Vincent, Pauli,
> From: Vincent Schut <sc...@sarvision.nl> > - an other option would be some smart reshaping, which finally gives you > a [y//2, x//2, 2, 2] array, which you could then reduce to calculate > stats (mean, std, etc) on the last two axes. I *think* you'd have to > first reshape both x and y axes, and then reposition the axes. An > example: > a = gdal_array.BandReadAsArray(blabla) > y,x = a.shape #y and x need be divideable by 2! > b = a.reshape(y/2, 2, x/2, x).transpose(0,2,1,3).reshape(y/2, x/2, 4) > bMean = b.mean(axis=-1) > bMax = ......etc. You and Pauli agree on this - seems like a good option. > - a third option would be to create an index array, which has a unique > value per 2x2 square, and then use histogram2d. This would, if you use > its 'weight' functionality, at least enable you to get efficient counts > and sums/means. Other stats might be hard, though. Hmmmm I don't get this, but I'll experiment. I've seen some really useful things done with histogram2d so it seems worthwhile to figure out. > Message: 6 > From: Pauli Virtanen <p...@iki.fi> > > Let's say the image looks like this: np.random.randint(0,2, > > 16).reshape(4,4) > > > > array([[0, 0, 0, 1], > > [0, 0, 1, 1], > > [1, 1, 0, 0], > > [0, 0, 0, 0]]) > > > > I want to use a square, non-overlapping moving window for resampling, so > > that I get a count of all the 1's in each 2x2 window. > > > > 0, 0, 0, 1 > > 0, 0, 1, 1 0 3 > > => 2 0 > > 1, 1, 0, 0 > > 0, 0, 0, 0 > > > > In another situation with similar data I'll need the average, or the > > maximum value, etc.. > > Non-overlapping windows can be done by reshaping: > > x = np.array([[0, 0, 0, 1, 1, 1], > [0, 0, 1, 1, 0, 0], > [1, 1, 0, 0, 1, 1], > [0, 0, 0, 0, 1, 1], > [1, 0, 1, 0, 1, 1], > [0, 0, 1, 0, 0, 0]]) > > y = x.reshape(3,2,3,2) > y2 = y.sum(axis=3).sum(axis=1) This is perfect - and so fast! Thanks! Now I just have to understand why it works ... Can anyone recommend a tutorial on working with (slicing, reshaping, etc.) multi-dimensional arrays? Stefan's slides are beautiful but my brain starts to hurt if I try to follow them line by line. -Robin _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
