Comments (1)
Let's check!
from __future__ import division
import numpy as np
def split_and_normalize_prices(seq, input_size):
seq = [np.array(seq[i * input_size: (i + 1) * input_size]) for i in range(len(seq) // input_size)]
print "After split:", seq
seq = [seq[0] / seq[0][0] - 1.0] + [curr / seq[i][-1] - 1.0 for i, curr in enumerate(seq[1:])]
print "After normalization:", seq
return seq
With this function defined, split_and_normalize_prices(range(1, 11), 4)
prints out:
After split: [array([1, 2, 3, 4]), array([5, 6, 7, 8])]
After normalization: [array([ 0., 1., 2., 3.]), array([ 0.25, 0.5 , 0.75, 1. ])]
I believe this is expected behavior :)
from stock-rnn.
Related Issues (20)
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