def test_robust_scale_sparse(failure_logger, sparse_clf_dataset, # noqa: F811
axis, with_scaling, quantile_range):
X_np, X = sparse_clf_dataset
if X.format != 'csc' and axis == 0:
X = X.tocsc()
elif X.format != 'csr' and axis == 1:
X = X.tocsr()
t_X = cu_robust_scale(X, axis=axis,
with_centering=False,
with_scaling=with_scaling,
quantile_range=quantile_range,
copy=True)
# assert type(t_X) == type(X)
if cpx.scipy.sparse.issparse(X):
assert cpx.scipy.sparse.issparse(t_X)
if scipy.sparse.issparse(X):
assert scipy.sparse.issparse(t_X)
sk_t_X = sk_robust_scale(X_np, axis=axis,
with_centering=False,
with_scaling=with_scaling,
quantile_range=quantile_range,
copy=True)
assert_allclose(t_X, sk_t_X)
def test_robust_scale(
failure_logger,
clf_dataset, # noqa: F811
with_centering,
axis,
with_scaling,
quantile_range):
X_np, X = clf_dataset
t_X = cu_robust_scale(X,
axis=axis,
with_centering=with_centering,
with_scaling=with_scaling,
quantile_range=quantile_range,
copy=True)
assert type(t_X) == type(X)
sk_t_X = sk_robust_scale(X_np,
axis=axis,
with_centering=with_centering,
with_scaling=with_scaling,
quantile_range=quantile_range,
copy=True)
assert_allclose(t_X, sk_t_X)