def random_vector(r): v = [ myrandom.uniform(-1, 1), myrandom.uniform(-1, 1), myrandom.uniform(-1, 1) ] return _gfrd.normalize(v, r)
def random_vector(r): # v, s = [0.0, 0.0, 0.0], 2.0 # while s > 1.0: # v[0] = myrandom.uniform (-1, 1) # v[1] = myrandom.uniform (-1, 1) # s = v[0] * v[0] + v[1] * v[1] # v[2] = -1 + 2 * s # a = 2 * numpy.sqrt(1 - s) # v[0] *= a # v[1] *= a cos_theta = myrandom.uniform(-1, 1) sin_theta = numpy.sqrt(1 - cos_theta * cos_theta) phi = myrandom.uniform(0, Pi2) sin_phi, cos_phi = math.sin(phi), math.cos(phi) # sincos v = [sin_theta * cos_phi, sin_theta * sin_phi, cos_theta] return _gfrd.normalize(v, r)
def normalize(a, l=1): return _gfrd.normalize(a, l)
def random_vector(r): v = [myrandom.uniform(-1,1), myrandom.uniform(-1,1), myrandom.uniform(-1,1)] return _gfrd.normalize(v, r)