<｜begin▁of▁sentence｜>### Instruction:
As an urban designer, imagine you are working on a project to revitalize a city's downtown area. You have a graph representing the street network with weighted edges, each indicating the capacity for traffic flow between intersections. You need to calculate the minimum cut between two crucial intersections, taking into account the capacities of the street segments. How would you use the st_mincut function in igraph to analyze this and inform your urban planning decisions?
### Response:
from igraph import Graph

# Create a graph
edges = [(0, 1), (1, 2), (2, 3), (3, 0), (0, 2)]
capacities = [10, 5, 15, 10, 5]
g = Graph(edges=edges)
g.es['capacity'] = capacities

# Calculate the minimum cut between vertex 0 and vertex 3
mincut_value, partition1, partition2, cut_edges = g.st_mincut(source=0, target=3, capacity=g.es['capacity'])
print(f'Minimum cut value: {mincut_value}')
print(f'Vertices in partition 1: {partition1}')
print(f'Vertices in partition 2: {partition2}')
print(f'Edges in the cut: {cut_edges}')
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