def test_robust_scaler_sparse( sparse_clf_dataset, # noqa: F811 with_scaling, quantile_range): X_np, X = sparse_clf_dataset if X.format != 'csc': X = X.tocsc() scaler = cuRobustScaler(with_centering=False, with_scaling=with_scaling, quantile_range=quantile_range, copy=True) t_X = scaler.fit_transform(X) r_X = scaler.inverse_transform(t_X) assert type(t_X) == type(X) assert type(r_X) == type(t_X) scaler = skRobustScaler(with_centering=False, with_scaling=with_scaling, quantile_range=quantile_range, copy=True) sk_t_X = scaler.fit_transform(X_np) sk_r_X = scaler.inverse_transform(sk_t_X) assert_allclose(t_X, sk_t_X) assert_allclose(r_X, sk_r_X)
def test_robust_scaler( clf_dataset, with_centering, # noqa: F811 with_scaling, quantile_range): X_np, X = clf_dataset scaler = cuRobustScaler(with_centering=with_centering, with_scaling=with_scaling, quantile_range=quantile_range, copy=True) t_X = scaler.fit_transform(X) r_X = scaler.inverse_transform(t_X) assert type(t_X) == type(X) assert type(r_X) == type(t_X) scaler = skRobustScaler(with_centering=with_centering, with_scaling=with_scaling, quantile_range=quantile_range, copy=True) sk_t_X = scaler.fit_transform(X_np) sk_r_X = scaler.inverse_transform(sk_t_X) assert_allclose(t_X, sk_t_X) assert_allclose(r_X, sk_r_X)