2008/8/26 Anne Archibald <[EMAIL PROTECTED]>: > 2008/8/22 Catherine Moroney <[EMAIL PROTECTED]>: >> I'm looking for a way to acccomplish the following task without lots >> of loops involved, which are really slowing down my code. >> >> I have a 128x512 array which I want to break down into 2x2 squares. >> Then, for each 2x2 square I want to do some simple calculations >> such as finding the maximum value, which I then store in a 64x256 >> array. > > You should be able to do some of this with reshape and transpose: > In [1]: import numpy as np > > In [3]: A = np.zeros((128,512)) > > In [4]: B = np.reshape(A,(64,2,256,2)) > > In [5]: C = np.transpose(B,(0,2,1,3)) > > In [6]: C.shape > Out[6]: (64, 256, 2, 2)
Or you can obtain a similar effect using my new favorite hammer: from numpy.lib import stride_tricks rows, cols = x.shape el = x.dtype.itemsize y = stride_tricks.as_strided(x, shape=(rows/2, cols/2, 2, 2), strides=(el*2*cols, el*2, el*cols, el)) Cheers Stéfan _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
