Merge pull request #3990 from chrishalcrow/propagate-relative-to

Propagate `relative_to` to `dump_to_pickle`

Author: alejoe91

src/spikeinterface/core/base.py

@@ -699,7 +699,7 @@ def dump(self, file_path: Union[str, Path], relative_to=None, folder_metadata=No
         if str(file_path).endswith(".json"):
             self.dump_to_json(file_path, relative_to=relative_to, folder_metadata=folder_metadata)
         elif str(file_path).endswith(".pkl") or str(file_path).endswith(".pickle"):
-            self.dump_to_pickle(file_path, folder_metadata=folder_metadata)
+            self.dump_to_pickle(file_path, relative_to=relative_to, folder_metadata=folder_metadata)
         else:
             raise ValueError("Dump: file must .json or .pkl")
 

src/spikeinterface/core/tests/test_baserecording.py

@@ -346,6 +346,38 @@ def test_BaseRecording(create_cache_folder):
         assert rec2.get_annotation(annotation_name) == rec_zarr2_loaded.get_annotation(annotation_name)
 
 
+def test_json_pickle_equivalence(create_cache_folder):
+    """
+    For a json-ifyable recording, the json and pickle outputs created by `dump` should be the same
+    (except for the probe information). We check this here for a saved-then-loaded recording,
+    which tests if relative paths are dealt with in the same way.
+    """
+
+    rec = generate_recording(durations=[1])
+    cache_folder = create_cache_folder
+
+    json_file_path = cache_folder / "recording.json"
+    pkl_file_path = cache_folder / "recording.pkl"
+
+    rec.dump(json_file_path, relative_to=cache_folder)
+    rec.dump(pkl_file_path, relative_to=cache_folder)
+
+    with open(json_file_path, "r") as f:
+        data_json = json.load(f)
+
+    with open(pkl_file_path, "rb") as f:
+        data_pickle = pickle.load(f)
+
+    for key, value in data_json.items():
+        # skip probe info, since pickle keeps some additional information
+        if key not in ["properties"]:
+            if isinstance(value, dict):
+                for sub_key, sub_value in value.items():
+                    assert np.all(sub_value == data_pickle[key][sub_key])
+            else:
+                assert np.all(value == data_pickle[key])
+
+
 def test_interleaved_probegroups():
     recording = generate_recording(durations=[1.0], num_channels=16)