def test_handles_convex_polygons(self):
"""
The original Delaunay algorithm always outputs a convex polygon
so, let us make sure that the boundary stays the same if it is concave
"""
v1 = Vertex(0, 0, 10, 0)
v2 = Vertex(1, 10, 0, 0)
v3 = Vertex(2, 4, 0, 0)
v4 = Vertex(3, 4, 4, 0)
face = [v1, v2, v3, v4]
triangles = triangulate(face)
self.assertEqual(len(triangles), 2)
# There is only one way to triangulate this polygon, so that it preserves the boundary
tri1 = [v1, v2, v4]
tri2 = [v2, v3, v4]
tri1_present = False
if self.isTrianglesEqual(tri1, triangles[0]):
tri1_present = True
elif self.isTrianglesEqual(tri1, triangles[1]):
tri1_present = True
tri2_present = False
if self.isTrianglesEqual(tri2, triangles[0]):
tri2_present = True
elif self.isTrianglesEqual(tri2, triangles[1]):
tri2_present = True
self.assertTrue(tri1_present)
self.assertTrue(tri2_present)
def test_does_not_change_triangular_face(self):
face = [Vertex(0, 1, 0, 0), Vertex(1, 2, 0, 0), Vertex(2, 0, 2, 0)]
triangulated = triangulate(face)
self.assertEqual(len(triangulated), 1)
triangulated_pos_set = set(map(lambda v: v.pos, triangulated[0]))
pos_set = set(map(lambda v: v.pos, face))
self.assertEqual(pos_set, triangulated_pos_set)
def test_triangulates_square_along_yz_plane(self):
face = [
Vertex(0, 0, 0, 0),
Vertex(1, 0, 1, 0),
Vertex(2, 0, 1, 1),
Vertex(3, 0, 0, 1),
]
triangulated = triangulate(face)
diagonal1 = np.array([0, 1, 1])
diagonal2 = np.array([0, -1, 1])
self.assertTriangulatesSquare(triangulated, diagonal1, diagonal2)
def test_handles_numerical_stability_in_disjoint_check(self):
"""
Looks strange, this test case is a real-life scenario that happened.
Disjointness check is "too-precise", sometimes even for convex polygons, it
would return too little triangles from the triangulation
"""
v1 = Vertex(0, 3, 0, 0)
v2 = Vertex(1, 4, 0, 0)
v3 = Vertex(2, 4.571428571428572, 1.428571428571428, 0)
v4 = Vertex(3, 3.047619047619047, 0.9523809523809523, 0)
face = [v1, v2, v3, v4]
triangles = triangulate(face)
self.assertEqual(len(triangles), 2)
def create_faces(vertices, edges, faces_vertices):
edges_bag = {} # TODO: Think of a better solution for this edges_bag
for e in edges:
edges_bag[(e.v1.id, e.v2.id)] = e
faces = []
for i, vertices_index in enumerate(faces_vertices):
face_to_triangulate = list(map(lambda x: vertices[x], vertices_index))
triangles = triangulate(face_to_triangulate)
for face_vertices in triangles:
face = Face(i, *face_vertices) # TODO: ? This makes id in Face not unique (which might not be a problem)
face_edges = zip(face_vertices, face_vertices[1:] + [face_vertices[0]])
for p in face_edges:
v1 = p[0].id
v2 = p[1].id
# Introduce new edges
if (v1, v2) not in edges_bag and (v2, v1) not in edges_bag:
edge = Edge(-1, p[0], p[1], EDGE_FLAT)
edges.append(edge)
edges_bag[(v1, v2)] = edge
if (v1, v2) in edges_bag:
edges_bag[(v1, v2)].face_left = face
elif (v2, v1) in edges_bag:
edges_bag[(v2, v1)].face_right = face
else:
raise RuntimeError("Impossible. You messed up edges map. ")
faces.append(face)
return faces