<｜begin▁of▁sentence｜>### Instruction:
As a project scheduler, let's consider a scenario where we are managing the construction of a road network. The road network is represented as an undirected graph, and each road segment has a specified capacity for traffic flow. For instance, the road segments and their capacities are [(Road A, Road B, 10), (Road A, Road C, 15), (Road B, Road D, 12), (Road C, Road D, 10), (Road C, Road E, 5), (Road D, Road E, 20)]. 

In this scenario, we need to utilize scheduling software to generate the Gomory-Hu tree of the road network. Additionally, we are also interested in using the NetworkX API to find the minimum spanning tree of the road network. This will allow us to optimize resource allocation and track progress effectively.
### Response:
from igraph import Graph

# Let's suppose we have an undirected Graph
edges = [(0, 1, 10), (0, 2, 15), (1, 3, 12), (2, 3, 10), (2, 4, 5), (3, 4, 20)]
# Create the graph with edges and edge capacities
graph = Graph(edges=edges)
# Adding edge weights/capacities
graph.es['capacity'] = [10, 15, 12, 10, 5, 20]

# Use the Gomory-Hu tree function
gomory_hu_tree = graph.gomory_hu_tree()

# Print the structure of the tree
print(gomory_hu_tree)

# To compare, here is how you would find the minimum spanning tree in NetworkX
import networkx as nx
G_nx = nx.Graph()
G_nx.add_weighted_edges_from(edges)
min_spanning_tree_nx = nx.minimum_spanning_tree(G_nx)
print(min_spanning_tree_nx.edges(data=True))
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