def implicitFunction(self, p):
check_vector3_vectorized(p)
N = p.shape[0]
# print "self.lamda", self.lamda
theta = p[:, 2] * self.lamda
# print theta.shape
# assert theta.shape == (N,)
ca = np.cos(theta)
sa = np.sin(theta)
# print theta.shape, "theta"
# print theta
p2 = np.concatenate((
ca[:, np.newaxis] * p[:, 0, np.newaxis] -
sa[:, np.newaxis] * p[:, 1, np.newaxis],
sa[:, np.newaxis] * p[:, 0, np.newaxis] +
ca[:, np.newaxis] * p[:, 1, np.newaxis],
p[:, 2, np.newaxis],
),
axis=1)
v = self.base_object.implicitFunction(p2)
check_scalar_vectorized(v)
return v
def implicitFunction(self, p):
check_vector3_vectorized(p)
va = self.a.implicitFunction(p)
vb = self.b.implicitFunction(p)
c = 1.0 - np.greater(va, vb)
v = va * c + vb * (1 - c)
check_scalar_vectorized(v)
return v
def implicitFunction(self, p):
check_vector3_vectorized(p)
p = np.concatenate((p, np.ones((p.shape[0], 1))), axis=1)
tp = np.dot(self.invmatrix, np.transpose(p))
tp = np.transpose(tp)
tp = tp[:, :3]
v = self.base_object.implicitFunction(tp)
check_scalar_vectorized(v)
return v
def implicitFunction(self, pa):
check_vector3_vectorized(pa)
pa = np.concatenate((pa, np.ones((pa.shape[0], 1))), axis=1)
tp = np.dot(self.invmatrix, np.transpose(
pa)) # inefficient. todo: multiply from right => will be efficient
tp = np.transpose(tp)
tp = tp[:, :3]
v = self.sphere.implicitFunction(tp)
check_scalar_vectorized(v)
return v
def implicitFunction(self, p):
check_vector3_vectorized(p)
va = self.a.implicitFunction(p)
vb = self.b.implicitFunction(p)
fa = self.afactor
fb = self.bfactor
v = -(1 - (fa*np.exp(va) + fb*np.exp(vb)) / (fa+fb))
check_scalar_vectorized(v)
return v
def ellipsoid_point_and_gradient_vectorized(self,
m,
xa,
correctGrad,
center=None):
""" Checks if the point x is on the surface, and if the gradient is correct."""
e = vector3.Ellipsoid(m)
msg = "Ellipsoid(m): " + str(e)
va = e.implicitFunction(xa)
ga = e.implicitGradient(xa)
check_vector3_vectorized(ga)
N = xa.shape[0]
check_scalar_vectorized(va, N)
assert ga.ndim == 2
assert ga.shape == (N, 3)
assert correctGrad.shape == (N, 3)
correctScalar = 0
less_a = np.less(np.abs(va - correctScalar), TOLERANCE)
if not np.all(less_a):
sys.stderr.write("Some error:")
sys.stderr.write(xa)
sys.stderr.write(va)
sys.stderr.write(ga)
sys.stderr.write(e)
self.assertTrue(np.all(less_a),
("Implicit Function's scalar value incorrect"))
for i in range(ga.shape[0]):
(are_parallel, are_directed) = vectors_parallel_and_direction(
ga[i, :], correctGrad[i, :])
self.assertTrue(are_parallel,
"Incorrect gradient: not parallel " + msg)
self.assertTrue(are_directed,
"parallel but opposite directions " + msg)