<｜begin▁of▁sentence｜>### Instruction:
As an Emergency Medical Dispatcher, you have received a request to analyze the neural network of C. elegans using the celegansneural.gml file. Your task is to use the I-Louvain algorithm from the cdlib library to conduct attributed community detection with random scalar attributes, and then output the results in a JSON format. This analysis is crucial for understanding the connectivity patterns within the neural network and could potentially lead to important insights for further research in neuroscience and network analysis.
### Response:
import networkx as nx
from cdlib import algorithms
import random

# Read the graph from the gml file
g = nx.read_gml('celegansneural.gml')

# Create random attributes for the nodes
labels = dict()
l1 = [0.1, 0.4, 0.5]
l2 = [34, 3, 112]
for node in g.nodes():
    labels[node] = {'l1': random.choice(l1), 'l2': random.choice(l2)}

# Apply the I-Louvain algorithm with the generated labels
communities = algorithms.ilouvain(g, labels)

# Generate a JSON representation of the algorithms object
json_repr = communities.to_json()

print(json_repr)
<|EOT|>
