<｜begin▁of▁sentence｜>### Instruction:
Given a power grid network which can be read from a GML file named power.gml, can you use the Louvain and Walktrap algorithms in cdlib to perform community detection on it? Afterwards, can you plot a similarity matrix comparing these two clusterings using adjusted mutual information as the scoring function? Notes: You need to print the resulting ClusterGrid instance.
### Response:
import networkx as nx
from cdlib import algorithms, viz, evaluation

# Read the power grid graph
G = nx.read_gml('power.gml')

# Detect communities using two different algorithms
coms_louvain = algorithms.louvain(G)
coms_walktrap = algorithms.walktrap(G)

# Plot a similarity matrix using adjusted mutual information as the scoring function
clustermap = viz.plot_sim_matrix([coms_louvain, coms_walktrap], evaluation.adjusted_mutual_information)
print(clustermap)
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