<｜begin▁of▁sentence｜>### Instruction:
Given the C. elegans neural network graph which you can read from a GML file named celegansneural.gml, can you use the lswl_plus function in cdlib to perform community detection with the following parameters: using strengths between [0,1], not merging outliers, and detecting non-overlapping communities? After the community detection, can you provide a JSON representation of the communities?
### Response:
import networkx as nx
from cdlib import algorithms

# Create a graph from the C. elegans neural network data
G = nx.read_gml('celegansneural.gml')

# Apply the LSWL+ algorithm for community detection
# Here we request to find non-overlapping communities and not merge outliers.
coms = algorithms.lswl_plus(G, strength_type=2, merge_outliers=False, detect_overlap=False)

# Convert the communities to JSON for serialization
coms_json = coms.to_json()

print(coms_json)
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