Expose seed for spike_locations (grid)

src/spikeinterface/postprocessing/spike_locations.py

@@ -20,6 +20,9 @@ class ComputeSpikeLocations(BaseSpikeVectorExtension):
         The localization method to use
     method_kwargs : dict, default: dict()
         Other kwargs depending on the method.
+    seed : int or None, default: None
+        Seed for random number generator. Used by the `grid_convolution` method to
+        reproducibly subsample peaks when computing the prototype waveform.
 
     Returns
     -------
@@ -48,6 +51,7 @@ def _set_params(
         spike_retriever_kwargs=None,
         method="center_of_mass",
         method_kwargs={},
+        seed=None,
     ):
         if spike_retriever_kwargs is None:
             spike_retriever_kwargs = {}
@@ -57,6 +61,7 @@ def _set_params(
             spike_retriever_kwargs=spike_retriever_kwargs,
             method=method,
             method_kwargs=method_kwargs,
+            seed=seed,
         )
 
     def _get_pipeline_nodes(self):
@@ -77,6 +82,7 @@ def _get_pipeline_nodes(self):
             method_kwargs=self.params["method_kwargs"],
             ms_before=self.params["ms_before"],
             ms_after=self.params["ms_after"],
+            seed=self.params.get("seed"),
         )
         return nodes
 

src/spikeinterface/sortingcomponents/peak_localization/main.py

@@ -25,6 +25,7 @@ def get_localization_pipeline_nodes(
     ms_before=0.5,
     ms_after=0.5,
     job_kwargs=None,
+    seed=None,
 ):
 
     assert (
@@ -52,7 +53,7 @@ def get_localization_pipeline_nodes(
 
         method_kwargs = method_kwargs.copy()
         method_kwargs["prototype"], _, _ = get_prototype_and_waveforms_from_peaks(
-            recording, peaks=peak_source.peaks, ms_before=ms_before, ms_after=ms_after, job_kwargs=job_kwargs
+            recording, peaks=peak_source.peaks, ms_before=ms_before, ms_after=ms_after, job_kwargs=job_kwargs, seed=seed
         )
 
     localization_nodes = method_class(recording, parents=[peak_source, extract_dense_waveforms], **method_kwargs)
@@ -72,6 +73,7 @@ def localize_peaks(
     pipeline_kwargs=None,
     verbose=False,
     job_kwargs=None,
+    seed=None,
     **old_kwargs,
 ) -> np.ndarray:
     """Localize peak (spike) in 2D or 3D depending the method.
@@ -102,6 +104,9 @@ def localize_peaks(
         If True, output is verbose
     job_kwargs : dict | None, default None
         A job kwargs dict. If None or empty dict, then the global one is used.
+    seed : int or None, default: None
+        Seed for random number generator. Used by `grid_convolution` to reproducibly
+        subsample peaks when computing the prototype waveform.
 
     {method_doc}
 
@@ -150,6 +155,7 @@ def localize_peaks(
         ms_before=ms_before,
         ms_after=ms_after,
         job_kwargs=job_kwargs,
+        seed=seed,
     )
 
     if pipeline_kwargs is None:

src/spikeinterface/sortingcomponents/peak_selection.py

@@ -106,7 +106,6 @@ def select_peak_indices(peaks, method, seed, **method_kwargs):
 
     selected_indices = []
 
-    seed = seed if seed else None
     rng = np.random.default_rng(seed=seed)
 
     if method == "uniform":