<｜begin▁of▁sentence｜>### Instruction:
Imagine we're designing a new activity for our physical education class where students move between different stations, represented as points, in a specific sequence determined by the most efficient pathway. Think of it as a fitness circuit with 5 key exercises, each station being a node connected in a linear path to the next exercise. The goal is to determine the best order to visit each station to maintain an optimal flow and minimize the time spent transitioning between exercises. Could we use NetworkX to help us create this spectral ordering for the stations? And if so, how would that sequence look?
### Response:
import networkx as nx

# Create a graph
G = nx.path_graph(5)

# Compute the spectral ordering of the graph
ordering = nx.spectral_ordering(G, weight=None, normalized=False, tol=1e-8, method='tracemin_pcg', seed=None)

print('Spectral ordering of the nodes:', ordering)
<|EOT|>
