def test_not_set_subset_X(matrix_type, subset_func):
    adata = ad.AnnData(matrix_type(asarray(sparse.random(20, 20))))
    init_hash = joblib.hash(adata)
    orig_X_val = adata.X.copy()
    while True:
        subset_idx = slice_subset(adata.obs_names)
        if len(adata[subset_idx, :]) > 2:
            break
    subset = adata[subset_idx, :]

    subset = adata[:, subset_idx]

    internal_idx = _normalize_index(
        subset_func(np.arange(subset.X.shape[1])), subset.var_names
    )
    assert subset.is_view
    subset.X[:, internal_idx] = 1
    assert not subset.is_view
    assert not np.any(asarray(adata.X != orig_X_val))

    assert init_hash == joblib.hash(adata)
def set_categories(self, categories: List[str]):
        """Sets the categories for Confusion Matrix.

        Args:
          categories: List of strings specifying the categories.
        """
        self._categories = []
        annotation_specs = []
        for category in categories:
            annotation_spec = {'displayName': category}
            self._categories.append(category)
            annotation_specs.append(annotation_spec)

        self._values['annotationSpecs'] = annotation_specs
        self._matrix = [[0
                         for i in range(len(self._categories))]
                        for j in range(len(self._categories))]
        self._values['row'] = self._matrix