<｜begin▁of▁sentence｜>### Instruction:
Given a NetworkX graph representing a social club's interactions, how would you represent the hierarchical community structure where each node's community membership at various levels is captured after performing a Hierarchical Leiden clustering algorithm?
### Response:
import networkx as nx
from graspologic.partition import HierarchicalCluster

# Suppose we have a networkx graph
G = nx.karate_club_graph()

# Example usage of the HierarchicalCluster class
node = 0  # Example node
cluster_id = 1  # Example cluster identifier
parent_cluster_id = None  # No parent cluster at the top level
level = 0  # Top level (no subdivisions)
is_final_cluster = True  # This is a terminal cluster

# Create a hierarchical cluster representation for node 0
hierarchical_cluster = HierarchicalCluster(node, cluster_id, parent_cluster_id, level, is_final_cluster)

# Now suppose you want to perform community detection on the graph
from graspologic.partition import HierarchicalCluster

# Function to perform hierarchical leiden clustering
def perform_hierarchical_leiden(G):
    # Some code that performs the hierarchical leiden clustering
    # and for each node in the graph, it performs the HierarchicalCluster
    # initialization as shown above.
    pass

# Run hierarchical leiden on our networkx graph
perform_hierarchical_leiden(G)
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