python – numpy / scipy,遍历子数组

for y in xrange(0,height,8):
    for x in xrange(0,width,8):
        d = image_data[y:y+8,x:x+8]
        # further processing on the 8x8-block

我不禁想知道是否有办法使用我可以使用的numpy / scipy来操作此操作或其他方法？某种迭代器？

一个MWE1：

#!/usr/bin/env python

import sys
import numpy as np
from scipy.fftpack import dct,idct
import scipy.misc
import matplotlib.pyplot as plt

def dctdemo(coeffs=1):
    unzig = np.array([
         0,1,8,16,9,2,3,10,17,24,32,25,18,11,4,5,12,19,26,33,40,48,41,34,27,20,13,6,7,14,21,28,35,42,49,56,57,50,43,36,29,22,15,23,30,37,44,51,58,59,52,45,38,31,39,46,53,60,61,54,47,55,62,63])

    lena = scipy.misc.lena()
    width,height = lena.shape

    # reconstructed
    rec = np.zeros(lena.shape,dtype=np.int64)

    # Can this part be vectorized?
    for y in xrange(0,8):
        for x in xrange(0,8):
            d = lena[y:y+8,x:x+8].astype(np.float)
            D = dct(dct(d.T,norm='ortho').T,norm='ortho').reshape(64)
            Q = np.zeros(64,dtype=np.float)
            Q[unzig[:coeffs]] = D[unzig[:coeffs]]
            Q = Q.reshape([8,8])
            q = np.round(idct(idct(Q.T,norm='ortho'))
            rec[y:y+8,x:x+8] = q.astype(np.int64)

    plt.imshow(rec,cmap='gray')
    plt.show()

if __name__ == '__main__':
    try:
        c = int(sys.argv[1])
    except ValueError:
        sys.exit()
    else:
        if 1 <= int(sys.argv[1]) <= 64:
            dctdemo(int(sys.argv[1]))

脚注：

>实际应用：https://github.com/figgis/dctdemo