帮我修改一下这段代码的错误import networkx as nx G = nx.DiGraph() start = [1, 3, 5, 7] to = [2, 4, 6, 8] for j in range(len(start)): G.add_edge(start[j], to[j]) nx.draw(G, with_lables=True)

import networkx as nx

G = nx.DiGraph()

start = [1, 3, 5, 7]
to = [2, 4, 6, 8]

for j in range(len(start)):
G.add_edge(start[j], to[j])

nx.draw(G, with_labels=True)

# 你在原来的代码中写成了 with_lables，正确的参数名称应该是 with_labels。此外，你需要在绘图之前先添加边。

相关问题

import pandas as pd import numpy as np import networkx as nx import matplotlib.pyplot as plt df = pd.read_excel(r"C:\Users\li'yi'jie\Desktop\运筹学网络规划数据.xlsx") edges = [] for i in range(len(df)): edge = { "id": df.loc[i, "边的编号"], "tail": df.loc[i, "边的尾节点"], "head": df.loc[i, "边的头节点"], "length": df.loc[i, "长度"], "capacity": df.loc[i, "容量"] } edges.append(edge) plt.figure(figsize=(15,15)) G = nx.DiGraph() for edge in edges: G.add_edge(edge["tail"], edge["head"], weight=edge["length"]) pos = nx.spring_layout(G) nx.draw(G, pos, with_labels=True) labels = nx.get_edge_attributes(G, "weight") nx.draw_networkx_edge_labels(G, pos, edge_labels=labels) #nx.draw_networkx_edge_labels(G, pos, edge_labels=labels, label_pos=0.3) plt.show() all_pairs = dict(nx.all_pairs_dijkstra_path_length(G)) rows = [] for start_node, dist_dict in all_pairs.items(): for end_node, dist in dist_dict.items(): rows.append({'起始节点': start_node, '终止节点': end_node, '最短路径长度': dist}) df_result = pd.DataFrame(rows) df_result.to_excel('all_pairs.xlsx', index=False)请问在写入excel的时候，能否把经过的边的编号一起写入呢？麻烦给下修改后的代码，谢谢你！

可以在遍历最短路径的时候记录下经过的边的编号，然后将其存储到结果表格中。以下是修改后的代码：

import pandas as pd
import numpy as np
import networkx as nx
import matplotlib.pyplot as plt

df = pd.read_excel(r"C:\Users\li'yi'jie\Desktop\运筹学网络规划数据.xlsx")

edges = []
for i in range(len(df)):
    edge = {
        "id": df.loc[i, "边的编号"],
        "tail": df.loc[i, "边的尾节点"],
        "head": df.loc[i, "边的头节点"],
        "length": df.loc[i, "长度"],
        "capacity": df.loc[i, "容量"]
    }
    edges.append(edge)

plt.figure(figsize=(15,15))
G = nx.DiGraph()
for edge in edges:
    G.add_edge(edge["tail"], edge["head"], weight=edge["length"])

pos = nx.spring_layout(G)
nx.draw(G, pos, with_labels=True)
labels = nx.get_edge_attributes(G, "weight")
nx.draw_networkx_edge_labels(G, pos, edge_labels=labels)
#plt.draw()
plt.show()

all_pairs = dict(nx.all_pairs_dijkstra_path(G))

rows = []
for start_node, paths in all_pairs.items():
    for end_node, path in paths.items():
        path_edges = []
        for i in range(len(path)-1):
            edge_id = G[path[i]][path[i+1]]['id']
            path_edges.append(edge_id)
        row = {
            '起始节点': start_node,
            '终止节点': end_node,
            '最短路径长度': nx.dijkstra_path_length(G, start_node, end_node),
            '经过的边编号': path_edges
        }
        rows.append(row)

df_result = pd.DataFrame(rows)
df_result.to_excel('all_pairs.xlsx', index=False)

修改后的代码中，我们在遍历最短路径时，记录下了经过的边的编号，并将其存储到结果表格的“经过的边编号”一列中。

Traceback (most recent call last): File "C:\Users\ying\Desktop\pythonProject5\main.py", line 84, in <module> end_times = nx.dag_late_finish(G, start_times) AttributeError: module 'networkx' has no attribute 'dag_late_finish'如何解决

这个错误是因为 `networkx` 模块中没有 `dag_late_finish` 属性。这个属性在较早的版本中可能存在，但在最新版本中已被删除。

你可以使用 `networkx` 中的 `topological_sort` 函数来实现类似的功能。下面是一个示例：

import networkx as nx

G = nx.DiGraph()
# 添加节点和边

start_times = nx.topological_sort(G)
end_times = {node: max(end_times.get(child, 0) for child in G.successors(node)) + weight for node, weight in G.nodes(data="weight")}

在这个示例中，我们使用了 `topological_sort` 函数来获取拓扑排序后的节点列表，然后使用一个字典推导式计算每个节点的最晚完成时间。

你可以根据你的具体需求进行修改。