<｜begin▁of▁sentence｜>### Instruction:
As a statistical analyst, you have a network analysis problem at a telecommunication company. You have a network graph representing connections between cell towers, and each edge has a capacity representing the maximum data flow it can handle. Using the st_mincut function in NetworkX, you need to calculate the minimum cut value between two specific towers, and also identify the vertices in the two partitions as well as the edges that constitute the cut.
### Response:
from igraph import Graph

# Create an example graph with weighted edges
g = Graph(edges=[(0, 1), (1, 2), (2, 3), (3, 0)], directed=False)
g.es['capacity'] = [10, 1, 10, 1]

source_vertex = 0
target_vertex = 2

# Calculate the minimum cut between vertex 0 and vertex 2
cut_value, partition1, partition2, cut_edges = g.st_mincut(source=source_vertex, target=target_vertex, capacity='capacity')

print(f'Min-cut value: {cut_value}')
print(f'Vertices in partition 1: {partition1}')
print(f'Vertices in partition 2: {partition2}')
print(f'Edges in the cut: {cut_edges}')
<|EOT|>
