diff --git a/tests/next_tests/integration_tests/cases.py b/tests/next_tests/integration_tests/cases.py index 3bc4c8a077..f70d2e2f17 100644 --- a/tests/next_tests/integration_tests/cases.py +++ b/tests/next_tests/integration_tests/cases.py @@ -133,13 +133,6 @@ def field( sizes: dict[gtx.Dimension, int], dtype: np.typing.DTypeLike, ) -> FieldValue: - if hasattr(self.value, "__array__"): - return constructors.as_field( - common.domain(sizes), - np.full(tuple(sizes.values()), self.value), - dtype=dtype, - allocator=backend, - ) return constructors.full( domain=common.domain(sizes), fill_value=self.value, diff --git a/tests/next_tests/integration_tests/feature_tests/ffront_tests/test_gt4py_builtins.py b/tests/next_tests/integration_tests/feature_tests/ffront_tests/test_gt4py_builtins.py index b170a44622..4d910cdfdb 100644 --- a/tests/next_tests/integration_tests/feature_tests/ffront_tests/test_gt4py_builtins.py +++ b/tests/next_tests/integration_tests/feature_tests/ffront_tests/test_gt4py_builtins.py @@ -138,10 +138,7 @@ def conditional_nested_tuple( return where(mask, ((a, b), (b, a)), ((5.0, 7.0), (7.0, 5.0))) size = cartesian_case.default_sizes[IDim] - bool_field = np.random.choice(a=[False, True], size=(size)) - mask = cases.allocate(cartesian_case, conditional_nested_tuple, "mask").strategy( - cases.ConstInitializer(bool_field) - )() + mask = cartesian_case.as_field([IDim], np.random.choice(a=[False, True], size=size)) a = cases.allocate(cartesian_case, conditional_nested_tuple, "a")() b = cases.allocate(cartesian_case, conditional_nested_tuple, "b")() @@ -211,10 +208,7 @@ def conditional( return where(mask, a, b) size = cartesian_case.default_sizes[IDim] - bool_field = np.random.choice(a=[False, True], size=(size)) - mask = cases.allocate(cartesian_case, conditional, "mask").strategy( - cases.ConstInitializer(bool_field) - )() + mask = cartesian_case.as_field([IDim], np.random.choice(a=[False, True], size=(size))) a = cases.allocate(cartesian_case, conditional, "a")() b = cases.allocate(cartesian_case, conditional, "b")() out = cases.allocate(cartesian_case, conditional, cases.RETURN)() @@ -228,10 +222,7 @@ def conditional_promotion(mask: cases.IBoolField, a: cases.IFloatField) -> cases return where(mask, a, 10.0) size = cartesian_case.default_sizes[IDim] - bool_field = np.random.choice(a=[False, True], size=(size)) - mask = cases.allocate(cartesian_case, conditional_promotion, "mask").strategy( - cases.ConstInitializer(bool_field) - )() + mask = cartesian_case.as_field([IDim], np.random.choice(a=[False, True], size=(size))) a = cases.allocate(cartesian_case, conditional_promotion, "a")() out = cases.allocate(cartesian_case, conditional_promotion, cases.RETURN)() diff --git a/tests/next_tests/integration_tests/feature_tests/ffront_tests/test_math_unary_builtins.py b/tests/next_tests/integration_tests/feature_tests/ffront_tests/test_math_unary_builtins.py index 35a8b2a959..64c009cb12 100644 --- a/tests/next_tests/integration_tests/feature_tests/ffront_tests/test_math_unary_builtins.py +++ b/tests/next_tests/integration_tests/feature_tests/ffront_tests/test_math_unary_builtins.py @@ -103,13 +103,8 @@ def binary_xor(inp1: cases.IBoolField, inp2: cases.IBoolField) -> cases.IBoolFie return inp1 ^ inp2 size = cartesian_case.default_sizes[IDim] - bool_field = np.random.choice(a=[False, True], size=(size)) - inp1 = cases.allocate(cartesian_case, binary_xor, "inp1").strategy( - cases.ConstInitializer(bool_field) - )() - inp2 = cases.allocate(cartesian_case, binary_xor, "inp2").strategy( - cases.ConstInitializer(bool_field) - )() + inp1 = cartesian_case.as_field([IDim], np.random.choice(a=[False, True], size=(size))) + inp2 = cartesian_case.as_field([IDim], np.random.choice(a=[False, True], size=(size))) out = cases.allocate(cartesian_case, binary_xor, cases.RETURN)() cases.verify(cartesian_case, binary_xor, inp1, inp2, out=out, ref=inp1 ^ inp2) @@ -120,13 +115,8 @@ def bit_and(inp1: cases.IBoolField, inp2: cases.IBoolField) -> cases.IBoolField: return inp1 & inp2 size = cartesian_case.default_sizes[IDim] - bool_field = np.random.choice(a=[False, True], size=(size)) - inp1 = cases.allocate(cartesian_case, bit_and, "inp1").strategy( - cases.ConstInitializer(bool_field) - )() - inp2 = cases.allocate(cartesian_case, bit_and, "inp2").strategy( - cases.ConstInitializer(bool_field) - )() + inp1 = cartesian_case.as_field([IDim], np.random.choice(a=[False, True], size=(size))) + inp2 = cartesian_case.as_field([IDim], np.random.choice(a=[False, True], size=(size))) out = cases.allocate(cartesian_case, bit_and, cases.RETURN)() cases.verify(cartesian_case, bit_and, inp1, inp2, out=out, ref=inp1 & inp2) @@ -137,13 +127,8 @@ def bit_or(inp1: cases.IBoolField, inp2: cases.IBoolField) -> cases.IBoolField: return inp1 | inp2 size = cartesian_case.default_sizes[IDim] - bool_field = np.random.choice(a=[False, True], size=(size)) - inp1 = cases.allocate(cartesian_case, bit_or, "inp1").strategy( - cases.ConstInitializer(bool_field) - )() - inp2 = cases.allocate(cartesian_case, bit_or, "inp2").strategy( - cases.ConstInitializer(bool_field) - )() + inp1 = cartesian_case.as_field([IDim], np.random.choice(a=[False, True], size=(size))) + inp2 = cartesian_case.as_field([IDim], np.random.choice(a=[False, True], size=(size))) out = cases.allocate(cartesian_case, bit_or, cases.RETURN)() cases.verify(cartesian_case, bit_or, inp1, inp2, out=out, ref=inp1 | inp2) @@ -165,10 +150,7 @@ def tilde_fieldop(inp1: cases.IBoolField) -> cases.IBoolField: return ~inp1 size = cartesian_case.default_sizes[IDim] - bool_field = np.random.choice(a=[False, True], size=(size)) - inp1 = cases.allocate(cartesian_case, tilde_fieldop, "inp1").strategy( - cases.ConstInitializer(bool_field) - )() + inp1 = cartesian_case.as_field([IDim], np.random.choice(a=[False, True], size=(size))) out = cases.allocate(cartesian_case, tilde_fieldop, cases.RETURN)() cases.verify(cartesian_case, tilde_fieldop, inp1, out=out, ref=~inp1) @@ -179,10 +161,7 @@ def not_fieldop(inp1: cases.IBoolField) -> cases.IBoolField: return not inp1 size = cartesian_case.default_sizes[IDim] - bool_field = np.random.choice(a=[False, True], size=(size)) - inp1 = cases.allocate(cartesian_case, not_fieldop, "inp1").strategy( - cases.ConstInitializer(bool_field) - )() + inp1 = cartesian_case.as_field([IDim], np.random.choice(a=[False, True], size=(size))) out = cases.allocate(cartesian_case, not_fieldop, cases.RETURN)() cases.verify(cartesian_case, not_fieldop, inp1, out=out, ref=~inp1)