<｜begin▁of▁sentence｜>### Instruction:
Imagine you're an agronomist overseeing a complex irrigation network represented by a directed graph, where nodes represent junction points in the irrigation system and weighted edges symbolize water channels of varying capacities and flow costs between those junctions. To optimize water delivery, you're considering various branching subnetworks—configurations where each junction has at most one upstream water source and no looping paths are present to ensure efficient water distribution.

One critical step in your analysis is to determine the total flow cost of a proposed branching subnetwork within this irrigation graph. How could you utilize the 'branching_weight' function within the networkx.algorithms.tree module to calculate the sum of the weights (which in your case could be flow costs or water channel capacities) of all the edges in this branching subnetwork? This calculation would assume that the relevant graph data is available to you, possibly stored in a .gml file or similar data structure for your analysis.
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph()

# Add weighted edges to the graph
G.add_weighted_edges_from([(0, 1, 2), (1, 2, 4), (2, 3, 3), (3, 4, 2)])

# Calculate the total weight of a branching
weight = nx.tree.branching_weight(G)
print('Total weight of the branching:', weight)
<|EOT|>
