Fix unicode size bug, rename functions, and add get_sorting_property

Author: alejoe91

src/spikeinterface/core/base.py

@@ -145,7 +145,7 @@ def ids_to_indices(
             non_existent_ids = [id for id in ids if id not in self._main_ids]
             if non_existent_ids:
                 error_msg = (
-                    f"IDs {non_existent_ids} are not channel ids of the extractor. \n"
+                    f"IDs {non_existent_ids} are not ids of the extractor. \n"
                     f"Available ids are {self._main_ids} with dtype {self._main_ids.dtype}"
                 )
                 raise ValueError(error_msg)
@@ -293,6 +293,11 @@ def set_property(
                     ), f"Mismatch between existing property dtype {existing_property.kind} and provided values dtype {dtype_kind}."
 
                 indices = self.ids_to_indices(ids)
+                if dtype_kind == "U":
+                    # re-adjust the size of the property
+                    existing_unicode_size = max(len(s) for s in self._properties[key])
+                    new_unicode_size = max(max(len(s) for s in values), existing_unicode_size)
+                    self._properties[key] = self._properties[key].astype(f"<U{new_unicode_size}")
                 self._properties[key][indices] = values
             else:
                 indices = self.ids_to_indices(ids)

src/spikeinterface/core/sortinganalyzer.py

@@ -743,7 +743,7 @@ def set_temporary_recording(self, recording: BaseRecording, check_dtype: bool =
             warnings.warn("SortingAnalyzer recording is already set. The current recording is temporarily replaced.")
         self._temporary_recording = recording
 
-    def set_unit_property(
+    def set_sorting_property(
         self,
         key,
         values: list | np.ndarray | tuple,
@@ -793,6 +793,25 @@ def set_unit_property(
                     # IMPORTANT: we need to re-consolidate the zarr store!
                     zarr.consolidate_metadata(zarr_root.store)
 
+    def get_sorting_property(self, key: str, ids: Optional[Iterable] = None) -> np.ndarray:
+        """
+        Get property vector for unit ids.
+
+        Parameters
+        ----------
+        key : str
+            The property name
+        ids : list/np.array, default: None
+            List of subset of ids to get the values.
+            if None all the ids are returned
+
+        Returns
+        -------
+        values : np.array
+            Array of values for the property
+        """
+        return self.sorting.get_property(key, ids=ids)
+
     def _save_or_select_or_merge(
         self,
         format="binary_folder",

src/spikeinterface/core/tests/test_sortinganalyzer.py

@@ -66,9 +66,9 @@ def test_SortingAnalyzer_memory(tmp_path, dataset):
     )
     assert not sorting_analyzer.return_scaled
 
-    # test set_unit_property
-    sorting_analyzer.set_unit_property(key="quality", values=["good"] * len(sorting_analyzer.unit_ids))
-    sorting_analyzer.set_unit_property(key="number", values=np.arange(len(sorting_analyzer.unit_ids)))
+    # test set_sorting_property
+    sorting_analyzer.set_sorting_property(key="quality", values=["good"] * len(sorting_analyzer.unit_ids))
+    sorting_analyzer.set_sorting_property(key="number", values=np.arange(len(sorting_analyzer.unit_ids)))
     assert "quality" in sorting_analyzer.sorting.get_property_keys()
     assert "number" in sorting_analyzer.sorting.get_property_keys()
 
@@ -109,9 +109,9 @@ def test_SortingAnalyzer_binary_folder(tmp_path, dataset):
     assert not sorting_analyzer.return_scaled
     _check_sorting_analyzers(sorting_analyzer, sorting, cache_folder=tmp_path)
 
-    # test set_unit_property
-    sorting_analyzer.set_unit_property(key="quality", values=["good"] * len(sorting_analyzer.unit_ids))
-    sorting_analyzer.set_unit_property(key="number", values=np.arange(len(sorting_analyzer.unit_ids)))
+    # test set_sorting_property
+    sorting_analyzer.set_sorting_property(key="quality", values=["good"] * len(sorting_analyzer.unit_ids))
+    sorting_analyzer.set_sorting_property(key="number", values=np.arange(len(sorting_analyzer.unit_ids)))
     assert "quality" in sorting_analyzer.sorting.get_property_keys()
     assert "number" in sorting_analyzer.sorting.get_property_keys()
     sorting_analyzer_reloded = load_sorting_analyzer(folder, format="auto")
@@ -191,9 +191,9 @@ def test_SortingAnalyzer_zarr(tmp_path, dataset):
         == LZMA.codec_id
     )
 
-    # test set_unit_property
-    sorting_analyzer.set_unit_property(key="quality", values=["good"] * len(sorting_analyzer.unit_ids))
-    sorting_analyzer.set_unit_property(key="number", values=np.arange(len(sorting_analyzer.unit_ids)))
+    # test set_sorting_property
+    sorting_analyzer.set_sorting_property(key="quality", values=["good"] * len(sorting_analyzer.unit_ids))
+    sorting_analyzer.set_sorting_property(key="number", values=np.arange(len(sorting_analyzer.unit_ids)))
     assert "quality" in sorting_analyzer.sorting.get_property_keys()
     assert "number" in sorting_analyzer.sorting.get_property_keys()
     sorting_analyzer_reloded = load_sorting_analyzer(sorting_analyzer.folder, format="auto")