def test_mixture_em():
model = MixtureModel(k = 2, d = 3, M = array([[0.7, 0.3],[0.2, 0.3],[0.1, 0.4]]), w = array([0.6,0.4]))
k, d, M, w = model["k"], model["d"], model["M"], model["w"]
N = 1e5
xs = model.sample(N)
lhood, _, (params, w_true) = MixtureModelEM(k, d).run(xs, params=(M, w))
w_true, params = fix_parameters(M, params, w_true)
lhood_, _, (params_, w_guess) = MixtureModelEM(k, d).run(xs)
w_data, params_ = fix_parameters(M, params_, w_guess)
print "true", M
print "true lhood", model.llikelihood(xs)
print "with em*", params
print "em lhood*", lhood
print "em lhood*", model.using(M = params, w = w_true).llikelihood(xs)
print "error with em*", norm(M - params)/norm(M)
print "with em", params_
print "em lhood", lhood_
print "em lhood", model.using(M = params_, w = w_guess).llikelihood(xs)
print "error with em", norm(M - params_)/norm(M)
assert norm(M - params)/norm(M) < 1e-1
assert norm(M - params_)/norm(M) < 1e-1
