def test_detection_type_arrays(self):
rng = np.random.RandomState(321)
variables = [
Scalar.uint(),
Scalar.int(),
Scalar.float(),
Scalar.double()
]
variables += [
Vector(n, dtype)
for n, dtype in itertools.product(range(2, 5), DataType.ALL)
]
for definition, layout, _ in itertools.product(
variables, [Layout.STD140, Layout.STD430], range(3)):
container = Struct(
[Array(definition, Random.shape(rng, 3, 5), layout)], layout)
glsl = self.build_glsl_program(
((container, 0, BufferUsage.STORAGE_BUFFER), ))
shader = self.shader_from_txt(glsl, verbose=False)
shader.inspect()
detected_definition, _ = shader.get_block(0)
self.assertTrue(container.compare(detected_definition, quiet=True))
if isinstance(definition, Vector):
if definition.length(
) < 3 and definition.dtype != DataType.DOUBLE:
self.assertEqual(detected_definition.layout, layout)
def test_nested_with_arrays_of_structs(self):
rng = np.random.RandomState(123)
simple = [Scalar.uint(), Scalar.int(), Scalar.float(), Scalar.double()]
simple += [
Vector(n, dtype)
for n, dtype in itertools.product(range(2, 5), DataType.ALL)
]
for layout, _ in itertools.product([Layout.STD140, Layout.STD430],
range(10)):
matrices = [
Matrix(n, m, dtype, layout)
for n, m, dtype in itertools.product(range(2, 5), range(
2, 5), [DataType.FLOAT, DataType.DOUBLE])
]
simple_and_matrices = simple + matrices
struct = Struct(rng.choice(simple_and_matrices,
size=4,
replace=False),
layout,
type_name="SomeStruct")
structs = [struct]
arrays = [Array(struct, Random.shape(rng, 2, 3), layout)]
for _ in range(2):
members = [arrays[-1]] + rng.choice(
simple_and_matrices, size=3, replace=False).tolist()
structs.append(
Struct(rng.permutation(members),
layout,
type_name="SomeStruct{}".format(len(structs))))
arrays.append(
Array(structs[-1], Random.shape(rng, 2, 3), layout))
container = structs[-1]
structs = structs[:-1]
self.run_test(container, structs, BufferUsage.STORAGE_BUFFER)
if layout == Layout.STD140:
self.run_test(container, structs, BufferUsage.UNIFORM_BUFFER)
def test_array_of_matrices(self):
# skipping ROW_MAJOR order for now since the glsl generation does not support it
rng = np.random.RandomState(123)
matrix_combinations = itertools.product(range(2, 5), range(
2, 5), [DataType.FLOAT, DataType.DOUBLE])
for (n, m, dtype), layout, _ in itertools.product(
matrix_combinations, [Layout.STD140, Layout.STD430], range(3)):
matrix = Matrix(n, m, dtype, layout)
container = Struct(
[Array(matrix, Random.shape(rng, 3, 5), layout)], layout)
self.run_test(container, [], BufferUsage.STORAGE_BUFFER)
def test_detection_type_arrays_of_matrices(self):
rng = np.random.RandomState(321)
matrix_attributes = itertools.product(range(2, 5), range(2, 5), [DataType.FLOAT, DataType.DOUBLE])
for (n, m, dtype), layout, _ in itertools.product(matrix_attributes, [Layout.STD140, Layout.STD430], range(3)):
matrix = Matrix(n, m, dtype, layout)
container = Struct([Array(matrix, Random.shape(rng, 3, 5), layout)], layout)
glsl = self.build_glsl_program(((container, 0, BufferUsage.STORAGE_BUFFER),))
shader = self.shader_from_txt(glsl, verbose=False)
shader.inspect()
detected_definition, _ = shader.code.get_block(0)
self.assertTrue(container.compare(detected_definition, quiet=True))
def test_array_of_vectors(self):
rng = np.random.RandomState(123)
vector_types = [
Vector(n, dtype)
for n, dtype in itertools.product(range(2, 5), DataType.ALL)
]
for definition, layout, _ in itertools.product(
vector_types, [Layout.STD140, Layout.STD430], range(5)):
container = Struct(
[Array(definition, Random.shape(rng, 3, 5), layout)], layout)
self.run_test(container, [], BufferUsage.STORAGE_BUFFER)
if layout == Layout.STD140:
self.run_test(container, [], BufferUsage.UNIFORM_BUFFER)
def test_array_of_scalars(self):
rng = np.random.RandomState(123)
scalar_types = [
Scalar.uint(),
Scalar.int(),
Scalar.float(),
Scalar.double()
]
for definition, layout, _ in itertools.product(
scalar_types, [Layout.STD140, Layout.STD430], range(5)):
container = Struct(
[Array(definition, Random.shape(rng, 5, 7), layout)], layout)
self.run_test(container, [], BufferUsage.STORAGE_BUFFER)
if layout == Layout.STD140:
self.run_test(container, [], BufferUsage.UNIFORM_BUFFER)
def test_array_of_structs(self):
rng = np.random.RandomState(123)
simple = [Scalar.uint(), Scalar.int(), Scalar.float(), Scalar.double()]
simple += [
Vector(n, dtype)
for n, dtype in itertools.product(range(2, 5), DataType.ALL)
]
for layout, _ in itertools.product([Layout.STD140, Layout.STD430],
range(5)):
struct = Struct(rng.choice(simple, size=3, replace=False),
layout,
type_name="SomeStruct")
array = Array(struct, Random.shape(rng, 3, 5), layout)
container = Struct([array], layout)
self.run_test(container, [struct], BufferUsage.STORAGE_BUFFER)
if layout == Layout.STD140:
self.run_test(container, [struct], BufferUsage.UNIFORM_BUFFER)