Write references in compound datasets as an array rather than iterati…

…vely

src/hdmf_zarr/backend.py

@@ -1011,21 +1011,42 @@ def write_dataset(self, **kwargs):  # noqa: C901
                     type_str.append(self.__serial_dtype__(t)[0])
 
             if len(refs) > 0:
-                dset = parent.require_dataset(name,
-                                              shape=(len(data), len(data[0])),
-                                              dtype=object,
-                                              object_codec=self.__codec_cls(),
-                                              **options['io_settings'])
+
                 self._written_builders.set_written(builder)  # record that the builder has been written
-                dset.attrs['zarr_dtype'] = type_str
+
+                # gather items to write
                 new_items = []
                 for j, item in enumerate(data):
                     new_item = list(item)
                     for i in refs:
                         new_item[i] = self.__get_ref(item[i], export_source=export_source)
-                    new_items.append(new_item)
-
-                dset[...] = np.array(new_items)
+                    new_items.append(tuple(new_item))
+
+                # Create dtype for storage, replacing values to match hdmf's hdf5 behavior
+                new_dtype = []
+                for field in options['dtype']:
+                    if field['dtype'] is str:
+                        new_dtype.append((field['name'], 'U25'))
+                    elif isinstance(field['dtype'], dict):
+                        # eg. for some references, dtype will be of the form
+                        # {'target_type': 'Baz', 'reftype': 'object'}
+                        # which should just get serialized as an object
+                        new_dtype.append((field['name'], 'O'))
+                    else:
+                        new_dtype.append((field['name'], field['dtype']))
+                dtype = np.dtype(new_dtype)
+
+                # cast and store compound dataset
+                arr = np.array(new_items, dtype=dtype)
+                dset = parent.require_dataset(
+                    name,
+                    shape=(len(arr),),
+                    dtype=dtype,
+                    object_codec=self.__codec_cls(),
+                    **options['io_settings']
+                )
+                dset.attrs['zarr_dtype'] = type_str
+                dset[...] = arr
             else:
                 # write a compound datatype
                 dset = self.__list_fill__(parent, name, data, options)