<｜begin▁of▁sentence｜>### Instruction:
Imagine you are overseeing a vast network of water channels in a forest, where each pathway can transport a certain volume of water. You're tasked with determining the greatest amount of water that can be shifted from a lake, labeled as the 'source node x,' to a reservoir, known as the 'sink node y,' through this network of channels. Is it possible for you to apply Dinitz's algorithm to calculate the maximum water flow between these two points, ensuring that you don't exceed the volume limits of any individual channel along the way?
### Response:
from networkx.algorithms.flow import dinitz

# Create a directed graph
G = nx.DiGraph()

# Add edges with capacities
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)

# Use Dinitz's algorithm to find the maximum flow from 'x' to 'y'
R = dinitz(G, 'x', 'y')

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