorting_analyzer=sorting_analyzer,

src/spikeinterface/widgets/unit_templates.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from ..core import SortingAnalyzer
 from .unit_waveforms import UnitWaveformsWidget
 from .base import to_attr
 
@@ -17,6 +18,9 @@ def plot_sortingview(self, data_plot, **backend_kwargs):
 
         dp = to_attr(data_plot)
 
+        sorting_analyzer = dp.sorting_analyzer_or_templates
+        assert isinstance(sorting_analyzer, SortingAnalyzer), "This widget requires a SortingAnalyzer as input"
+
         assert len(dp.templates_shading) <= 4, "Only 2 ans 4 templates shading are supported in sortingview"
 
         # ensure serializable for sortingview
@@ -50,7 +54,7 @@ def plot_sortingview(self, data_plot, **backend_kwargs):
         v_average_waveforms = vv.AverageWaveforms(average_waveforms=aw_items, channel_locations=locations)
 
         if not dp.hide_unit_selector:
-            v_units_table = generate_unit_table_view(dp.sorting_analyzer.sorting)
+            v_units_table = generate_unit_table_view(sorting_analyzer.sorting)
 
             self.view = vv.Box(
                 direction="horizontal",