from sample import Sample
from train import train
from random import randint
import numpy as np
from tensorflow import keras
window_size = 20
s = Sample()
X_train, X_test, y_train, y_test = s.getData(window_size, True)
checkpoint_name = "checkpoint-epoch_018.hdf5"
num_predict_windows = 2000
if len(checkpoint_name) == 0:
model, history = train(X_train, X_test, y_train, y_test, window_size)
else:
model = keras.models.load_model("experiments/checkpoints/" +
checkpoint_name)
predictWindows = list(X_test[randint(0, len(X_test))])
while len(predictWindows) < num_predict_windows:
l = len(predictWindows)
inp = np.array([predictWindows[l - window_size:l]])
pred = model.predict(inp)
predictWindows.append(pred[0])
s.toFile(predictWindows)
