def function(): covmat1 = CovMat.random(100) covmat2 = CovMat.random(100) a = Distance.euclidean(covmat1, covmat2) b = Distance.log_euclidean(covmat1, covmat2) c = Distance.log_determinant(covmat1, covmat2) d = Distance.riemannian(covmat1, covmat2) e = Distance.wasserstein(covmat1, covmat2) f = Distance.kullback(covmat1, covmat2) g = Distance.kullback_right(covmat1, covmat2) h = Distance.kullback_sym(covmat1, covmat2)
def test_euclidean(): m1 = CovMat.random(10) m2 = CovMat.random(10) old_dist = distance_euclid(m1.numpy_array, m2.numpy_array) m1.reset_fields() m2.reset_fields() new_dist = Distance.euclidean(m1, m2) if abs( old_dist - new_dist ) < 1e-10: print("euclid: PASS") return True else: print("euclid: FAIL") return False
def test_euclidean(): m1 = CovMat.random(10) m2 = CovMat.random(10) old_dist = distance_euclid(m1.numpy_array, m2.numpy_array) m1.reset_fields() m2.reset_fields() new_dist = Distance.euclidean(m1, m2) if abs(old_dist - new_dist) < 1e-10: print("euclid: PASS") return True else: print("euclid: FAIL") return False