def test_is_symetric_or_tri(): n = 100 m = 50 X = np.random.random((n, m)) assert_raises(ValueError, validation.is_symetric_or_tri, X) X = np.random.random((n, n)) assert_raises(ValueError, validation.is_symetric_or_tri, X) X = X + X.T validation.is_symetric_or_tri(X) X[np.tri(n, dtype=bool)] = 0 validation.is_symetric_or_tri(X)
def test_is_symetric_or_tri(): n = 100 m = 50 random_state = np.random.RandomState(seed=42) X = random_state.randn(n, m) assert_raises(ValueError, validation.is_symetric_or_tri, X) X = random_state.randn(n, n) assert_raises(ValueError, validation.is_symetric_or_tri, X) X = X + X.T validation.is_symetric_or_tri(X) X = np.triu(X) validation.is_symetric_or_tri(X)
def test_is_symetric_or_tri(): n = 100 m = 50 random_state = np.random.RandomState(seed=42) X = random_state.randn(n, m) assert_raises(ValueError, validation.is_symetric_or_tri, X) X = random_state.randn(n, n) assert_raises(ValueError, validation.is_symetric_or_tri, X) X = X + X.T validation.is_symetric_or_tri(X) X[np.tri(n, dtype=bool)] = 0 validation.is_symetric_or_tri(X)
def test_is_symetric_or_tri_sparse(): n = 100 m = 50 random_state = np.random.RandomState(seed=42) X = sparse.csr_matrix(random_state.randn(n, m)) assert_raises(ValueError, validation.is_symetric_or_tri, X) X = sparse.csr_matrix(random_state.randn(n, n)) assert_raises(ValueError, validation.is_symetric_or_tri, X) X = random_state.randn(n, n) X = X + X.T X = sparse.csr_matrix(X) validation.is_symetric_or_tri(X) X[np.tri(n, dtype=bool)] = 0 validation.is_symetric_or_tri(X)