def test_pca_and_mds():
"""
"""
X = randn(10,3)
M = MDS(X, rdim=2)
u1 = M.train()
P = PCA(X,rdim=2)
u2 = P.train()
eta = np.dot(u1.T,u2)
delta = eta - np.diag(np.diag(eta))
print delta, eta
assert (np.sum(delta**2)<1.e-12*np.sum(eta**2))
def test_pca():
"""
Test of the multi-dimensional scaling algorithm
"""
X = randn(10,3)
P = PCA(X, rdim=2)
u = P.train()
x = X[:2]
a = P.test(x)
eps = 1.e-12
test = np.sum(a-u[:2])**2<eps
print a, u[:2]
assert test