dbt-selly/dbt-env/share/doc/networkx-2.7.1/examples/drawing/plot_tsp.py

53 lines
1.3 KiB
Python

"""
==========================
Traveling Salesman Problem
==========================
This is an example of a drawing solution of the traveling salesman problem
The function is used to produce the solution is christofides,
where given a set of nodes, it calculates the route of the nodes
that the traveler has to follow in order to minimize the total cost.
"""
import matplotlib.pyplot as plt
import networkx as nx
import networkx.algorithms.approximation as nx_app
import math
G = nx.random_geometric_graph(20, radius=0.4, seed=3)
pos = nx.get_node_attributes(G, "pos")
# Depot should be at (0,0)
pos[0] = (0.5, 0.5)
H = G.copy()
# Calculating the distances between the nodes as edge's weight.
for i in range(len(pos)):
for j in range(i + 1, len(pos)):
dist = math.hypot(pos[i][0] - pos[j][0], pos[i][1] - pos[j][1])
dist = dist
G.add_edge(i, j, weight=dist)
cycle = nx_app.christofides(G, weight="weight")
edge_list = list(nx.utils.pairwise(cycle))
# Draw closest edges on each node only
nx.draw_networkx_edges(H, pos, edge_color="blue", width=0.5)
# Draw the route
nx.draw_networkx(
G,
pos,
with_labels=True,
edgelist=edge_list,
edge_color="red",
node_size=200,
width=3,
)
print("The route of the traveller is:", cycle)
plt.show()