def best_similarity_transform_test():
N = 20
for K in [3]: # TODO: multiple dimensions
X = np.random.randn(K, N)
R = random_rotation()
# R = np.eye(K)
t = np.random.randn(K, 1)
# print 'R: %s' % R
# print 't: %s' % t
Y = np.dot(R, X) + t
R2, t2 = best_similarity_transform(X, Y)
# print 'R2: %s' % R2
# print 't2: %s' % t2
Y2 = np.dot(R2, X) + t2
assert_allclose(R, R2, atol=1e-10)
assert_allclose(t, t2)
assert_allclose(Y, Y2)
def best_similarity_transform_test():
N = 20
for K in [3]: # TODO: multiple dimensions
X = np.random.randn(K, N)
R = random_rotation()
# R = np.eye(K)
t = np.random.randn(K, 1)
# print 'R: %s' % R
# print 't: %s' % t
Y = np.dot(R, X) + t
R2, t2 = best_similarity_transform(X, Y)
# print 'R2: %s' % R2
# print 't2: %s' % t2
Y2 = np.dot(R2, X) + t2
assert_allclose(R, R2, atol=1e-10)
assert_allclose(t, t2)
assert_allclose(Y, Y2)
def best_orthogonal_transform_test1():
X = random_directions(20)
R = random_rotation()
Y = np.dot(R, X)
R2 = best_orthogonal_transform(X, Y)
assert_allclose(R, R2)
def best_orthogonal_transform_test1():
X = random_directions(20)
R = random_rotation()
Y = np.dot(R, X)
R2 = best_orthogonal_transform(X, Y)
assert_allclose(R, R2)
