<｜begin▁of▁sentence｜>### Instruction:
Imagine you're orchestrating a grand networking event at a stylish convention center, designed like a lattice of interconnecting halls, represented by a floor plan 'network_diagram.gml'. In this elaborate setup, certain halls are connected by exclusive walkways that can sway the flow of attendee traffic significantly. Assume the event has halls numbered 1 through 5, with walkways connecting them as follows: Hall 1 to Hall 2, Hall 1 to Hall 3, Hall 2 to Hall 3, Hall 3 to Hall 4, Hall 4 to Hall 5, and Hall 5 back to Hall 1, forming a network of pathways.

For this event, Halls 1 and 2 are positioned as the primary reception areas where guests arrive and mingle, serving as the sources of traffic. Halls 4 and 5, on the other hand, host the main attractions of the event - keynote presentations and gala dinners, acting as the target destinations where most attendees are headed.

In order to manage this flow efficiently and ensure all guests have a smooth experience navigating to the main attractions, could you weave into the event plan a strategy to determine the walkway's 'Edge Current Flow Betweenness Centrality'? Specifically, you would need to focus on assessing the prominence of each walkway in handling the flood of movement from the reception areas, Halls 1 and 2, to the main events occurring in Halls 4 and 5. Integrating this into your logistical blueprint will enable the facilitation of crowd control and ensure optimal use of space within the convention center.
### Response:
import networkx as nx
import numpy as np

# Define a function to calculate edge current flow betweenness centrality for a subset

def calculate_edge_current_flow_betweenness_subset(G, sources, targets, normalized=True, weight=None, dtype=np.float64, solver='lu'):
    return nx.edge_current_flow_betweenness_centrality_subset(
        G, sources, targets, normalized=normalized, weight=weight, dtype=dtype, solver=solver
    )

# Create a graph
G = nx.Graph()
G.add_edges_from([(1, 2), (1, 3), (2, 3), (3, 4), (4, 5), (5, 1)])

# Define sources and targets
sources = [1, 2]
targets = [4, 5]

# Calculate current flow betweenness centrality for edges with a subset
betweenness = calculate_edge_current_flow_betweenness_subset(G, sources, targets)

print(betweenness)
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