How to use the phylib.io.array._spikes_per_cluster function in phylib

self._cluster_ids = _unique(self._spike_clusters)
        # Clusters to remove.
        if to_remove is not None:
            for clu in to_remove:
                self._spikes_per_cluster.pop(clu, None)
        # Clusters to add.
        if to_add:
            for clu, spk in to_add.items():
                self._spikes_per_cluster[clu] = spk
        # If spikes_per_cluster is invalid, recompute the entire
        # spikes_per_cluster array.
        coherent = np.all(np.in1d(self._cluster_ids, sorted(self._spikes_per_cluster)))
        if not coherent:
            logger.debug("Recompute spikes_per_cluster manually: this might take a while.")
            sc = self._spike_clusters
            self._spikes_per_cluster = _spikes_per_cluster(sc)

def __init__(self, model):
        self.model = model
        self.dir_path = Path(model.dir_path)
        self.spc = _spikes_per_cluster(model.spike_clusters)
        self.renames = _FILE_RENAMES

# The fact that spike selection has been previously extended to
        # whole clusters is critical here.
        new_clusters = _unique(new_spike_clusters)
        if len(new_clusters) == 1:
            return self._do_merge(spike_ids, old_clusters, new_clusters[0])

        # We return the UpdateInfo structure.
        up = _assign_update_info(spike_ids, old_spike_clusters, new_spike_clusters)

        # We update the new cluster id (strictly increasing during a session).
        self._new_cluster_id = max(self._new_cluster_id, max(up.added) + 1)

        # We make the assignments.
        self._spike_clusters[spike_ids] = new_spike_clusters
        # OPTIM: we update spikes_per_cluster manually.
        new_spc = _spikes_per_cluster(new_spike_clusters, spike_ids)
        self._update_cluster_ids(to_remove=old_clusters, to_add=new_spc)
        return up