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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def aggregate_partition(self, membership_partition=None):
 """ Aggregate the graph according to the current partition and provide a default partition for it. The aggregated graph can then be found as a parameter of the partition ``partition.graph``. Notes ----- This function contrasts to the function ``cluster_graph`` in igraph itself, which also provides the aggregate graph, but we may require setting the appropriate ``resolution_parameter``, ``weights`` and ``node_sizes``. In particular, this function also ensures that the quality defined on the aggregate partition is identical to the quality defined on the original partition. Examples -------- True """

    partition_agg = self._FromCPartition(_c_leiden._MutableVertexPartition_aggregate_partition(self._partition))

    if (not membership_partition is None):
      membership = partition_agg.membership
      for v in self.graph.vs:
        membership[self.membership[v.index]] = membership_partition.membership[v.index]
      partition_agg.set_membership(membership)

    return partition_agg