<｜begin▁of▁sentence｜>### Instruction:
Imagine you're working on the UI for an innovative new network analysis tool, and part of the challenge involves visualizing the interactions between different user clusters within the network. Right now, our focus is on the visual representation and interaction design for a feature that will help users understand the 'mixing expansion' between two specific user groups.

In this scenario, we have a test graph with user connections represented by the edges [(1, 2), (1, 3), (2, 3), (3, 4), (4, 5), (5, 1)], and we're interested in exploring the connections between two subsets of users: Group S, which includes users 1 and 2, and Group T, comprising users 4 and 5.

The challenge is to design an interface that clearly shows how 'mixed' or interconnected these two groups are within the network. For this, we'll need to develop a visualization feature that calculates and displays the 'mixing expansion' between Group S and Group T users. How would you craft this experience so that the calculated metric can be easily understood and explored by our users?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(1, 2), (1, 3), (2, 3), (3, 4), (4, 5), (5, 1)])

# Define two node sets
S = {1, 2}
T = {4, 5}

# Calculate mixing expansion between S and T
mix_expansion = nx.mixing_expansion(G, S, T)

print('Mixing expansion between S and T:', mix_expansion)
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