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 get_spec(field, limit=10, query='', query_dsl=''):
    """Returns aggregation specs for a term of filtered events.

    The aggregation spec will summarize values of an attribute
    whose events fall under a filter.

    Args:
        field (str): this denotes the event attribute that is used
            for aggregation.
        limit (int): How many buckets to return, defaults to 10.
        query (str): the query field to run on all documents prior to
            aggregating the results.
        query_dsl (str): the query DSL field to run on all documents prior
            to aggregating the results (optional). Either a query string
            or a query DSL has to be present.

    Raises:
        ValueError: if neither query_string or query_dsl is provided.

    Returns:
        a dict value that can be used as an aggregation spec.
    """
    if query:
        query_filter = {
            'bool': {
                'must': [
                    {
                        'query_string': {
                            'query': query
                        }
                    }
                ]
            }
        }
    elif query_dsl:
        query_filter = query_dsl
    else:
        raise ValueError('Neither query nor query DSL provided.')


    return {
        'query': query_filter,
        'aggs': {
            'aggregation': {
                'terms': {
                    'field': field,
                    'size': limit
                }
            }
        }
    }