Python快速获取已知城市坐标的距离矩阵
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Python快速获取已知城市坐标的距离矩阵
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def compute_euclidean_distance_matrix(locations):"""獲取坐標的距離矩陣"""distances = {}for from_counter, from_node in enumerate(locations):distances[from_counter] = {}for to_counter, to_node in enumerate(locations):if from_counter == to_counter:distances[from_counter][to_counter] = 0else:# Euclidean distancedistances[from_counter][to_counter] = (int(math.hypot((from_node[0] - to_node[0]),(from_node[1] - to_node[1]))))return distances
其中,locations的標準格式如下:
locations = [(288, 149), (288, 129), (270, 133), (256, 141), (256, 157), (246, 157),(236, 169), (228, 169), (228, 161), (220, 169), (212, 169), (204, 169),(196, 169), (188, 169), (196, 161), (188, 145), (172, 145), (164, 145),(156, 145), (148, 145), (140, 145), (148, 169), (164, 169), (172, 169),(156, 169), (140, 169), (132, 169), (124, 169), (116, 161), (104, 153),(104, 161), (104, 169), (90, 165), (80, 157), (64, 157), (64, 165),(56, 169), (56, 161), (56, 153), (56, 145), (56, 137), (56, 129),(56, 121), (40, 121), (40, 129), (40, 137), (40, 145), (40, 153),(40, 161), (40, 169), (32, 169), (32, 161), (32, 153), (32, 145),(32, 137), (32, 129), (32, 121), (32, 113), (40, 113), (56, 113),(56, 105), (48, 99), (40, 99), (32, 97), (32, 89), (24, 89),(16, 97), (16, 109), (8, 109), (8, 97), (8, 89), (8, 81),(8, 73), (8, 65), (8, 57), (16, 57), (8, 49), (8, 41),(24, 45), (32, 41), (32, 49), (32, 57), (32, 65), (32, 73),(32, 81), (40, 83), (40, 73), (40, 63), (40, 51), (44, 43),(44, 35), (44, 27), (32, 25), (24, 25), (16, 25), (16, 17),(24, 17), (32, 17), (44, 11), (56, 9), (56, 17), (56, 25),(56, 33), (56, 41), (64, 41), (72, 41), (72, 49), (56, 49),(48, 51), (56, 57), (56, 65), (48, 63), (48, 73), (56, 73),(56, 81), (48, 83), (56, 89), (56, 97), (104, 97), (104, 105),(104, 113), (104, 121), (104, 129), (104, 137), (104, 145), (116, 145),(124, 145), (132, 145), (132, 137), (140, 137), (148, 137), (156, 137),(164, 137), (172, 125), (172, 117), (172, 109), (172, 101), (172, 93),(172, 85), (180, 85), (180, 77), (180, 69), (180, 61), (180, 53),(172, 53), (172, 61), (172, 69), (172, 77), (164, 81), (148, 85),(124, 85), (124, 93), (124, 109), (124, 125), (124, 117), (124, 101),(104, 89), (104, 81), (104, 73), (104, 65), (104, 49), (104, 41),(104, 33), (104, 25), (104, 17), (92, 9), (80, 9), (72, 9),(64, 21), (72, 25), (80, 25), (80, 25), (80, 41), (88, 49),(104, 57), (124, 69), (124, 77), (132, 81), (140, 65), (132, 61),(124, 61), (124, 53), (124, 45), (124, 37), (124, 29), (132, 21),(124, 21), (120, 9), (128, 9), (136, 9), (148, 9), (162, 9),(156, 25), (172, 21), (180, 21), (180, 29), (172, 29), (172, 37),(172, 45), (180, 45), (180, 37), (188, 41), (196, 49), (204, 57),(212, 65), (220, 73), (228, 69), (228, 77), (236, 77), (236, 69),(236, 61), (228, 61), (228, 53), (236, 53), (236, 45), (228, 45),(228, 37), (236, 37), (236, 29), (228, 29), (228, 21), (236, 21),(252, 21), (260, 29), (260, 37), (260, 45), (260, 53), (260, 61),(260, 69), (260, 77), (276, 77), (276, 69), (276, 61), (276, 53),(284, 53), (284, 61), (284, 69), (284, 77), (284, 85), (284, 93),(284, 101), (288, 109), (280, 109), (276, 101), (276, 93), (276, 85),(268, 97), (260, 109), (252, 101), (260, 93), (260, 85), (236, 85),(228, 85), (228, 93), (236, 93), (236, 101), (228, 101), (228, 109),(228, 117), (228, 125), (220, 125), (212, 117), (204, 109), (196, 101),(188, 93), (180, 93), (180, 101), (180, 109), (180, 117), (180, 125),(196, 145), (204, 145), (212, 145), (220, 145), (228, 145), (236, 145),(246, 141), (252, 125), (260, 129), (280, 133)]總結
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