<｜begin▁of▁sentence｜>### Instruction:
Given a directed graph with nodes x, a, b, c, d, e, y and edges with capacities as follows: x-a with 3.0, x-b with 1.0, a-c with 3.0, b-c with 5.0, b-d with 4.0, d-e with 2.0, c-y with 2.0, e-y with 3.0; can you use the edmonds_karp function to compute the maximum flow from the source node 'x' to the sink node 'y' in this network?
### Response:
from networkx.algorithms.flow import edmonds_karp

# Create a directed graph
G = nx.DiGraph()
G.add_edge('x', 'a', capacity=3.0)
G.add_edge('x', 'b', capacity=1.0)
G.add_edge('a', 'c', capacity=3.0)
G.add_edge('b', 'c', capacity=5.0)
G.add_edge('b', 'd', capacity=4.0)
G.add_edge('d', 'e', capacity=2.0)
G.add_edge('c', 'y', capacity=2.0)
G.add_edge('e', 'y', capacity=3.0)

# Run Edmonds-Karp algorithm
R = edmonds_karp(G, 'x', 'y')

# Get the value of the maximum flow
flow_value = R.graph['flow_value']
print('The maximum flow from node x to node y is:', flow_value)
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