def test_empty_mesh(self):
"""
What happens when we call functions on an empty mesh?
"""
mesh = Mesh(np.zeros((0, 3), np.float32), np.zeros((0, 3), int))
mesh.simplify(1.0)
assert len(mesh.vertices_zyx) == len(mesh.normals_zyx) == len(
mesh.faces) == 0
mesh.simplify(0.1)
assert len(mesh.vertices_zyx) == len(mesh.normals_zyx) == len(
mesh.faces) == 0
mesh.laplacian_smooth(0)
assert len(mesh.vertices_zyx) == len(mesh.normals_zyx) == len(
mesh.faces) == 0
mesh.laplacian_smooth(2)
assert len(mesh.vertices_zyx) == len(mesh.normals_zyx) == len(
mesh.faces) == 0
mesh.stitch_adjacent_faces()
assert len(mesh.vertices_zyx) == len(mesh.normals_zyx) == len(
mesh.faces) == 0
mesh.serialize(fmt='obj')
assert len(mesh.vertices_zyx) == len(mesh.normals_zyx) == len(
mesh.faces) == 0
mesh.serialize(fmt='drc')
assert len(mesh.vertices_zyx) == len(mesh.normals_zyx) == len(
mesh.faces) == 0
mesh.compress()
concatenate_meshes((mesh, mesh))
assert len(mesh.vertices_zyx) == len(mesh.normals_zyx) == len(
mesh.faces) == 0
def test_mismatches(self):
mesh_1, mesh_2, mesh_3 = self.mesh_1, self.mesh_2, self.mesh_3
mesh_1.recompute_normals()
# let's really mess up mesh 3 -- give it the wrong number of normals
mesh_3.recompute_normals()
mesh_3.normals_zyx = mesh_3.normals_zyx[:-1]
try:
_combined_mesh = concatenate_meshes((mesh_1, mesh_2, mesh_3))
except RuntimeError:
pass
else:
assert False, "Expected a RuntimeError, but did not see one."
def test_concatenate(self):
mesh_1, mesh_2, mesh_3, mesh_4 = self.mesh_1, self.mesh_2, self.mesh_3, self.mesh_4
vertexes_1, vertexes_2, vertexes_3 = self.vertexes_1, self.vertexes_2, self.vertexes_3
faces_1, faces_2, faces_3 = self.faces_1, self.faces_2, self.faces_3
combined_mesh = concatenate_meshes((mesh_1, mesh_2, mesh_3, mesh_4))
assert (combined_mesh.vertices_zyx == np.concatenate(
(vertexes_1, vertexes_2, vertexes_3))).all()
expected_faces = np.concatenate((faces_1, faces_2, faces_3))
expected_faces[len(faces_1):] += len(vertexes_1)
expected_faces[len(faces_1) + len(faces_2):] += len(vertexes_2)
assert (combined_mesh.faces == expected_faces).all()
def test_concatenate(tiny_meshes):
mesh_1, mesh_2, mesh_3, mesh_4 = tiny_meshes
vertexes_1, vertexes_2, vertexes_3 = mesh_1.vertices_zyx, mesh_2.vertices_zyx, mesh_3.vertices_zyx
faces_1, faces_2, faces_3 = mesh_1.faces, mesh_2.faces, mesh_3.faces
combined_mesh = concatenate_meshes((mesh_1, mesh_2, mesh_3, mesh_4))
assert (combined_mesh.vertices_zyx == np.concatenate(
(vertexes_1, vertexes_2, vertexes_3))).all()
expected_faces = np.concatenate((faces_1, faces_2, faces_3))
expected_faces[len(faces_1):] += len(vertexes_1)
expected_faces[len(faces_1) + len(faces_2):] += len(vertexes_2)
assert (combined_mesh.faces == expected_faces).all()
def test_normals_guarantees(self):
"""
Member functions have guarantees about whether normals are present or absent after the function runs.
- simplify(): Always present afterwards
- laplacian_smooth(): Always present afterwards
- stitch_adjacent_faces(): Present afterwards IFF they were present before.
"""
data_box = np.array(self.data_box)
FACTOR = 2
data_box *= FACTOR
mesh_orig = Mesh.from_binary_vol(self.binary_vol, data_box)
mesh = copy.deepcopy(mesh_orig)
assert mesh.normals_zyx.shape[0] > 1
# Verify normals are always present after simplification,
# Regardless of whether or not they were present before,
# or if simplification was even performed.
mesh.simplify(1.0)
assert mesh.normals_zyx.shape[0] > 1
mesh.simplify(0.5)
assert mesh.normals_zyx.shape[0] > 1
mesh.drop_normals()
mesh.simplify(0.5)
assert mesh.normals_zyx.shape[0] > 1
# Verify normals are always present after smoothing,
# Regardless of whether or not they were present before,
# or if smoothing was even performed.
mesh = copy.deepcopy(mesh_orig)
mesh.laplacian_smooth(0)
assert mesh.normals_zyx.shape[0] > 1
mesh.laplacian_smooth(2)
assert mesh.normals_zyx.shape[0] > 1
mesh.drop_normals()
mesh.laplacian_smooth(2)
assert mesh.normals_zyx.shape[0] > 1
# Verify that the presence or absence of normals is the SAME after stitching,
# Whether or not stitching had any effect.
# no stitching, keep normals
mesh = copy.deepcopy(mesh_orig)
stitching_performed = mesh.stitch_adjacent_faces()
assert not stitching_performed
assert mesh.normals_zyx.shape[0] > 1
# no stitching, no normals in the first place
mesh.drop_normals()
stitching_performed = mesh.stitch_adjacent_faces()
assert not stitching_performed
assert mesh.normals_zyx.shape[0] == 0
# stitching, generate normals
mesh = copy.deepcopy(mesh_orig)
duplicated_mesh = concatenate_meshes([mesh, mesh])
assert duplicated_mesh.normals_zyx.shape[0] > 1
stitching_performed = duplicated_mesh.stitch_adjacent_faces()
assert stitching_performed
assert duplicated_mesh.normals_zyx.shape[0] > 1
# stitching, no normals in the first place
mesh = copy.deepcopy(mesh_orig)
duplicated_mesh = concatenate_meshes([mesh, mesh])
duplicated_mesh.drop_normals()
stitching_performed = duplicated_mesh.stitch_adjacent_faces()
assert stitching_performed
assert duplicated_mesh.normals_zyx.shape[0] == 0