def test_log_noninformative_beta_prior(): from microscopes.common.scalar_functions import ( log_noninformative_beta_prior, ) alpha, beta = 0.8, 0.2 assert log_noninformative_beta_prior.input_dim() == 2 val = log_noninformative_beta_prior(alpha, beta) assert_almost_equals(val, -2.5 * np.log(alpha + beta), places=5)
def prior_fn(raw): return log_noninformative_beta_prior(raw['alpha'], raw['beta'])