Thank you all, all of these methods work well  :) ---- ZHUO QL (KDr2) http://kdr2.com On Thursday, November 30, 2017, 2:26:16 AM GMT+8, Eric Hermes wrote: On Wed, 2017-11-29 at 12:00 -0500, numpy-discussion-request@python.org wrote:

Date: Wed, 29 Nov 2017 14:56:28 +0000 (UTC) From: "ZHUO QL (KDr2)" To: Discussion of Numerical Python Subject: [Numpy-discussion] Is there a way that indexing a matrix of     data with a matrix of indices? Message-ID: <360382279.3966234.1511967388050@mail.yahoo.com> Content-Type: text/plain; charset="utf-8"

Hi, all suppose: - D, is the data matrix, its shape is? M x N- I, is the indices matrix, its shape is M x K,? K<=N Is there a efficient way to get a Matrix R with the same shape of I so that R[x,y] = D[x, I[x,y]] ? A nested for-loop or list-comprehension is too slow for me.?? Thanks.

I don't know if this will be substantially faster, but you can try the following: I += np.array(range(M))[:, np.newaxis] * N R = D.ravel()[I.ravel()].reshape((M, K)) Eric

---- ZHUO QL (KDr2) http://kdr2.com