def test_selfintersects(self):
tree_handle_no = aabb_normals.aabbtree_n_compute(self.simple_m.v,
self.simple_m.f.astype(np.uint32).copy(),
0.5)
self.assertTrue(aabb_normals.aabbtree_n_selfintersects(tree_handle_no) == 0)
tree_handle_yes = aabb_normals.aabbtree_n_compute(self.self_int_cyl_m.v,
self.self_int_cyl_m.f.astype(np.uint32).copy(),
0.5)
self.assertTrue(aabb_normals.aabbtree_n_selfintersects(tree_handle_yes) == (2 * 8))
def test_cylinders(self):
create_tree = lambda eps: aabb_normals.aabbtree_n_compute(
self.cylinder_m.v,
self.cylinder_m.f.astype(np.uint32).copy(), eps)
tree_handle_no_normals = create_tree(0)
tree_handle_normals = create_tree(10)
query_v = self.cylinder_trans_m.v
tri_n = NormalizeRows(
TriToScaledNormal(self.cylinder_trans_m.v,
self.cylinder_trans_m.f))
query_n = np.zeros(self.cylinder_trans_m.v.shape)
for i_f in range(self.cylinder_trans_m.f.shape[0]):
query_n[self.cylinder_trans_m.f[i_f, :], :] += tri_n[i_f, :]
query_n = NormalizeRows(query_n)
closest_tri, _ = aabb_normals.aabbtree_n_nearest(
tree_handle_no_normals, query_v, query_n)
# all closest triangles are the two extremes
self.assertTrue(np.unique(closest_tri).shape[0] <= 4)
closest_tri_n, _ = aabb_normals.aabbtree_n_nearest(
tree_handle_normals, query_v, query_n)
# there are four triangles that do not need to be reached, in the center and in the extremes
self.assertTrue(
np.unique(closest_tri_n).shape[0] >= (self.cylinder_m.f.shape[0] -
4))
def test_dist_classic(self):
tree_handle = aabb_normals.aabbtree_n_compute(
self.simple_m.v,
self.simple_m.f.astype(np.uint32).copy(), 0.0)
query_v = np.array([[0.5, 0.1, 0.25], [0.5, 0.1, 0.25]])
query_n = np.array([[0.0, 1.0, 0.0], [1.0, 0.0, 0.0]])
closest_tri, closest_p = aabb_normals.aabbtree_n_nearest(
tree_handle, query_v, query_n)
self.assertTrue((closest_tri == np.array([[0, 0]])).all())
self.assertTrue((closest_p == query_v).all())