change name of target_object to localized_entity

spec/ndx-anatomical-localization.extensions.yaml

@@ -59,7 +59,7 @@ groups:
         neurodata_type_inc: VectorData
         doc: "The z coordinate"
         quantity: 1
-      - name: target_object
+      - name: localized_entity
         neurodata_type_inc: DynamicTableRegion
         doc: "The object to which the coordinates refer (e.g. electrode)"
         quantity: 1

src/pynwb/ndx_anatomical_localization/ndx_anatomical_localization.py

@@ -1,7 +1,7 @@
 from hdmf.common import DynamicTable
-from hdmf.utils import docval, get_docval, AllowPositional
-from pynwb import get_class, register_class
+from hdmf.utils import get_docval, AllowPositional
 
+from pynwb import get_class, register_class, docval, register_map
 
 TempSpace = get_class("Space", "ndx-anatomical-localization")
 TempAnatomicalCoordinatesTable = get_class("AnatomicalCoordinatesTable", "ndx-anatomical-localization")
@@ -56,20 +56,20 @@ class AnatomicalCoordinatesTable(TempAnatomicalCoordinatesTable):
         {"name": "space", "type": Space, "doc": "space of the table"},
         {"name": "method", "type": str, "doc": "method of the table"},
         {"name": "target", "type": DynamicTable,
-         "doc": 'target table. ignored if a "target_object" column is provided in "columns"', "default": None},
+         "doc": 'target table. ignored if a "localized_entity" column is provided in "columns"', "default": None},
         *get_docval(DynamicTable.__init__),
         allow_positional=AllowPositional.ERROR,
     )
     def __init__(self, **kwargs):
         columns = kwargs.get("columns")
         target = kwargs.pop("target")
-        if not columns or "target_object" not in [c.name for c in columns]:
-            # set the target table of the "target_object" column only if the "target_object" column is not in "columns"
+        if not columns or "localized_entity" not in [c.name for c in columns]:
+            # set the target table of the "localized_entity" column only if the "localized_entity" column is not in "columns"
             if target is None:
                 raise ValueError(
                     '"target" (the target table that contains the objects that have these coordinates) '
                     'must be provided in AnatomicalCoordinatesTable.__init__ '
-                    'if the "target_object" column is not in "columns".')
-            kwargs["target_tables"] = {"target_object": target}
+                    'if the "localized_entity" column is not in "columns".')
+            kwargs["target_tables"] = {"localized_entity": target}
 
         super().__init__(**kwargs)

src/pynwb/tests/test_anatomical_coordinates.py

@@ -27,7 +27,7 @@ def test_create_anatomical_coordinates_table():
         method="method",
         space=space,
     )
-    [table.add_row(x=1.0, y=2.0, z=3.0, brain_region="CA1", target_object=x) for x in range(5)]
+    [table.add_row(x=1.0, y=2.0, z=3.0, brain_region="CA1", localized_entity=x) for x in range(5)]
 
     localization.add_anatomical_coordinates_tables([table])
 
@@ -43,10 +43,10 @@ def test_create_anatomical_coordinates_table():
 
         assert read_coordinates_table.method == "method"
         assert read_coordinates_table.description == "Anatomical coordinates table"
-        assert read_coordinates_table.target_object.table is read_electrodes_table
+        assert read_coordinates_table.localized_entity.table is read_electrodes_table
         assert read_coordinates_table.space.fields == Space.get_predefined_space("CCFv3").fields
         npt.assert_array_equal(read_coordinates_table["x"].data[:], np.array([1.0, 1.0, 1.0, 1.0, 1.0]))
         npt.assert_array_equal(read_coordinates_table["y"].data[:], np.array([2.0, 2.0, 2.0, 2.0, 2.0]))
         npt.assert_array_equal(read_coordinates_table["z"].data[:], np.array([3.0, 3.0, 3.0, 3.0, 3.0]))
         npt.assert_array_equal(read_coordinates_table["brain_region"].data[:], np.array(["CA1", "CA1", "CA1", "CA1", "CA1"]))
-        npt.assert_array_equal(read_coordinates_table["target_object"].data[:], np.array([0, 1, 2, 3, 4]))
+        npt.assert_array_equal(read_coordinates_table["localized_entity"].data[:], np.array([0, 1, 2, 3, 4]))