<｜begin▁of▁sentence｜>### Instruction:
As a network scientist at a research institution, you have been tasked with analyzing the collaboration patterns in the field of Condensed Matter Physics using the Condensed Matter collaborations 2005 graph, extracted from the gml file named cond-mat-2005.gml. Your goal is to use the Louvain and Walktrap community detection algorithms available in the cdlib library to identify communities. Additionally, you are required to plot the relationship between the size (number of nodes) and internal edge density for the detected communities. This analysis will provide valuable insights into the collaborative structure within the field and help in understanding the dynamics of research collaborations in Condensed Matter Physics.
### Response:
import networkx as nx
from cdlib import algorithms, viz, evaluation

# Load the Condensed Matter collaborations 2005 graph from a gml file
g = nx.read_gml('cond-mat-2005.gml')

# Perform community detection using Louvain algorithm
coms = algorithms.louvain(g)

# Perform community detection using Walktrap algorithm
coms2 = algorithms.walktrap(g)

# Plot the relation between size (number of nodes) and internal edge density
lmplot = viz.plot_com_properties_relation([coms, coms2], evaluation.size, evaluation.internal_edge_density)
print(lmplot)
<|EOT|>
