fix setattr for index and data

nwb_linkml/src/nwb_linkml/includes/hdmf.py

@@ -65,10 +65,6 @@ class DynamicTableMixin(BaseModel):
     def _columns(self) -> Dict[str, Union[list, "NDArray", "VectorDataMixin"]]:
         return {k: getattr(self, k) for i, k in enumerate(self.colnames)}
 
-    @property
-    def _columns_list(self) -> List[Union[list, "NDArray", "VectorDataMixin"]]:
-        return [getattr(self, k) for i, k in enumerate(self.colnames)]
-
     @overload
     def __getitem__(self, item: str) -> Union[list, "NDArray", "VectorDataMixin"]: ...
 
@@ -283,7 +279,7 @@ class DynamicTableMixin(BaseModel):
                         model[key] = VectorIndex(name=key, description="", value=val)
                     else:
                         model[key] = VectorData(name=key, description="", value=val)
-                except ValidationError as e:
+                except ValidationError as e:  # pragma: no cover
                     raise ValidationError(
                         f"field {key} cannot be cast to VectorData from {val}"
                     ) from e
@@ -423,24 +419,24 @@ class VectorIndexMixin(BaseModel, Generic[T]):
             kwargs["value"] = value
         super().__init__(**kwargs)
 
-    def _getitem_helper(self, arg: int) -> Union[list, NDArray]:
+    def _slice(self, arg: int) -> slice:
         """
         Mimicking :func:`hdmf.common.table.VectorIndex.__getitem_helper`
         """
         start = 0 if arg == 0 else self.value[arg - 1]
         end = self.value[arg]
-        return self.target.value[slice(start, end)]
+        return slice(start, end)
 
     def __getitem__(self, item: Union[int, slice, Iterable]) -> Any:
         if self.target is None:
             return self.value[item]
         else:
             if isinstance(item, (int, np.integer)):
-                return self._getitem_helper(item)
+                return self.target.value[self._slice(item)]
             elif isinstance(item, (slice, Iterable)):
                 if isinstance(item, slice):
                     item = range(*item.indices(len(self.value)))
-                return [self._getitem_helper(i) for i in item]
+                return [self.target.value[self._slice(i)] for i in item]
             else:
                 raise AttributeError(f"Could not index with {item}")
 
@@ -458,8 +454,27 @@ class VectorIndexMixin(BaseModel, Generic[T]):
 
         """
         if self.target:
-            # __getitem__ will return the indexed reference to the target
-            self[key] = value
+            if isinstance(key, (int, np.integer)):
+                self.target.value[self._slice(key)] = value
+            elif isinstance(key, (slice, Iterable)):
+                if isinstance(key, slice):
+                    key = range(*key.indices(len(self.value)))
+
+                if isinstance(value, Iterable):
+                    if len(key) != len(value):
+                        raise ValueError(
+                            "Can only assign equal-length iterable to a slice, manually index the"
+                            " ragged values of of the target VectorData object if you need more"
+                            " control"
+                        )
+                    for i, subval in zip(key, value):
+                        self.target.value[self._slice(i)] = subval
+                else:
+                    for i in key:
+                        self.target.value[self._slice(i)] = value
+            else:  # pragma: no cover
+                raise AttributeError(f"Could not index with {key}")
+
         else:
             self.value[key] = value
 

nwb_linkml/tests/test_includes/test_hdmf.py

@@ -241,7 +241,7 @@ def test_dynamictable_resolve_index():
     assert inst.new_col_2._index is inst.new_col_2_index
 
 
-def dynamictable_assert_equal_length():
+def test_dynamictable_assert_equal_length():
     """
     Dynamictable validates that columns are of equal length
     """
@@ -277,7 +277,7 @@ def dynamictable_assert_equal_length():
         "new_col_1": hdmf.VectorData(value=np.arange(100)),
         "new_col_1_index": hdmf.VectorIndex(value=np.arange(0, 100, 5) + 5),
     }
-    with pytest.raises(ValidationError, pattern="Columns are not of equal length"):
+    with pytest.raises(ValidationError, match="Columns are not of equal length"):
         _ = MyDT(**cols)
 
 
@@ -324,6 +324,15 @@ def test_vectordata_indexing():
     assert data[0] == 1
     data[0] = 0
 
+    # indexes by themselves are the same
+    index_notarget = hdmf.VectorIndex(value=index_array)
+    assert index_notarget[0] == index_array[0]
+    assert all(index_notarget[0:3] == index_array[0:3])
+    oldval = index_array[0]
+    index_notarget[0] = 5
+    assert index_notarget[0] == 5
+    index_notarget[0] = oldval
+
     index = hdmf.VectorIndex(value=index_array, target=data)
     data._index = index
 
@@ -338,8 +347,16 @@ def test_vectordata_indexing():
             assert all(subitem == i)
 
     # setting uses the same indexing logic
-    data[0][:] = 5
+    data[0] = 5
     assert all(data[0] == 5)
+    data[0:3] = [5, 4, 3]
+    assert all(data[0] == 5)
+    assert all(data[1] == 4)
+    assert all(data[2] == 3)
+    data[0:3] = 6
+    assert all(data[0] == 6)
+    assert all(data[1] == 6)
+    assert all(data[2] == 6)
 
 
 def test_vectordata_getattr():