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- import numpy as np
- import torch
- Data = np.loadtxt('./DataLib/Data.csv', delimiter=',')
- NumState = 13
- DataState = Data[:, :NumState]
- DataStateMax = np.max(DataState, axis=0)
- DataStateMin = np.min(DataState, axis=0)
- DataStateMaxMin = np.vstack([DataStateMax, DataStateMin])
- print(DataStateMaxMin)
- DataStateNor = 2*(DataState - DataStateMin) / (DataStateMax - DataStateMin) - 1
- np.savetxt('./DataLib/DataNor.csv', DataStateNor, delimiter=',')
- DataStateNor = torch.tensor(DataStateNor, dtype=torch.float32)
- torch.save(DataStateNor, './DataLib/Data.pt')
- np.savetxt('./DataLib/DataStateMaxMin.csv', DataStateMaxMin, delimiter=',')
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