<｜begin▁of▁sentence｜>### Instruction:
Imagine you, a skilled cartographer, are tasked with designing an intricate map for a newly developed area to facilitate navigation, planning, and research purposes. The map includes a network of roads connecting important landmarks, represented by points 0, 1, 2, and 3. The lengths and travel times on these roads vary, thus each road segment between the landmarks is marked with a weight that reflects its travel time. Specifically, the roads and their travel times are as follows: a road from landmark 0 to landmark 1 with a travel time of 3 units, a road from landmark 1 to landmark 2 with 7.5 units, a road from landmark 2 to landmark 3 at 2.2 units, and a direct path from 0 to 3 taking just 1 unit of time.

As part of your comprehensive mapping and analysis, you aim to calculate the average minimum travel time between all pairs of landmarks, taking into account the travel times (weights) of each road segment to ensure the most efficient routes are highlighted on your map. This calculation will greatly aid in the optimization of transportation and logistic strategies within this area. How would you go about determining this average, ensuring your calculations reflect the varying weights of each road segment on your meticulously designed map?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_weighted_edges_from([(0, 1, 3), (1, 2, 7.5), (2, 3, 2.2), (0, 3, 1)])

# Calculate average shortest path length
avg_shortest_path_length = nx.average_shortest_path_length(G, weight='weight')

print('Average shortest path length:', avg_shortest_path_length)
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