def __divide_all(self, vertices, triangles):
# Subdivide each triangle in the old approximation and normalize
# the new points thus generated to lie on the surface of the unit
# sphere.
# Each input triangle with vertices labelled [0,1,2] as shown
# below will be turned into four new triangles:
#
# Make new points
# a = (0+2)/2
# b = (0+1)/2
# c = (1+2)/2
# 1
# /\ Normalize a, b, c
# / \
# b/____\ c Construct new triangles
# /\ /\ t1 [0,b,a]
# / \ / \ t2 [b,1,c]
# /____\/____\ t3 [a,b,c]
# 0 a 2 t4 [a,c,2]
v = []
for tri in triangles:
v0 = vertices[tri[0]]
v1 = vertices[tri[1]]
v2 = vertices[tri[2]]
a = vm.unit_vector((v0 + v2) * 0.5)
b = vm.unit_vector((v0 + v1) * 0.5)
c = vm.unit_vector((v1 + v2) * 0.5)
v += [v0, b, a, b, v1, c, a, b, c, a, c, v2]
return v, np.arange(len(v)).reshape((-1, 3))
def calculate_vertice_norms(self):
self._vertices_norm = []
for v_id in range(len(self._vertices)):
v_norm = np.array([0.,0.,0.])
for face in self._faces:
if face.contains_vertex(v_id):
v_norm += face._norm
self._vertices_norm.append(VecMath.unit_vector(v_norm))
model.remove_face(face)
model.merge(embedded_model)
return embedded_model
if __name__ == "__main__":
radius = 100.
sphere = primitives.Sphere(radius)
obj_model = sphere.triangulate(recursion_level=2)
for iter in range(0,4):
print(f'noise iteration({iter})')
for idx, vertex in enumerate(obj_model._vertices):
l = min([edge.length for edge in obj_model.get_edges_with_vertex(idx)]) * .1
rnd_d = get_random_norm()
dir = VecMath.unit_vector(vertex)
transf = MtxMath.conv_to_euclid(VecMath.rotate_fromto_matrix(np.array([0., 0., 1.]), dir))
tv = transf * (rnd_d*euclid.Vector3(l,l,10))
vertex += tv
# sphere_model.triangulate()
ObjExporter.write(obj_model, f'./export/_sphere_noise.obj')
print(f'Faces: {len(obj_model._faces)}')
print(f'Vertices: {len(obj_model._vertices)}')
bbox_size = obj_model._size
print(f'Boundingbox: [{bbox_size[0]}, {bbox_size[1]}, {bbox_size[2]}]')
target_lid_size = 100. #mm^2
faceted_model = Model()
def from_points(cls, p0, p1, p2, norm_dir=1.):
""" Create a plane from 3 points that span the plane """
return Plane(p0, vm.unit_vector(np.cross(p1 - p0, p2 - p0) * norm_dir))
d = euclid.Vector3(random.uniform(0, 1), random.uniform(0, 1),
0.).normalize()
# d = euclid.Vector3(0., 0., 0.)
# d.x = random.uniform(-1, 1)
# d.y = random.uniform(-1, 1)
# d.z = random.uniform(-.1, .1)
# d.z = 1.
return d
if __name__ == "__main__":
radius = 100.
sphere = primitives.Sphere(radius)
sphere_model = sphere.triangulate(recursion_level=2)
for iter in range(0, 4):
print(f'noise iteration({iter})')
for idx, vertex in enumerate(sphere_model._vertices):
l = min([
edge.length for edge in sphere_model.get_edges_with_vertex(idx)
]) * .1
rnd_d = get_random_norm()
dir = vm.unit_vector(vertex)
transf = MtxMath.conv_to_euclid(
vm.rotate_fromto_matrix(np.array([0., 0., 1.]), dir))
tv = transf * (rnd_d * euclid.Vector3(l, l, 10))
vertex += tv
# sphere_model.triangulate()
ObjExporter.write(sphere_model, f'./export/_sphere_noise.obj')
def calculate_norm(self, vertices):
self._norm = np.cross(
vertices[self._vertex_ids[1]] - vertices[self._vertex_ids[0]],
vertices[self._vertex_ids[2]] - vertices[self._vertex_ids[0]])
self._norm = VecMath.unit_vector(self._norm)
def test_unit_vector(self):
self.assertEqual(
np.linalg.norm(VecMath.unit_vector(np.array([1., 2., 3.]))), 1.)
