Prepare 0.105.2 bug fixes release

doc/releases/0.105.2.rst

@@ -0,0 +1,24 @@
+.. _release0.105.2:
+
+SpikeInterface 0.105.2 release notes
+------------------------------------
+
+October 14th 2026
+
+Minor release with bug fixes
+
+
+core:
+
+* Fix: channel_slice should not check overlapping probes (#4862)
+* Reintroduce ``set_times(..., with_warning)``, with deprecation (#4864)
+
+postprocessing:
+
+* Fix: grid convolution select_peaks (#4863)
+* Fix: PCA computation in lazy mode (#4861)
+
+
+Contributors:
+
+* @alejoe91

doc/whatisnew.rst

@@ -64,8 +64,8 @@ Release notes
   releases/0.9.1.rst
 
 
-Versions 0.105.1
-================
+Versions 0.105.1/2
+==================
 
 * Minor releases with bug fixes and performance improvements
 

src/spikeinterface/core/channelslice.py

@@ -66,7 +66,7 @@ def __init__(self, recording, channel_ids=None, renamed_channel_ids=None):
             parent_probegroup = self._parent.get_probegroup()
             sliced_probegroup = parent_probegroup.get_slice(self._parent_channel_indices)
             sliced_probegroup.set_global_device_channel_indices(np.arange(len(self._channel_ids)))
-            self.set_probegroup(sliced_probegroup)
+            self.set_probegroup(sliced_probegroup, check_overlap=False)
             # Reset channel groups to original ones to avoid remapping
             self.set_channel_groups(recording.get_channel_groups()[self._parent_channel_indices])
 

src/spikeinterface/core/time_series.py

@@ -222,7 +222,7 @@ def has_time_vector(self, segment_index: Optional[int] = None):
         segment_index = self._check_segment_index(segment_index)
         return self.segments[segment_index].has_time_vector()
 
-    def set_times(self, times, segment_index=None):
+    def set_times(self, times, segment_index=None, with_warning=None):
         """Set times for a recording segment.
 
         Parameters
@@ -233,6 +233,14 @@ def set_times(self, times, segment_index=None):
         segment_index : int or None, default: None
             The segment index (required for multi-segment)
         """
+        if with_warning is not None:
+            warnings.warn(
+                "The 'with_warning' parameter is deprecated and will be removed in 0.106.0. "
+                "Setting times in memory is now correctly propagated in preprocessing and saving operations, "
+                "so you can safely remove the 'with_warning' parameter.",
+                FutureWarning,
+                stacklevel=2,
+            )
         segment_index = self._check_segment_index(segment_index)
         rs = self.segments[segment_index]
 

src/spikeinterface/postprocessing/principal_component.py

@@ -171,16 +171,24 @@ def get_pca_model(self):
             * if mode is "by_channel_local", "pca_model" is a list of PCA model by channel
             * if mode is "by_channel_global" or "concatenated", "pca_model" is a single PCA model
         """
-        if self.sorting_analyzer._lazy:
-            raise RuntimeError("PCA models are not loaded in lazy mode. Reload the sorting analyzer in non-lazy mode.")
         mode = self.params["mode"]
         if mode == "by_channel_local":
             pca_models = []
             for chan_id in self.sorting_analyzer.channel_ids:
-                pca_models.append(self.data[f"pca_model_{mode}_{chan_id}"])
+                pca_model = self.data.get(f"pca_model_{mode}_{chan_id}")
+                if pca_model is None and self._sorting_analyzer._lazy:
+                    raise RuntimeError(
+                        "PCA models are not loaded in lazy mode. Reload the sorting analyzer in non-lazy mode."
+                    )
+                pca_models.append(pca_model)
+            return pca_models
         else:
-            pca_models = self.data[f"pca_model_{mode}"]
-        return pca_models
+            pca_model = self.data.get(f"pca_model_{mode}")
+            if pca_model is None and self._sorting_analyzer._lazy:
+                raise RuntimeError(
+                    "PCA models are not loaded in lazy mode. Reload the sorting analyzer in non-lazy mode."
+                )
+            return pca_model
 
     def get_projections_one_unit(self, unit_id, sparse=False):
         """
@@ -330,8 +338,6 @@ def _run(self, verbose=False, **job_kwargs):
         Compute the PCs on waveforms extacted within the by ComputeWaveforms.
         Projections are computed only on the waveforms sampled by the SortingAnalyzer.
         """
-        if self.sorting_analyzer._lazy:
-            raise RuntimeError("PCA models are not loaded in lazy mode. Reload the sorting analyzer in non-lazy mode.")
         p = self.params
         mode = p["mode"]
 

src/spikeinterface/postprocessing/tests/test_spike_locations.py

@@ -12,7 +12,7 @@ class TestSpikeLocationsExtension(AnalyzerExtensionCommonTestSuite):
             dict(method="center_of_mass", spike_retriever_kwargs=dict(channel_from_template=True)),
             dict(method="center_of_mass", spike_retriever_kwargs=dict(channel_from_template=False)),
             dict(method="monopolar_triangulation"),
-            dict(method="grid_convolution"),
+            dict(method="grid_convolution", method_kwargs=dict(n_peaks=100)),
         ],
     )
     def test_extension(self, params):

src/spikeinterface/sortingcomponents/peak_localization/main.py

@@ -60,6 +60,11 @@ def get_localization_pipeline_nodes(
         # How do you get peaks
 
         method_kwargs = method_kwargs.copy()
+        n_peaks = method_kwargs.pop("n_peaks", None)
+        if n_peaks is not None:
+            prototype_extra_kwargs = {"n_peaks": n_peaks}
+        else:
+            prototype_extra_kwargs = {}
         method_kwargs["prototype"], _, _ = get_prototype_and_waveforms_from_peaks(
             recording,
             peaks=peaks_or_spikes,
@@ -68,6 +73,7 @@ def get_localization_pipeline_nodes(
             channel_index_array=channel_index_array,
             job_kwargs=job_kwargs,
             seed=seed,
+            **prototype_extra_kwargs,
         )
 
     localization_nodes = method_class(recording, parents=[peak_source, extract_dense_waveforms], **method_kwargs)

src/spikeinterface/sortingcomponents/tools.py

@@ -130,23 +130,28 @@ def get_prototype_and_waveforms_from_peaks(
     nbefore = ms_to_samples(ms_before, recording.sampling_frequency)
     nafter = ms_to_samples(ms_after, recording.sampling_frequency)
 
-    few_peaks = select_peaks(
+    few_peaks, few_indices = select_peaks(
         peaks,
         recording=recording,
         method="uniform",
         n_peaks=n_peaks,
         margin=(nbefore, nafter),
         channel_index_array=channel_index_array,
+        return_indices=True,
         seed=seed,
     )
+    if channel_index_array is not None:
+        few_channel_index_array = channel_index_array[few_indices]
+    else:
+        few_channel_index_array = None
     waveforms = extract_waveform_at_max_channel(
         recording,
         few_peaks,
         ms_before=ms_before,
         ms_after=ms_after,
         job_kwargs=job_kwargs,
         job_name="waveform prototype",
-        channel_index_array=channel_index_array,
+        channel_index_array=few_channel_index_array,
     )
 
     with np.errstate(divide="ignore", invalid="ignore"):