def test_vbgmm(verbose=0):
# perform the estimation of a gmm
n = 100
dim = 2
x = nr.randn(n, dim)
x[:30] += 2
k = 2
b = VBGMM(k, dim)
b.guess_priors(x)
b.initialize(x)
b.estimate(x, verbose=verbose)
z = b.map_label(x)
# fixme : find a less trivial test
assert z.max() + 1 == b.k
def test_vbgmm_select(kmax=6, verbose=0):
# perform the estimation of a gmm
n = 100
dim = 3
x = nr.randn(n, dim)
x[:30] += 2
show = 0
be = -np.infty
for k in range(1, kmax):
b = VBGMM(k, dim)
b.guess_priors(x)
b.initialize(x)
b.estimate(x)
z = b.map_label(x)
ek = b.evidence(x)
if verbose:
print k, ek
if ek > be:
be = ek
bestk = k
assert bestk < 3
