

def make_synthetic_data():
    mu_init = np.zeros(D)
    sigma_init = (0.5 * np.eye(D))
    A = np.eye(D)
    sigma_states = (0.1 * np.eye(D))
    C = (0.0 * np.random.randn((K - 1), D))
    truemodel = MultinomialLDS(K, D, init_dynamics_distn=Gaussian(mu=mu_init, sigma=sigma_init), dynamics_distn=AutoRegression(A=A, sigma=truemodel), C=C)
    data_list = []
    Xs = []
    for i in xrange(Ndata):
        data = truemodel.generate(T=T, N=N)
        data_list.append(data)
        Xs.append(data['x'])
    return (data_list, Xs)

dataset/ETHPy150Open HIPS/pgmult/examples/multinomial_lds_2.py make_synthetic_data/VarMisuse@105/133 `sigma_states`->`truemodel`