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def get_from_one(ts, window_size, stride): ts_length = ts.shape[0] print(ts_length) samples = [] for start in np.arange(0, ts_length, stride): if start + window_size > ts_length: break samples.append(ts[start:start + window_size]) return np.array(samples) 怎么感觉这个窗口化代码有问题呢,比如ts_length=128,windows=8,stride=1 最终代码得到的结果是 [0,1,2,3,4,5,6,7], [1,2,3,4,5,6,7,8], [2,3,4,5,6,7,8,9], ⋮ [120,121,122,123,124,125,126,127] 这个和你论文中叙述的不一样呀,按照你论文中的操作应该得到是 [0,1,2,3,4,5,6,7] [8,9,10,11,12,13,14,15] [16,17,18,19,20,21,22,23] ⋮ [120,121,122,123,124,125,126,127]
The text was updated successfully, but these errors were encountered:
我们做了多次实验,代码中的是效果最好的窗口化方法,没及时说给您带来误解很抱歉。
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def get_from_one(ts, window_size, stride):
ts_length = ts.shape[0]
print(ts_length)
samples = []
for start in np.arange(0, ts_length, stride):
if start + window_size > ts_length:
break
samples.append(ts[start:start + window_size])
return np.array(samples)
怎么感觉这个窗口化代码有问题呢,比如ts_length=128,windows=8,stride=1
最终代码得到的结果是
[0,1,2,3,4,5,6,7],
[1,2,3,4,5,6,7,8],
[2,3,4,5,6,7,8,9],
⋮
[120,121,122,123,124,125,126,127]
这个和你论文中叙述的不一样呀,按照你论文中的操作应该得到是
[0,1,2,3,4,5,6,7]
[8,9,10,11,12,13,14,15]
[16,17,18,19,20,21,22,23]
⋮
[120,121,122,123,124,125,126,127]
The text was updated successfully, but these errors were encountered: