76 lines
2.8 KiB
Python
76 lines
2.8 KiB
Python
from matplotlib import pyplot as plt
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from libs.simulated_annealing import SimulatedAnnealing, distance, total_distance
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cities = [[565, 575], [25, 185], [345, 750], [945, 685], [845, 655], [880, 660], [25, 230], [525, 1000], [580, 1175], [650, 1130], [1605, 620], [1220, 580], [1465, 200], [1530, 5], [845, 680], [725, 370], [145, 665], [415, 635], [510, 875], [560, 365], [300, 465], [520, 585], [480, 415], [835, 625], [975, 580], [1215, 245], [1320, 315], [1250, 400], [660, 180], [410, 250], [420, 555], [575, 665], [1150, 1160], [700, 580], [685, 595], [685, 610], [770, 610], [795, 645], [720, 635], [760, 650], [475, 960], [95, 260], [875, 920], [700, 500], [555, 815], [830, 485], [1170, 65], [830, 610], [605, 625], [595, 360], [1340, 725], [1740, 245]]
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optimal = 7542
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temperature = 10000
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cooling_rate = 0.999
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temperature_ok = 0.01
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max_times = [1, 2, 5]
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iterations = 2
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best_distances = []
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times = []
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colors = [
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'#1f77b4', # Bleu moyen
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'#ff7f0e', # Orange
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'#2ca02c', # Vert
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'#d62728', # Rouge
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'#9467bd', # Violet
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'#8c564b', # Marron
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'#e377c2', # Rose
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'#7f7f7f', # Gris
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'#bcbd22', # Vert olive
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'#17becf', # Turquoise
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'#1b9e77', # Vert Teal
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'#d95f02', # Orange foncé
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'#7570b3', # Violet moyen
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'#e7298a', # Fuchsia
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'#66a61e', # Vert pomme
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'#e6ab02', # Jaune or
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'#a6761d', # Bronze
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'#666666', # Gris foncé
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'#f781bf', # Rose clair
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'#999999', # Gris moyen
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]
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for max_time in max_times:
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for iteration in range(iterations):
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simulated_annealing = SimulatedAnnealing(cities, temperature=10000, cooling_rate=0.999, temperature_ok=0.01)
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print("Running iteration number {}/{} ({} sec)".format(iteration + 1, iterations, max_time))
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best_distance, best_route = SimulatedAnnealing.run()
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best_distances.append([best_distance, colors[max_times.index(max_time) % len(colors)]])
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times.append(max_time)
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title = ""
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title += "Best distance per iterations\n"
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title += "Temperature: " + str(temperature) + " "
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title += "Cooling rate: " + str(cooling_rate) + " "
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title += "Temperature ok: " + str(temperature_ok) + " "
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plt.title(title)
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plt.xlabel('Iteration')
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plt.ylabel('Distance')
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plt.axhline(y=optimal, color='r')
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distances = [x[0] for x in best_distances] # Extractions des valeurs
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for best_distance in best_distances:
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print(best_distance)
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max_dist = max(distances)
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plt.ylim(0, max_dist+max_dist*0.2)
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values = [item[0] for item in best_distances]
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colors = [item[1] for item in best_distances]
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bars = plt.bar(range(len(values)), values, color=colors)
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for i, bar in enumerate(bars):
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yval = bar.get_height()
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plt.text(bar.get_x() + bar.get_width()/2, yval + 0.05,
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"dist: {}\ntime: {}s".format(int(yval), times[i]),
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rotation=75, ha='center', va='bottom')
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plt.xticks(range(len(values)), [str(i+1) for i in range(len(values))])
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plt.show() |