Stride를 이용한 속도 최적화( Slicing )

In [82]:

import numpy as np
from timeit import timeit
from numpy.lib.stride_tricks import as_strided

In [83]:

prices = np.random.randn(100)

In [84]:

prices.shape

Out[84]:

(100,)

In [85]:

window = 10

In [87]:

def make_X1():
    X1 = np.zeros([len(prices) - window, window])
    for day in range(len(X1)):
        X1[day, : ] = prices[day: day+window]
    return X1

In [81]:

def make_X2():
    stride, = prices.strides
    desited_shape = [ len(prices) - window , window ]
    
    X2 = as_strided( prices, desited_shape, strides = [stride, stride], writeable = False )
    return X2

In [88]:

timeit(make_X1)

Out[88]:

59.9649412

[ i for i in range ( 101 )] 

In [163]:

prices = [[ 1,2,3,4,5 ],[ 5, 4, 3, 2, 1 ],[ 1, 2, 3, 4, 5 ],[ 5, 4, 3, 2, 1 ],[ 1, 2, 3, 4, 5 ]]

In [168]:

X3 = as_strided(  prices, (2, 2), strides = [ 20 , 4], writeable = True  )

In [169]:

X3

Out[169]:

array([[1, 2],
       [5, 4]])