def test_not_connected_mesh(self, device, dtype):
num_vertices = 4
faces = torch.tensor([[0, 1, 2]], dtype=torch.long, device=device)
result = mesh.uniform_laplacian(num_vertices, faces)
# Any row and column related to V3 is zeros.
assert torch.equal(result[3, :3],
torch.zeros((3), device=device, dtype=torch.float))
assert torch.equal(result[:3, 3],
torch.zeros((3), device=device, dtype=torch.float))
def test_uniform_laplacian(self, device, dtype):
num_vertices = 5
faces = torch.tensor([[1, 3, 2], [1, 4, 0]],
dtype=torch.long,
device=device)
output = mesh.uniform_laplacian(num_vertices, faces)
expected = torch.tensor(
[[-1, 0.5, 0, 0, 0.5], [0.25, -1, 0.25, 0.25, 0.25],
[0, 0.5, -1, 0.5, 0], [0, 0.5, 0.5, -1, 0], [0.5, 0.5, 0, 0, -1]],
dtype=torch.float,
device=device)
assert torch.equal(output, expected)
def test_not_connected_mesh(self, device, dtype):
num_vertices = 5
faces = torch.tensor([[0, 1, 2]], dtype=torch.long, device=device)
with pytest.raises(ValueError,
match="The mesh is not fully connected."):
result = mesh.uniform_laplacian(num_vertices, faces)