<｜begin▁of▁sentence｜>### Instruction:
A researcher has several network graphs representing different types of interactions among the same set of entities. They want to identify a subgraph where interactions are common across all the different networks. How can the researcher find the largest connected component that is common to all given network graphs?
### Response:
import networkx as nx
import numpy as np
from graspologic.utils import multigraph_lcc_intersection

# Step 1: Construct multiple network graphs (for example three random graphs)
G1 = nx.erdos_renyi_graph(n=100, p=0.1)
G2 = nx.erdos_renyi_graph(n=100, p=0.2)
G3 = nx.erdos_renyi_graph(n=100, p=0.3)

# Step 2: Find the largest connected component intersection
intersection_graph = multigraph_lcc_intersection(graphs=[G1, G2, G3])

# Step 3: Check if we want the indices of the original graphs
intersection_graph, inds = multigraph_lcc_intersection(graphs=[G1, G2, G3], return_inds=True)

print('Intersection Graph:', intersection_graph)
print('Indices of the original graphs kept:', inds)
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