KoopmanESN/TrajTrans/StateOnly/ESN/AutoEncoderProcess.py

import torch
import numpy as np
import matplotlib.pyplot as plt

DeepKoopmanModel = torch.load('./ModelLib/DeepKoopmanModel.pt', map_location="cpu")

DataNor = np.loadtxt('./DataLib/DataNor.csv', delimiter=',')
DataNor = torch.from_numpy(DataNor).float()

Latent = DeepKoopmanModel.encoder(DataNor)
Latent = Latent.detach().numpy()

Max = np.max(Latent, axis=0)
Min = np.min(Latent, axis=0)
LatentMaxMin = np.vstack([Max, Min])
LatentNor = 2*(Latent-Min)/(Max-Min)-1

np.savetxt('./DataLib/Latent.csv', Latent, delimiter=',')
np.savetxt('./DataLib/LatentNor.csv', LatentNor, delimiter=',')
np.savetxt('./DataLib/LatentMaxMin', LatentMaxMin, delimiter=',')

plt.figure()
plt.plot(LatentNor[:, 30])
plt.show()