def check_params(natparam):
natparam2 = standard_to_natural(*natural_to_standard(natparam))
assert np.allclose(natparam, natparam2)
def rand_niw(n):
S = rand_psd(n) + n * np.eye(n)
m = npr.randn(n)
kappa = n + npr.uniform(1, 3)
nu = n + npr.uniform(1, 3)
return standard_to_natural(S, m, kappa, nu)
def init_niw_natparam(N):
nu, S, m, kappa = N+niw_conc, (N+niw_conc)*np.eye(N), np.zeros(N), niw_conc
m = m + random_scale * npr.randn(*m.shape)
return niw.standard_to_natural(S, m, kappa, nu)
def init_niw_natparam(N):
nu, S, m, kappa = N+niw_conc, (N+niw_conc)*np.eye(N), np.zeros(N), niw_conc
m = m + random_scale * npr.randn(*m.shape)
return niw.standard_to_natural(S, m, kappa, nu)
def check_params(natparam):
natparam2 = standard_to_natural(*natural_to_standard(natparam))
assert np.allclose(natparam, natparam2)
def rand_niw(n):
S = rand_psd(n) + n * np.eye(n)
m = npr.randn(n)
kappa = n + npr.uniform(1, 3)
nu = n + npr.uniform(1, 3)
return standard_to_natural(S, m, kappa, nu)