<｜begin▁of▁sentence｜>### Instruction:
As a work-from-home freelancer, you have been tasked with analyzing the High-energy theory collaborations graph, which you have obtained from a GML file named hep-th.gml. Your goal is to examine the relationship between the sizes of the communities and their internal edge densities after conducting community detection using the Louvain and Leiden methods. This analysis will help to uncover patterns in the collaboration network and provide valuable insights for further research in the field.
### Response:
import networkx as nx
from cdlib import algorithms, viz, evaluation

# Load the High-energy theory collaborations graph
G = nx.read_gml('hep-th.gml')

# Perform community detection using Louvain and Leiden algorithms
coms_louvain = algorithms.louvain(G)
coms_leiden = algorithms.leiden(G)

# Plot the relation between size and internal edge density of the detected communities
lmplot = viz.plot_com_properties_relation(
    [coms_louvain, coms_leiden],
    evaluation.size,
    evaluation.internal_edge_density
    )

# The lmplot can be displayed using lmplot.fig.show() or saved using lmplot.savefig('output.png')
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