np.save(prefix+'data_'+save_name, x_input[:, 1:, :])
np.save(prefix+'v_'+save_name, v_input[1:, :])
np.save(prefix+'label_'+save_name, label[1:, :])
and I did some inspection of the saved train data, it's confirmed that they are all 0s:
>>> import numpy as np
>>> t = np.load("data/elect/train_data_elect.npy")
>>> np.max(t[:, 0, 0])
0.0
>>> np.min(t[:, 0, 0])
0.0
>>>
Hi,
I have a few questions about preprocess_elect.py:
in prep_data():
v_input[:, 1]is never used (read or write), so why you need this 2nd column?https://github.com/ant-research/Pyraformer/blob/master/preprocess_elect.py#L35
about x_input:
https://github.com/ant-research/Pyraformer/blob/master/preprocess_elect.py#L58
x_input[count, 1:, 0] from 1 onward, x_input contains the real raw input data, but
x_input[count, 0, 0]is never assigned, so it will remain all 0s, which means it does not contain any real raw input data(https://github.com/ant-research/Pyraformer/blob/master/preprocess_elect.py#L67 this line for x_input[count, 0, 0] is also zero)
why don't you just drop all such
x_input[:, 0, :], since they are the wrong training data? and why you want to save it in the final train npy file?i.e. change https://github.com/ant-research/Pyraformer/blob/master/preprocess_elect.py#L72-L74 to
and I did some inspection of the saved train data, it's confirmed that they are all 0s: