<｜begin▁of▁sentence｜>### Instruction:
Given a directed graph with the edge set [('A', 'B'), ('B', 'C'), ('C', 'D'), ('D', 'A')], how do you compute the trophic incoherence parameter using NetworkX, excluding self-loops as part of the calculation?
### Response:
import networkx as nx
from networkx.algorithms import trophic

# Create a directed graph
G = nx.DiGraph()
# Add edges (including possibly a self-loop if cannibalism is considered)
G.add_edges_from([('A', 'B'), ('B', 'C'), ('C', 'D'), ('D', 'A')])
# Compute the trophic incoherence parameter
q = trophic.trophic_incoherence_parameter(G, cannibalism=False)
print('Trophic incoherence parameter:', q)
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