图中边的随机删除

Question

我试图删除一个随机过程中的边作为p的函数，其中p是从0到1。在第一次迭代中，从图中随机删除0.1或10%的节点。在第二次迭代中，20%的剩余边被删除，以此类推。 我的错误发生在被删除的边再次出现在随机函数中。你知道吗

我的尝试：

import networkx as nx
import random
import numpy as np
graph = nx.fast_gnp_random_graph(20,0.3)



p_values = [0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9]


for i in p_values:
    print(i)

for i in p_values:

    array=[]    

    n=nx.number_of_edges(graph)
    edges = list(graph.edges)

    no_edges_del = int(n*i)
    print(no_edges_del)

    for j in range(no_edges_del):
        chosen_edge = random.choice(edges)
        print(chosen_edge)
        print(chosen_edge[0])
        graph.remove_edge(chosen_edge[0], chosen_edge[1])

        GC = nx.number_of_nodes(max(nx.connected_component_subgraphs(graph), key=len))

        array.append(GC/n)      

错误-

Traceback (most recent call last):
  File "1.py", line 26, in <module>
    graph.remove_edge(chosen_edge[0], chosen_edge[1])
  File "D:\anaconda\lib\site-packages\networkx\classes\graph.py", line 1011, in remove_edge
    raise NetworkXError("The edge %s-%s is not in the graph" % (u, v))
networkx.exception.NetworkXError: The edge 14-15 is not in the graph

Answer 1

在for循环开始之前得到一组边。当从图形中删除边时，需要从该集中删除边，以便在以后的迭代中不再选择它们。你知道吗

或者，在选择要删除的边之前，从每次迭代的图中获取边集。你知道吗

Answer 2

解决方案如下。
在每次迭代中，考虑当前百分比p并删除p*number_of_remaining_edges边。你知道吗

import random
import networkx as nx

g = nx.fast_gnp_random_graph(20,0.3)
p_values = [0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9]

for p in p_values:
    g.remove_edges_from(random.sample(g.edges(),k=int(p*g.number_of_edges())))