Fixes after Pierre remove many features methods!!!

SpikeInterface · Mar 4, 2024 · 5b48417 · 5b48417
1 parent f9640e8
commit 5b48417
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Showing 3 changed files with 9 additions and 8 deletions.
diff --git a/src/spikeinterface/sortingcomponents/clustering/position_and_features.py b/src/spikeinterface/sortingcomponents/clustering/position_and_features.py
@@ -47,6 +47,8 @@ class PositionAndFeaturesClustering:
 
     @classmethod
     def main_function(cls, recording, peaks, params):
+        from sklearn.preprocessing import QuantileTransformer
+
         assert HAVE_HDBSCAN, "twisted clustering needs hdbscan to be installed"
 
         if "n_jobs" in params["job_kwargs"]:
@@ -68,22 +70,22 @@ def main_function(cls, recording, peaks, params):
 
         position_method = d["peak_localization_kwargs"]["method"]
 
-        features_list = [position_method, "ptp", "energy"]
+        features_list = [position_method, "ptp",]
         features_params = {
             position_method: {"radius_um": params["radius_um"]},
             "ptp": {"all_channels": False, "radius_um": params["radius_um"]},
-            "energy": {"radius_um": params["radius_um"]},
         }
 
         features_data = compute_features_from_peaks(
             recording, peaks, features_list, features_params, ms_before=1, ms_after=1, **params["job_kwargs"]
         )
 
-        hdbscan_data = np.zeros((len(peaks), 4), dtype=np.float32)
+        hdbscan_data = np.zeros((len(peaks), 3), dtype=np.float32)
         hdbscan_data[:, 0] = features_data[0]["x"]
         hdbscan_data[:, 1] = features_data[0]["y"]
         hdbscan_data[:, 2] = features_data[1]
-        hdbscan_data[:, 3] = features_data[2]
+
+
 
         preprocessing = QuantileTransformer(output_distribution="uniform")
         hdbscan_data = preprocessing.fit_transform(hdbscan_data)

diff --git a/src/spikeinterface/sortingcomponents/features_from_peaks.py b/src/spikeinterface/sortingcomponents/features_from_peaks.py
@@ -215,4 +215,5 @@ def compute(self, traces, peaks, waveforms):
     "amplitude": AmplitudeFeature,
     "ptp": PeakToPeakFeature,
     "random_projections": RandomProjectionsFeature,
+    "center_of_mass": LocalizeCenterOfMass,
 }
diff --git a/src/spikeinterface/sortingcomponents/tests/test_features_from_peaks.py b/src/spikeinterface/sortingcomponents/tests/test_features_from_peaks.py
@@ -26,12 +26,11 @@ def test_features_from_peaks():
         **job_kwargs,
     )
 
-    feature_list = ["amplitude", "ptp", "center_of_mass", "energy"]
+    feature_list = ["amplitude", "ptp", "center_of_mass",]
     feature_params = {
         "amplitude": {"all_channels": False, "peak_sign": "neg"},
         "ptp": {"all_channels": False},
         "center_of_mass": {"radius_um": 120.0},
-        "energy": {"radius_um": 160.0},
     }
     features = compute_features_from_peaks(recording, peaks, feature_list, feature_params=feature_params, **job_kwargs)
 
@@ -45,14 +44,13 @@ def test_features_from_peaks():
 
     # split feature variable
     job_kwargs["n_jobs"] = 2
-    amplitude, ptp, com, energy = compute_features_from_peaks(
+    amplitude, ptp, com, = compute_features_from_peaks(
         recording, peaks, feature_list, feature_params=feature_params, **job_kwargs
     )
     assert amplitude.ndim == 1  # because all_channels=False
     assert ptp.ndim == 1  # because all_channels=False
     assert com.ndim == 1
     assert "x" in com.dtype.fields
-    assert energy.ndim == 1
 
     # amplitude and peak to peak with multi channels
     d = {"all_channels": True}