On Sun, May 3, 2009 at 8:15 PM, Chris Colbert <sccolb...@gmail.com> wrote: > in my endless pursuit of perfomance, i'm searching for a quick way to create > a 3d histogram from a 3d rgb image. > > Here is what I have so far for a (16,16,16) 3d histogram: > > def hist3d(imgarray): > histarray = N.zeros((16, 16, 16)) > temp = imgarray.copy() > (i, j) = imgarray.shape[0:2] > temp = (temp - temp % 16) / 16 > for a in range(i): > for b in range(j): > (b1, b2, b3) = temp[a, b, :] > histarray[b1, b2, b3] += 1 > return histarray > > this works, but takes about 4 seconds for a 640x480 image. > > I tried doing the inverse of my previous post, namely replacing the nested > for loop with: > histarray[temp[:,:,0], temp[:,:,1], temp[:,:,2]] += 1 > > > but that doesn't work for whatever reason. It gives me number, but they're > incorrect. > > Any ideas?
I'm not sure what exactly you need, but did you look at np.histogramdd ? reading the help file, this might work numpy.histogramdd(temp[:,:,0].ravel(), temp[:,:,1].ravel(), temp[:,:,2].ravel(), bins=16) but I never used histogramdd. also looking at the source of numpy is often very instructive, lots of good tricks to find in there: np.source(np.histogramdd). Josef _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
