def test_view_mixin_copies_data(adata, array_type: type, attr):
    N = 100
    adata = ad.AnnData(
        obs=pd.DataFrame(index=np.arange(N)), var=pd.DataFrame(index=np.arange(N))
    )

    X = array_type(sparse.eye(N, N).multiply(np.arange(1, N + 1)))
    if attr == "X":
        adata.X = X
    else:
        getattr(adata, attr)["arr"] = X

    view = adata[:50]

    if attr == "X":
        arr_view = view.X
    else:
        arr_view = getattr(view, attr)["arr"]

    arr_view_copy = arr_view.copy()

    if sparse.issparse(X):
        assert not np.shares_memory(arr_view.indices, arr_view_copy.indices)
        assert not np.shares_memory(arr_view.indptr, arr_view_copy.indptr)
        assert not np.shares_memory(arr_view.data, arr_view_copy.data)

        arr_view_copy.data[0] = -5
        assert not np.array_equal(arr_view_copy.data, arr_view.data)
    else:
        assert not np.shares_memory(arr_view, arr_view_copy)

        arr_view_copy[0, 0] = -5
        assert not np.array_equal(arr_view_copy, arr_view)
def log_stream(self, logger_name, level_name, format_str):
        """ Attaches a log handler to the specified logger and sends emitted logs 
            back as stream. 
        """
        if logger_name != "" and logger_name not in self.available_loggers():
            raise ValueError("logger {0} is not available".format(logger_name))

        level_name_upper = level_name.upper() if level_name else "NOTSET"
        try:
            level = getattr(logging, level_name_upper)
        except AttributeError, e:
            raise AttributeError("log level {0} is not available".format(level_name_upper))