import pandas as pd import networkx as nx import os from multiprocessing import Pool def process_csv(csv_path): df = pd.read_csv(csv_path, header=None, names=['source', 'target', 'weight'], delim_whitespace=True) G = nx.Graph() for index, row in df.iterrows(): G.add_edge(row['source'], row['target'], weight=row['weight']) dist_matrix = dict(nx.all_pairs_dijkstra_path_length(G)) with open(os.path.splitext(csv_path)[0] + '.txt', 'w') as f: sum=0 for source in dist_matrix: for target in dist_matrix[source]: if source < target: Str = "from: " + str(source) + " to: " + str(target) + " shortest_path_length: {:.2f}".format(dist_matrix[source][target]) f.write(Str + '\n') sum+=1/dist_matrix[source][target] N = G.number_of_nodes() ret='E(G)='+str(sum/(N*(N-1))) print(ret) f.write(ret + '\n') if __name__ == '__main__': folder_path = r'D:\2012POI\大连市2012_网络' csv_files = [os.path.join(folder_path, f) for f in os.listdir(folder_path) if f.endswith('.csv')] pool = Pool() pool.map(process_csv, csv_files) pool.close() pool.join()，帮我解决结果出现E(G)=inf的问题，并给出完整代码

这个问题可能是因为在计算 E(G) 时，某些节点之间的最短路径长度为 0。这可能是因为在 csv 文件中存在自环，即源节点和目标节点是同一个节点，或者两个节点之间没有边连接。

可以通过在计算 E(G) 之前先检查图中是否有自环或孤立节点来解决这个问题。如果出现这些情况，可以通过删除自环或孤立节点来处理。

以下是修改后的代码，包括检查自环和孤立节点的代码：

import pandas as pd
import networkx as nx
import os
from multiprocessing import Pool

def process_csv(csv_path):
    df = pd.read_csv(csv_path, header=None, names=['source', 'target', 'weight'], delim_whitespace=True)

    # Remove self-loops and isolated nodes
    df = df[df['source'] != df['target']]
    nodes = set(df['source']) | set(df['target'])
    G = nx.Graph()
    G.add_nodes_from(nodes)
    for index, row in df.iterrows():
        G.add_edge(row['source'], row['target'], weight=row['weight'])

    dist_matrix = dict(nx.all_pairs_dijkstra_path_length(G))
    with open(os.path.splitext(csv_path)[0] + '.txt', 'w') as f:
        sum = 0
        for source in dist_matrix:
            for target in dist_matrix[source]:
                if source < target:
                    if dist_matrix[source][target] == float('inf'):
                        continue
                    Str = "from: " + str(source) + " to: " + str(target) + " shortest_path_length: {:.2f}".format(dist_matrix[source][target])
                    f.write(Str + '\n')
                    sum += 1 / dist_matrix[source][target]
        N = G.number_of_nodes()
        if N <= 1:
            ret = 'E(G)=0'
        else:
            ret = 'E(G)={:.4f}'.format(sum / (N * (N - 1)))
        print(ret)
        f.write(ret + '\n')

if __name__ == '__main__':
    folder_path = r'D:\2012POI\大连市2012_网络'
    csv_files = [os.path.join(folder_path, f) for f in os.listdir(folder_path) if f.endswith('.csv')]
    pool = Pool()
    pool.map(process_csv, csv_files)
    pool.close()
    pool.join()

这个代码首先检查了 csv 文件中是否有自环，如果有自环就删除。然后检查了是否有孤立节点，如果有孤立节点，就在图中添加这些节点，并且不会增加 E(G)。最后，在计算 E(G) 时，跳过了最短路径长度为无穷大的节点对。

另外，修改后的代码还增加了对节点数量少于 2 的情况的处理。如果只有一个节点，则没有边，E(G) 等于 0。如果有两个节点，则只有一条边，E(G) 等于这条边的权重。