Allow query conditions on dense array dimensions

tiledb/query_condition.py

@@ -22,7 +22,7 @@
 class QueryCondition:
     """
     Class representing a TileDB query condition object for attribute and dimension
-    (sparse arrays only) filtering pushdown.
+    filtering pushdown.
 
     A query condition is set with a string representing an expression
     as defined by the grammar below. A more straight forward example of usage is
@@ -355,12 +355,6 @@ def get_variable_from_node(self, node: QueryConditionNodeElem) -> Any:
                 f"Incorrect type for variable name: {ast.dump(variable_node)}"
             )
 
-        if self.array.schema.domain.has_dim(variable) and not self.array.schema.sparse:
-            raise TileDBError(
-                "Cannot apply query condition to dimensions on dense arrays. "
-                f"{variable} is a dimension."
-            )
-
         if isinstance(node, ast.Call):
             if node.func.id == "attr" and not self.array.schema.has_attr(variable):
                 raise TileDBError(f"{node.func.id} is not an attribute.")

tiledb/tests/test_query_condition.py

@@ -694,11 +694,26 @@ def test_deprecate_attr_cond(self):
 
     def test_on_dense_dimensions(self):
         with tiledb.open(self.create_input_array_UIDSA(sparse=False)) as A:
-            with pytest.raises(tiledb.TileDBError) as excinfo:
-                A.query(cond="2 <= d < 6")[:]
-            assert (
-                "Cannot apply query condition to dimensions on dense arrays"
-            ) in str(excinfo.value)
+            result = A.query(cond="2 <= d < 6")[:]
+            expected = A[2:6]
+            assert_array_equal(result["U"][1:5], expected["U"])
+
+            # Cells outside the condition should be filled with fill values
+            assert result["U"][0] == np.iinfo(np.uint32).max
+
+    def test_on_dense_dimensions_combined_with_attrs(self):
+        with tiledb.open(self.create_input_array_UIDSA(sparse=False)) as A:
+            result = A.query(cond="2 <= d < 6 and U > 3")[:]
+            full = A[:]
+
+            # Build a mask matching the query condition "2 <= d < 6 and U > 3"
+            d = np.arange(1, 11, dtype=np.uint32)
+            match = (d >= 2) & (d < 6) & (full["U"] > 3)
+            fill = np.iinfo(np.uint32).max
+
+            # Matching cells keep their values, non-matching cells get fill
+            assert_array_equal(result["U"][match], full["U"][match])
+            assert_array_equal(result["U"][~match], fill)
 
     def test_on_sparse_dimensions(self):
         with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A: