Created
July 28, 2020 01:17
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build_dataset LSTM.py
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# make dataset to input | |
def build_dataset(time_series, seq_length): | |
dataX = [] | |
dataY = [] | |
for i in range(0, len(time_series) - seq_length): | |
_x = time_series[i:i + seq_length, :] | |
_y = time_series[i + seq_length, [-1]] # Next close price | |
print(_x, "->", _y) | |
dataX.append(_x) | |
dataY.append(_y) | |
return np.array(dataX), np.array(dataY) |
Author
alik604
commented
Jul 28, 2020
import numpy as np
def to_sequences(seq_size, obs):
x = []
y = []
for i in range(len(obs)-SEQUENCE_SIZE-1):
#print(i)
window = obs[i:(i+SEQUENCE_SIZE)]
after_window = obs[i+SEQUENCE_SIZE]
window = [[x] for x in window]
#print("{} - {}".format(window,after_window))
x.append(window)
y.append(after_window)
return np.array(x),np.array(y)
SEQUENCE_SIZE = 25
x_train,y_train = to_sequences(SEQUENCE_SIZE,spots_train)
x_test,y_test = to_sequences(SEQUENCE_SIZE,spots_test)
print("Shape of training set: {}".format(x_train.shape))
print("Shape of test set: {}".format(x_test.shape))
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