WIP

Author: yger

src/spikeinterface/sorters/internal/spyking_circus2.py

@@ -158,7 +158,7 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
                 whitening_kwargs["regularize_kwargs"] = {"method": "LedoitWolf"}
                 whitening_kwargs["apply_mean"] = True
             recording_w = whiten(recording_f, **whitening_kwargs)
-            
+
         else:
             recording_w = recording_f
 

src/spikeinterface/sortingcomponents/clustering/iterative_hdbscan.py

@@ -44,10 +44,7 @@ class IterativeHDBSCANClustering:
             },
         },
         "merge_from_templates": dict(
-            similarity_thresh=0.8, 
-            num_shifts=3, 
-            use_lags=True, 
-            similarity_metric=["l1", "l2", "cosine"]
+            similarity_thresh=0.8, num_shifts=3, use_lags=True, similarity_metric=["l1", "l2", "cosine"]
         ),
         "merge_from_features": None,
         "debug_folder": None,

src/spikeinterface/sortingcomponents/waveforms/peak_svd.py

@@ -53,6 +53,7 @@ def extract_peaks_svd(
     # Step 1 : select a few peaks to fit the SVD
     if svd_model is None:
         from sklearn.decomposition import TruncatedSVD
+
         few_peaks = select_peaks(
             peaks, recording=recording, method="uniform", n_peaks=n_peaks_fit, margin=(nbefore, nafter), seed=seed
         )