def test_packed_face_areas(self, device, dtype):
vertices = torch.tensor(
[[0., 0., 0.], [0., 0., 1.], [0., 1., 0.], [2., 0., 0.2],
[0., 0., 0.], [0., 1., 1.], [2., 0., 0.]],
device=device,
dtype=dtype)
faces = torch.tensor([[0, 1, 2], [1, 0, 3], [0, 1, 2]],
device=device,
dtype=torch.long)
first_idx_vertices = torch.LongTensor([0, 4, 7], device='cpu')
num_faces_per_mesh = torch.LongTensor([2, 1], device='cpu')
output = mesh.packed_face_areas(vertices, first_idx_vertices, faces,
num_faces_per_mesh)
expected_output = torch.tensor([0.5, 1., math.sqrt(2.)],
device=device,
dtype=dtype)
assert torch.allclose(output, expected_output)
def test_packed_sample_points_with_areas(self, packed_vertices_info,
packed_faces_info, dtype, device):
num_samples = 1000
vertices, first_idx_vertices = packed_vertices_info
faces, num_faces_per_mesh = packed_faces_info
face_areas = mesh.packed_face_areas(vertices, first_idx_vertices,
faces, num_faces_per_mesh)
points1, face_choices1 = with_seed(1234)(mesh.packed_sample_points)(
vertices, first_idx_vertices, faces, num_faces_per_mesh,
num_samples, face_areas)
points2, face_choices2 = with_seed(1234)(
mesh.packed_sample_points)(vertices, first_idx_vertices, faces,
num_faces_per_mesh, num_samples)
assert torch.allclose(points1, points2)
assert torch.equal(face_choices1, face_choices2)
