def make_path(X, D):
tsp = TSP()
# Using the data matrix
tsp.read_data(X)
# Using the distance matrix
tsp.read_mat(D)
from tspy.solvers import TwoOpt_solver
two_opt = TwoOpt_solver(initial_tour='NN', iter_num=10000)
two_opt_tour = tsp.get_approx_solution(two_opt)
#tsp.plot_solution('TwoOpt_solver')
best_tour = tsp.get_best_solution()
return best_tour
from tspy import TSP
import matplotlib.pyplot as plt
from tspy.solvers import TwoOpt_solver
from tspy.lower_bounds import Held_Karp
from tspy.lower_bounds import Connected_LP_bound
import numpy as np
a = TSP()
N = 100
a.read_data(np.random.rand(N, 2))
sol = TwoOpt_solver('NN')
a.get_approx_solution(sol)
plt.figure(figsize=(5, 5))
a.plot_solution('TwoOpt_solver')
a.get_lower_bound(Connected_LP_bound())
a.get_lower_bound(
Held_Karp(n_iter=1000, batch_size=50, alp_factor=1, start_alp=0.001))