Merge pull request #3488 from samuelgarcia/kilosort_matching_gpl

kilosort-matching in si

src/spikeinterface/sortingcomponents/matching/method_list.py

@@ -12,3 +12,11 @@
     "circus-omp-svd": CircusOMPSVDPeeler,
     "wobble": WobbleMatch,
 }
+
+try:
+    # Kilosort licence (GPL 3) is forcing us to make and use an external package
+    from spikeinterface_kilosort_components import KiloSortMatching
+
+    matching_methods["kilosort-matching"] = KiloSortMatching
+except ImportError:
+    pass

src/spikeinterface/sortingcomponents/motion/motion_utils.py

@@ -632,6 +632,5 @@ def ensure_time_bins(time_bin_centers_s=None, time_bin_edges_s=None):
     return time_bin_centers_s, time_bin_edges_s
 
 
-
 def ensure_time_bin_edges(time_bin_centers_s=None, time_bin_edges_s=None):
     return ensure_time_bins(time_bin_centers_s, time_bin_edges_s)[1]

src/spikeinterface/sortingcomponents/motion/tests/test_motion_interpolation.py

@@ -12,6 +12,7 @@
 from spikeinterface.sortingcomponents.tests.common import make_dataset
 from spikeinterface.core import generate_ground_truth_recording
 
+
 def make_fake_motion(rec):
     # make a fake motion object
 
@@ -25,7 +26,7 @@ def make_fake_motion(rec):
         seg_time_bins = np.arange(0.5, duration - 0.49, 0.5)
         seg_disp = np.zeros((seg_time_bins.size, spatial_bins.size))
         seg_disp[:, :] = np.linspace(-30, 30, seg_time_bins.size)[:, None]
-        
+
         temporal_bins.append(seg_time_bins)
         displacement.append(seg_disp)
 
@@ -204,7 +205,6 @@ def test_InterpolateMotionRecording():
         seed=2205,
     )
 
-
     motion = make_fake_motion(rec)
 
     rec2 = InterpolateMotionRecording(rec, motion, border_mode="force_extrapolate")

src/spikeinterface/sortingcomponents/tests/test_template_matching.py

@@ -45,9 +45,39 @@ def test_find_spikes_from_templates(method, sorting_analyzer):
         "templates": templates,
     }
     method_kwargs = {}
-    if method in ("naive", "tdc-peeler", "circus", "tdc-peeler2"):
+    if method in (
+        "naive",
+        "tdc-peeler",
+        "circus",
+    ):
         method_kwargs["noise_levels"] = noise_levels
 
+    if method == "kilosort-matching":
+        from spikeinterface.sortingcomponents.peak_selection import select_peaks
+        from spikeinterface.sortingcomponents.tools import extract_waveform_at_max_channel
+        from spikeinterface.sortingcomponents.peak_detection import detect_peaks
+
+        peaks = detect_peaks(sorting_analyzer.recording, method="locally_exclusive", skip_after_n_peaks=5000)
+        few_wfs = extract_waveform_at_max_channel(sorting_analyzer.recording, peaks, ms_before=1, ms_after=2)
+
+        wfs = few_wfs[:, :, 0]
+        import numpy as np
+
+        n_components = 5
+        from sklearn.cluster import KMeans
+
+        wfs /= np.linalg.norm(wfs, axis=1)[:, None]
+        model = KMeans(n_clusters=n_components, n_init=10).fit(wfs)
+        temporal_components = model.cluster_centers_
+        temporal_components = temporal_components / np.linalg.norm(temporal_components[:, None])
+        temporal_components = temporal_components.astype(np.float32)
+        from sklearn.decomposition import TruncatedSVD
+
+        model = TruncatedSVD(n_components=n_components).fit(wfs)
+        spatial_components = model.components_.astype(np.float32)
+        method_kwargs["spatial_components"] = spatial_components
+        method_kwargs["temporal_components"] = temporal_components
+
     # method_kwargs["wobble"] = {
     #     "templates": waveform_extractor.get_all_templates(),
     #     "nbefore": waveform_extractor.nbefore,
@@ -91,5 +121,7 @@ def test_find_spikes_from_templates(method, sorting_analyzer):
     # method = "tdc-peeler"
     # method =  "circus"
     # method = "circus-omp-svd"
-    method = "wobble"
+    # method = "wobble"
+    method = "kilosort-matching"
+
     test_find_spikes_from_templates(method, sorting_analyzer)