On Aug 27, 2004, at 8:34 PM, Russell E. Owen wrote:
Any suggestions on an efficient means to bin a 2-d array? REBIN is the IDL function I'm trying to mimic. Binning allows one to combine sets of pixels from one array to form a new array that is smaller by a given factor along each dimension.
To nxm bin a 2-dimensional array, one averages (or sums or ?) each nxm block of entries from the input image to form the corresponding entry of the output image.
For example, to 2x2 bin a two-dimensional image, one would: average (0,0), (0,1), (1,0), (1,1) to form (0,0) average (0,2), (0,3), (1,2), (1,3) to form (0,1) ...
In case it helps, in my immediate case I'm binning a boolean array (a mask) and thus can live with almost any kind of combination.
Note that a boxcar smoothing costs no more than doing the above averaging. So in numarray, you could do the following: from numarray.convolve import boxcar b = boxcar(a, (n,n)) rebinnedarray = b[::n,::n].copy() or something like this (I haven't tried to figure out the correct offset for the slice) where one wants to rebin by a factor of n in both dimensions. We should probably add a built in function to do this. Perry