<｜begin▁of▁sentence｜>### Instruction:
Given a weighted graph with edge set [('x', 'a', 3), ('x', 'b', 1), ('a', 'c', 3), ('b', 'c', 5), ('b', 'd', 4), ('d', 'e', 2), ('c', 'y', 2), ('e', 'y', 3)], use the Stoer-Wagner algorithm to find the minimum edge cut, considering edge weights. What are the cut value and the partition that define the minimum cut?
### Response:
import networkx as nx

# Create a weighted graph
G = nx.Graph()
G.add_edge('x', 'a', weight=3)
G.add_edge('x', 'b', weight=1)
G.add_edge('a', 'c', weight=3)
G.add_edge('b', 'c', weight=5)
G.add_edge('b', 'd', weight=4)
G.add_edge('d', 'e', weight=2)
G.add_edge('c', 'y', weight=2)
G.add_edge('e', 'y', weight=3)

# Use Stoer-Wagner algorithm to find the minimum cut
cut_value, partition = nx.stoer_wagner(G, weight='weight')

# Print the results
print('Cut value:', cut_value)
print('Partition:', partition)
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