def test_set_subset_varm(adata, subset_func):
    init_hash = joblib.hash(adata)
    orig_varm_val = adata.varm["o"].copy()

    while True:
        subset_idx = slice_subset(adata.var_names)
        if (adata[:, subset_idx]).shape[1] > 2:
            break
    subset = adata[:, subset_idx]

    internal_idx = _normalize_index(
        subset_func(np.arange(subset.varm["o"].shape[0])), subset.var_names
    )

    assert subset.is_view
    subset.varm["o"][internal_idx] = 1
    assert not subset.is_view
    assert np.all(adata.varm["o"] == orig_varm_val)

    assert init_hash == joblib.hash(adata)
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)