简化这些代码：import numpy as np import matplotlib.pyplot as plt import networkx as nx G1 = nx.DiGraph() G1.add_edge('V1', 'V2', capacity=70) G1.add_edge('V1', 'V3', capacity=100) G1.add_edge('V1', 'V4', capacity=90) G1.add_edge('V2', 'V6', capacity=80) G1.add_edge('V3', 'V4', capacity=40) G1.add_edge('V3', 'V5', capacity=70) G1.add_edge('V4', 'V5', capacity=40) G1.add_edge('V4', 'V6', capacity=100) G1.add_edge('V5', 'V6', capacity=90) from networkx.algorithms.flow import edmonds_karp maxFlowValue, maxFlowDict = nx.maximum_flow(G1, 'V1', 'V6', flow_func=edmonds_karp) edgeCapacity = nx.get_edge_attributes(G1, 'capacity') edgeLabel = {} for i in edgeCapacity.keys(): edgeLabel[i] = f'c={edgeCapacity[i]:}' edgeLists = [] for i in maxFlowDict.keys(): for j in maxFlowDict[i].keys(): edgeLabel[(i, j)] += ',f=' + str(maxFlowDict[i][j]) if maxFlowDict[i][j] > 0: edgeLists.append((i,j)) print("最大流值: ", maxFlowValue) print("最大流的路径：", edgeLists) print("最大流的途径及流量: ", maxFlowDict) fig, ax = plt.subplots(figsize=(8, 6)) pos = {'V1': (3, 3.5), 'V2': (4, 4), 'V3': (4, 3), 'V4': (5, 3.5), 'V5': (5.5, 3), 'V6': (6.5, 3.5) } edge_labels = nx.get_edge_attributes(G1, 'capacity') ax.set_title("abcd") nx.draw(G1, pos, with_labels=True, node_color='c', node_size=300, font_size=10) nx.draw_networkx_edge_labels(G1, pos, edgeLabel, font_color='navy') nx.draw_networkx_edges(G1, pos, edgelist=edgeLists, edge_color='m') plt.axis('on') plt.show()

以下是代码的简化版：

import networkx as nx
import matplotlib.pyplot as plt

# 创建有向图并添加边
G1 = nx.DiGraph()
edges = [('V1', 'V2', 70), ('V1', 'V3', 100), ('V1', 'V4', 90), ('V2', 'V6', 80), ('V3', 'V4', 40),
         ('V3', 'V5', 70), ('V4', 'V5', 40), ('V4', 'V6', 100), ('V5', 'V6', 90)]
G1.add_weighted_edges_from(edges, weight='capacity')

# 计算最大流
max_flow_value, max_flow_dict = nx.maximum_flow(G1, 'V1', 'V6')

# 获取每条边的容量和流量信息
edge_labels = {(u, v): f'c={d["capacity"]},f={max_flow_dict[u][v]}' for u, v, d in G1.edges(data=True)}

# 获取最大流的路径和边列表
edge_lists = [(u, v) for u in max_flow_dict for v in max_flow_dict[u] if max_flow_dict[u][v] > 0]

# 输出结果
print("最大流值: ", max_flow_value)
print("最大流的路径：", edge_lists)
print("最大流的途径及流量: ", max_flow_dict)

# 绘制有向图
fig, ax = plt.subplots(figsize=(8, 6))
pos = {'V1': (3, 3.5), 'V2': (4, 4), 'V3': (4, 3), 'V4': (5, 3.5), 'V5': (5.5, 3), 'V6': (6.5, 3.5)}
nx.draw(G1, pos, with_labels=True, node_color='c', node_size=300, font_size=10)
nx.draw_networkx_edge_labels(G1, pos, edge_labels, font_color='navy')
nx.draw_networkx_edges(G1, pos, edgelist=edge_lists, edge_color='m')
plt.axis('on')
plt.title("abcd")
plt.show()