nadavh at visionsense.com
Sat Aug 28 13:54:05 CDT 2004
For the most general form of binning I use a convolution (by a 2D mask) followed by a subsmapling.
For example for a 3x3 binning:
mask = ones((3,3))
binned = convolve2d(data,mask,'same')[1::3,1::3]
From: Russell E. Owen [mailto:owen at astro.washington.edu]
Sent: Sat 28-Aug-04 03:34
To: numpy-discussion at lists.sourceforge.net
Subject: [Numpy-discussion] rebin
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
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
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.
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