<｜begin▁of▁sentence｜>### Instruction:
Imagine you're working in your bike shop, where structuring the layout serves as a crucial part of organizing the space efficiently. Now, consider your collection of bicycles as nodes in a path network, with 4 bicycles placed end-to-end resembling a linear path graph. You're curious about how you might optimize the positioning of these bicycles in a more visually appealing, balanced manner within the spatial confines of your shop.

Could you think of using the spring layout mechanism from NetworkX, much like tuning the tension in a bike chain, to determine the most aesthetically pleasing arrangement of these 4 bicycles? After setting it up, how would you go about sketching out this new layout using Matplotlib to create a visual blueprint of your shop's floor plan?
### Response:
import networkx as nx
import matplotlib.pyplot as plt

# Create a graph
G = nx.path_graph(4)

# Apply the spring layout algorithm
pos = nx.spring_layout(G, k=0.15, iterations=50)

# Draw the graph
nx.draw(G, pos, with_labels=True)
plt.show()
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