Switch to __array_ufunc__ as a way to avoid numpy broadcasting

Author: inducer

arraycontext/context.py

@@ -306,34 +306,6 @@ def _get_fake_numpy_namespace(self) -> Any:
     def __hash__(self) -> int:
         raise TypeError(f"unhashable type: '{type(self).__name__}'")
 
-    @abstractmethod
-    def empty(self,
-              shape: Union[int, Tuple[int, ...]],
-              dtype: "np.dtype[Any]") -> Array:
-        pass
-
-    @abstractmethod
-    def zeros(self,
-              shape: Union[int, Tuple[int, ...]],
-              dtype: "np.dtype[Any]") -> Array:
-        pass
-
-    def empty_like(self, ary: Array) -> Array:
-        from warnings import warn
-        warn(f"{type(self).__name__}.empty_like is deprecated and will stop "
-            "working in 2023. Prefer actx.np.zeros_like instead.",
-            DeprecationWarning, stacklevel=2)
-
-        return self.empty(shape=ary.shape, dtype=ary.dtype)
-
-    def zeros_like(self, ary: Array) -> Array:
-        from warnings import warn
-        warn(f"{type(self).__name__}.zeros_like is deprecated and will stop "
-            "working in 2023. Use actx.np.zeros_like instead.",
-            DeprecationWarning, stacklevel=2)
-
-        return self.zeros(shape=ary.shape, dtype=ary.dtype)
-
     @abstractmethod
     def from_numpy(self,
                    array: NumpyOrContainerOrScalar

test/test_arraycontext.py

@@ -136,7 +136,8 @@ def __init__(self, actx, data):
         self.array_context = actx
         self.data = data
 
-    __array_priority__ = 10
+    # prevent numpy broadcasting
+    __array_ufunc__ = None
 
     def __bool__(self):
         if len(self) == 1 and self.data[0].size == 1:
@@ -222,6 +223,8 @@ class MyContainer:
     momentum: np.ndarray
     enthalpy: Union[DOFArray, np.ndarray]
 
+    __array_ufunc__ = None
+
     @property
     def array_context(self):
         if isinstance(self.mass, np.ndarray):
@@ -1367,7 +1370,8 @@ def test_container_equality(actx_factory):
 class Foo:
     u: DOFArray
 
-    __array_priority__ = 1  # disallow numpy arithmetic to take precedence
+    # prevent numpy arithmetic from taking precedence
+    __array_ufunc__ = None
 
     @property
     def array_context(self):