I am honestly not certain whether this, or the SciPy list, is the
appropriate place to post this; please let me know if I got it wrong.
I am convolving a 1D data set containing a relatively narrow peak, with
a relatively narrow Gaussian kernel, in order to emulate the effect of
atmospheric seeing on astrophysical observations.
I have a 1D data array 45 pixels long, and a Gaussian kernel, and run
np.convolve(data, kernel, mode='same') on the two arrays, the resulting
array's peak is shifted relative to the origin. I have attached a plot
The original data is shown in blue. When I convolve it with a symmetric
kernel (black), I get an offset resulting peak (magenta). If I flip the
kernel -- even though it is perfectly symmetric -- the resulting curve
is offset in the opposite direction (yellow). However, if I offset the
kernel so it is centered exactly one pixel below the central value, the
output array gets centered correct (red), even if I flip the (now no
longer symmetric) kernel.
This is using Numpy 1.11.3, python 2.7.13, on Anaconda 4.3.0 64-bit on
Using astropy.convolution, reproduces the correct red curve, so I can
use that for now, but it seems to me this is either a bug or, if it is
indeed the intended behavior, a word of caution would be merited in the
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