

def fit_gaussian_lds_model(Xs, N_samples=100):
    testmodel = DefaultLDS(n=D, p=K)
    for X in Xs:
        testmodel.add_data(X)
    samples = []
    lls = []
    for smpl in progprint_xrange(N_samples):
        testmodel.resample_model()
        samples.append(testmodel.copy_sample())
        lls.append(testmodel.log_likelihood())
    lls = np.array(lls)
    return lls

dataset/ETHPy150Open HIPS/pgmult/examples/multinomial_lds_2.py fit_gaussian_lds_model/original