import networkx as nx import matplotlib.pyplot as plt # 输入数据 locations = [[125.330802,125.401931,125.326444,125.332284,125.322837,125.32563,125.334942,125.378548,125.386251,125.426883,125.42665,125.437111,125.453763,125.431396,125.430705,125.41968,125.437906,125.404171,125.385772,125.341942,125.341535,125.300812,125.307316,125.345642,125.331492,125.330322,125.284474,125.334851,125.30606,125.377211,125.381077,125.417041,125.41427,125.416371,125.432283,125.401676,125.403855,125.38582,125.426733,125.291], [43.917542,43.919075,43.905821,43.90266,43.900238,43.89703,43.888187,43.904508,43.892574,43.907904,43.896354,43.894605,43.889122,43.88774,43.882928,43.887149,43.8789,43.879647,43.883112,43.873763,43.861505,43.854652,43.876513,43.850479,43.833745,43.825044,43.812019,43.803154,43.793054,43.788869,43.824152,43.816805,43.801673,43.82893,43.83235,43.843713,43.854322,43.868372,43.871792,43.8306]] num_flights = 4 flight_capacity = [10, 10, 10, 10] # 将坐标转化为图 G = nx.Graph() for i in range(len(locations[0])): G.add_node(i+1, pos=(locations[0][i], locations[1][i])) for i in range(len(locations[0])): for j in range(i+1, len(locations[0])): dist = ((locations[0][i]-locations[0][j])**2 + (locations[1][i]-locations[1][j])**2)**0.5 G.add_edge(i+1, j+1, weight=dist) # 添加起点和终点 start_node = len(locations[0])+1 end_node = len(locations[0])+2 G.add_node(start_node, pos=(0, 0)) G.add_node(end_node, pos=(0, 0)) # 添加边和边权 for i in range(len(locations[0])): G.add_edge(start_node, i+1, weight=0) G.add_edge(i+1, end_node, weight=0) for f in range(num_flights): for i in range(len(locations[0])): G.add_edge(i+1, len(locations[0])+f*len(locations[0])+i+1, weight=0) G.add_edge(len(locations[0])+f*len(locations[0])+i+1, end_node, weight=0) # 添加航班容量的限制 for f in range(num_flights): for i in range(len(locations[0])): G.add_edge(len(locations[0])+f*len(locations[0])+i+1, len(locations[0])+f*len(locations[0])+len(locations[0])+1, weight=-flight_capacity[f]) #创造路径规划模型 path_model = nx.DiGraph() for i in range(len(locations[0])): for f in range(num_flights): for j in range(len(locations[0])): if i != j: path_model.add_edge(len(locations[0])+flen(locations[0])+i+1, len(locations[0])+flen(locations[0])+j+1, weight=G[i+1][j+1]['weight']+G[len(locations[0])+flen(locations[0])+i+1][len(locations[0])+f*len(locations[0])+j+1]['weight']) 添加航班时间的限制 for f in range(num_flights): for i in range(len(locations[0])): for j in range(len(locations[0])): if i != j: path_model.add_edge(len(locations[0])+f*len(locations[0])+i+1, len(locations[0])+((f+1)%num_flights)*len(locations[0])+j+1, weight=G[i+1][j+1]['weight']) 求解最短路径 path = nx.bellman_ford_path(path_model, source=start_node, target=end_node, weight='weight') 绘制路径图 pos = nx.get_node_attributes(G, 'pos') nx.draw_networkx_nodes(G, pos, node_size=50, node_color='w') nx.draw_networkx_labels(G, pos) nx.draw_networkx_edges(G, pos, edgelist=G.edges(), width=0.5) for f in range(num_flights): start = len(locations[0])+f*len(locations[0])+1 end = len(locations[0])+(f+1)*len(locations[0])+1 nx.draw_networkx_edges(G, pos, edgelist=path[start:end], edge_color='r', width=2.0, alpha=0.7) plt.axis('off') plt.show()找出错误并修改

在代码中，有一些语法错误和拼写错误。以下是修改后的代码：

import networkx as nx
import matplotlib.pyplot as plt

# 输入数据
locations = [
    [125.330802,125.401931,125.326444,125.332284,125.322837,125.32563,125.334942,125.378548,125.386251,125.426883,125.42665,125.437111,125.453763,125.431396,125.430705,125.41968,125.437906,125.404171,125.385772,125.341942,125.341535,125.300812,125.307316,125.345642,125.331492,125.330322,125.284474,125.334851,125.30606,125.377211,125.381077,125.417041,125.41427,125.416371,125.432283,125.401676,125.403855,125.38582,125.426733,125.291],
    [43.917542,43.919075,43.905821,43.90266,43.900238,43.89703,43.888187,43.904508,43.892574,43.907904,43.896354,43.894605,43.889122,43.88774,43.882928,43.887149,43.8789,43.879647,43.883112,43.873763,43.861505,43.854652,43.876513,43.850479,43.833745,43.825044,43.812019,43.803154,43.793054,43.788869,43.824152,43.816805,43.801673,43.82893,43.83235,43.843713,43.854322,43.868372,43.871792,43.8306]
]
num_flights = 4
flight_capacity = [10, 10, 10, 10]

# 将坐标转化为图
G = nx.Graph()
for i in range(len(locations[0])):
    G.add_node(i+1, pos=(locations[0][i], locations[1][i]))
for i in range(len(locations[0])):
    for j in range(i+1, len(locations[0])):
        dist = ((locations[0][i]-locations[0][j])**2 + (locations[1][i]-locations[1][j])**2)**0.5
        G.add_edge(i+1, j+1, weight=dist)

# 添加起点和终点
start_node = len(locations[0])+1
end_node = len(locations[0])+2
G.add_node(start_node, pos=(0, 0))
G.add_node(end_node, pos=(0, 0))

# 添加边和边权
for i in range(len(locations[0])):
    G.add_edge(start_node, i+1, weight=0)
    G.add_edge(i+1, end_node, weight=0)
for f in range(num_flights):
    for i in range(len(locations[0])):
        G.add_edge(i+1, len(locations[0])+f*len(locations[0])+i+1, weight=0)
        G.add_edge(len(locations[0])+f*len(locations[0])+i+1, end_node, weight=0)

# 添加航班容量的限制
for f in range(num_flights):
    for i in range(len(locations[0])):
        G.add_edge(len(locations[0])+f*len(locations[0])+i+1, len(locations[0])+f*len(locations[0])+len(locations[0])+1,
                   weight=-flight_capacity[f])

# 创造路径规划模型
path_model = nx.DiGraph()
for i in range(len(locations[0])):
    for f in range(num_flights):
        for j in range(len(locations[0])):
            if i != j:
                path_model.add_edge(len(locations[0])+f*len(locations[0])+i+1, len(locations[0])+f*len(locations[0])+j+1,
                                    weight=G[i+1][j+1]['weight']+G[len(locations[0])+f*len(locations[0])+i+1][len(locations[0])+f*len(locations[0])+j+1]['weight'])

# 添加航班时间的限制
for f in range(num_flights):
    for i in range(len(locations[0])):
        for j in range(len(locations[0])):
            if i != j:
                path_model.add_edge(len(locations[0])+f*len(locations[0])+i+1, len(locations[0])+((f+1)%num_flights)*len(locations[0])+j+1,
                                    weight=G[i+1][j+1]['weight'])

# 求解最短路径
path = nx.bellman_ford_path(path_model, source=start_node, target=end_node, weight='weight')

# 绘制路径图
pos = nx.get_node_attributes(G, 'pos')
nx.draw_networkx_nodes(G, pos, node_size=50, node_color='w')
nx.draw_networkx_labels(G, pos)
nx.draw_networkx_edges(G, pos, edgelist=G.edges(), width=0.5)
for f in range(num_flights):
    start = len(locations[0])+f*len(locations[0])+1
    end = len(locations[0])+(f+1)*len(locations[0])+1
    nx.draw_networkx_edges(G, pos, edgelist=path[start:end], edge_color='r', width=2.0, alpha=0.7)
plt.axis('off')
plt.show()