def test_set_scalar_subset_X(matrix_type, subset_func):
    adata = ad.AnnData(matrix_type(np.zeros((10, 10))))
    orig_X_val = adata.X.copy()
    subset_idx = slice_subset(adata.obs_names)

    adata_subset = adata[subset_idx, :]

    adata_subset.X = 1

    assert adata_subset.is_view
    assert np.all(asarray(adata[subset_idx, :].X) == 1)

    assert asarray((orig_X_val != adata.X)).sum() == mul(*adata_subset.shape)
def __init__(self, root, cwd, kindpats, ctx=None, badfn=None):
        super(patternmatcher, self).__init__(root, cwd, badfn)
        # kindpats are already normalized to be relative to repo-root.
        # Can we use tree matcher?
        rules = _kindpatstoglobs(kindpats, recursive=False)
        fallback = True
        if rules is not None:
            try:
                matcher = treematcher(root, cwd, badfn=badfn, rules=rules)
                # Replace self to 'matcher'.
                self.__dict__ = matcher.__dict__
                self.__class__ = matcher.__class__
                fallback = False
            except ValueError:
                # for example, Regex("Compiled regex exceeds size limit of 10485760 bytes.")
                pass
        if fallback:
            self._prefix = _prefix(kindpats)
            self._pats, self.matchfn = _buildmatch(ctx, kindpats, "$", root)

        self._files = _explicitfiles(kindpats)