def test_view_of_view_modification():
    adata = ad.AnnData(np.zeros((10, 10)))
    adata[0, :][:, 5:].X = np.ones(5)
    assert np.all(adata.X[0, 5:] == np.ones(5))
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2))
    assert np.all(adata.X[1:3, 1:3] == np.ones((2, 2)))

    adata.X = sparse.csr_matrix(adata.X)
    adata[0, :][:, 5:].X = np.ones(5) * 2
    assert np.all(asarray(adata.X)[0, 5:] == np.ones(5) * 2)
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2)) * 2
    assert np.all(asarray(adata.X)[1:3, 1:3] == np.ones((2, 2)) * 2)
def rpc_bulk(orchestrator, audit_name, rpc_code, *arguments):

    # Get the implementor for the RPC code.
    # Raise NotImplementedError if it's not defined.
    try:
        method, blocking = rpcMap[rpc_code]
    except KeyError:
        raise NotImplementedError("RPC code not implemented: %r" % rpc_code)

    # This can't be done with blocking implementors!
    if blocking:
        raise NotImplementedError(
            "Cannot run blocking RPC calls in bulk. Code: %r" % rpc_code)

    # Prepare a partial function call to the implementor.
    caller = partial(method, orchestrator, audit_name)

    # Use the built-in map() function to issue all the calls.
    # This ensures we support the exact same interface and functionality.
    return map(caller, *arguments)