def test_sample(): mean = 0 cov = 10 scaling = 1 offset = 0. truncate = 1e-2 dom = LogNormalDomain(mean, cov, offset, scaling, truncate) X = dom.sample(100) print(dom.isinside(X)) assert np.all(dom.isinside(X))
def test_normalize(): mean = 0 cov = 10 scaling = 1 offset = 0. truncate = 1e-2 dom = LogNormalDomain(mean, cov, offset, scaling, truncate) dom_norm = dom.normalized_domain() print(dom_norm.lb) print(dom_norm.ub) assert np.isclose(dom_norm.lb, -1) assert np.isclose(dom_norm.ub, 1) # TODO: Check densities X = dom.sample(100) X_norm = dom.normalize(X) p = dom.pdf(X) p_norm = dom_norm.pdf(X_norm) assert np.all(np.isclose(p, p_norm))