<｜begin▁of▁sentence｜>### Instruction:
As a Gymnastics Coach who trains and coaches gymnasts in skills, routines, and competitions for gymnastics events, imagine you have a team of gymnasts in practice. Some gymnasts are skilled in performing specific routines, like a one-handed cartwheel or a back handspring. Suppose you have a group routine that requires a specific set of gymnasts to perform different skills in succession. During practice, you designate certain pairs of gymnasts to work together, with each pair showcasing a synchronized routine involving connecting moves.

Now, let's say you are using a tool called NetworkX to keep track of these gymnast pairings. In this tool, you define the connections between different gymnasts as edges. For instance, if gymnasts A and B perform a connected routine, you create an edge between A and B in the network.

Consider the following scenario: In your team, gymnasts 1, 2, 3, and 4 have specific routines they can perform together. You have designated a particular pair, gymnasts 2 and 3, to showcase a connected routine. Using NetworkX's is_maximal_matching function, you aim to determine if this designated pairing of gymnasts is the most extensive combination possible within the routine, ensuring that no other pair can be added to the sequence without breaking the synchronization.
### Response:
from networkx.algorithms.matching import is_maximal_matching
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(1, 2), (2, 3), (3, 4)])

# Define a set of edges that form a matching
matching = {(2, 3)}

# Check if the matching is maximal
is_maximal = is_maximal_matching(G, matching)
print('Is the matching maximal?', is_maximal)
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