我正在嘗試為圖中節(jié)點(diǎn)的每個(gè)子集分配一個(gè)熱編碼。下面是我正在嘗試的代碼import networkx as nximport numpy as npgraph=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)我得到這個(gè)結(jié)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.]]任何幫助都感激不盡
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小唯快跑啊
TA貢獻(xiàn)1863條經(jīng)驗(yàn) 獲得超2個(gè)贊
如果我明白你想要做什么，我認(rèn)為你需要稍微調(diào)整你的代碼。您當(dāng)前正在打印每個(gè)循環(huán)并將每個(gè)循環(huán)的 prob_vec 重置為 0。我認(rèn)為你想做更多這樣的事情：
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)
這輸出：
[[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.]]
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