Merge pull request #2896 from samuelgarcia/some_fix

Important fixes

src/spikeinterface/core/analyzer_extension_core.py

@@ -488,9 +488,9 @@ def get_templates(self, unit_ids=None, operator="average", percentile=None, save
                 self.params["operators"] += [(operator, percentile)]
             templates_array = self.data[key]
 
-        if save:
-            if not self.sorting_analyzer.is_read_only():
-                self.save()
+            if save:
+                if not self.sorting_analyzer.is_read_only():
+                    self.save()
 
         if unit_ids is not None:
             unit_indices = self.sorting_analyzer.sorting.ids_to_indices(unit_ids)

src/spikeinterface/core/sortinganalyzer.py

@@ -585,9 +585,10 @@ def load_from_zarr(cls, folder, recording=None):
             rec_attributes["probegroup"] = None
 
         # sparsity
-        if "sparsity_mask" in zarr_root.attrs:
-            # sparsity = zarr_root.attrs["sparsity"]
-            sparsity = ChannelSparsity(zarr_root["sparsity_mask"], cls.unit_ids, rec_attributes["channel_ids"])
+        if "sparsity_mask" in zarr_root:
+            sparsity = ChannelSparsity(
+                np.array(zarr_root["sparsity_mask"]), sorting.unit_ids, rec_attributes["channel_ids"]
+            )
         else:
             sparsity = None
 
@@ -1596,10 +1597,6 @@ def load_data(self):
                 self.data[ext_data_name] = ext_data
 
         elif self.format == "zarr":
-            # Alessio
-            # TODO: we need decide if we make a copy to memory or keep the lazy loading. For binary_folder it used to be lazy with memmap
-            # but this make the garbage complicated when a data is hold by a plot but the o SortingAnalyzer is delete
-            # lets talk
             extension_group = self._get_zarr_extension_group(mode="r")
             for ext_data_name in extension_group.keys():
                 ext_data_ = extension_group[ext_data_name]
@@ -1615,7 +1612,8 @@ def load_data(self):
                 elif "object" in ext_data_.attrs:
                     ext_data = ext_data_[0]
                 else:
-                    ext_data = ext_data_
+                    # this load in memmory
+                    ext_data = np.array(ext_data_)
                 self.data[ext_data_name] = ext_data
 
     def copy(self, new_sorting_analyzer, unit_ids=None):

src/spikeinterface/core/sparsity.py

@@ -118,6 +118,14 @@ def __repr__(self):
         txt = f"ChannelSparsity - units: {self.num_units} - channels: {self.num_channels} - density, P(x=1): {density:0.2f}"
         return txt
 
+    def __eq__(self, other):
+        return (
+            isinstance(other, ChannelSparsity)
+            and np.array_equal(self.channel_ids, other.channel_ids)
+            and np.array_equal(self.unit_ids, other.unit_ids)
+            and np.array_equal(self.mask, other.mask)
+        )
+
     @property
     def unit_id_to_channel_ids(self):
         if self._unit_id_to_channel_ids is None:

src/spikeinterface/core/tests/test_sortinganalyzer.py

@@ -155,10 +155,15 @@ def _check_sorting_analyzers(sorting_analyzer, original_sorting, cache_folder):
 
         data = sorting_analyzer2.get_extension("dummy").data
         assert "result_one" in data
+        assert isinstance(data["result_one"], str)
+        assert isinstance(data["result_two"], np.ndarray)
         assert data["result_two"].size == original_sorting.to_spike_vector().size
+        assert np.array_equal(data["result_two"], sorting_analyzer.get_extension("dummy").data["result_two"])
 
         assert sorting_analyzer2.return_scaled == sorting_analyzer.return_scaled
 
+        assert sorting_analyzer2.sparsity == sorting_analyzer.sparsity
+
     # select unit_ids to several format
     for format in ("memory", "binary_folder", "zarr"):
         if format != "memory":

src/spikeinterface/widgets/utils_matplotlib.py

@@ -15,7 +15,7 @@ def make_mpl_figure(figure=None, ax=None, axes=None, ncols=None, num_axes=None,
             if "ipympl" not in matplotlib.get_backend():
                 ax = figure.add_subplot(111)
             else:
-                ax = figure.add_subplot(111, layout="constrained")
+                ax = figure.add_subplot(111)
             axes = np.array([[ax]])
         else:
             assert ncols is not None