如何在二维数组中正确赋值？

Question

我正在尝试为图中节点的每个子集分配一个热编码。下面是我正在尝试的代码

import networkx as nx
import numpy as np
graph=nx.karate_club_graph()
nodes=list(graph.nodes())
n=graph.number_of_nodes()
subset_nodes=[1,2]

for v in subset_nodes:
    y=nodes.index(v)
    prob_vec=np.zeros((n,n))
    prob_vec[0][y]=1
    print(prob_vec)

我得到这个结果

[0. 1. 0. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]
 ...
 [0. 0. 0. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]]
[[0. 0. 1. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]
 ...
 [0. 0. 0. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]]

I expect a matrix, with the subset nodes rows contains one hot encoding(1 value for each node in the subset node and others being zeros) like below:
[0. 1. 0. ... 0. 0. 0.]
 [0.0 . 1. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]
 ...
 [0. 0. 0. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]]

任何帮助将不胜感激

Answer 1

如果我明白你想做什么，我认为你需要稍微调整一下你的代码。您当前正在打印每个循环并将每个循环的 prob_vec 重置为 0。我想你想做更多像这样的事情：

import networkx as nx
import numpy as np
graph=nx.karate_club_graph()
nodes=list(graph.nodes())
n=graph.number_of_nodes()
subset_nodes=[1,2]

prob_vec=np.zeros((n,n))
for v in range(n):
  y = nodes.index(v)
  if y in subset_nodes:
    prob_vec[v][y]=1

print(prob_vec)

这输出：

[[0. 0. 0. ... 0. 0. 0.]
 [0. 1. 0. ... 0. 0. 0.]
 [0. 0. 1. ... 0. 0. 0.]
 ...
 [0. 0. 0. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]
 [0. 0. 0. ... 0. 0. 0.]]

如何在二维数组中正确赋值？

How to correctly assign values in 2D array?

python

graph

data-mining