[Numpy-discussion] Possible bug in Numpy.convolve
Thøger Emil Rivera-Thorsen
thoger.emil at gmail.com
Wed Mar 22 22:44:04 EDT 2017
OK, this is embarrassing.
I had in fact made the kernel only almost symmetric, it was slightly
offset to one side.
This caused it. Only a wetware bug.
Sorry for having wasted your time!
On 03/23/2017 03:38 AM, josef.pktd at gmail.com wrote:
>
>
> On Wed, Mar 22, 2017 at 10:06 PM, Thøger Emil Rivera-Thorsen
> <thoger.emil at gmail.com <mailto:thoger.emil at gmail.com>> wrote:
>
> Dear list;
>
> 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 to illustrate.
>
> 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 Ubuntu 16.10
>
> 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 docstring.
>
> Cheers,
>
> Emil Rivera-Thorsen
>
>
>
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>
>
> Can you provide an example to replicate?
>
> I haven't seen this behavior, it looks centered to me, at least for
> odd window length..
> AFAIR, I had to try a bit in the past for how to set the window and
> location with even window length.
>
> >>> np.__version__
> '1.11.2'
>
> >>> x = np.linspace(-1, 1, 21)
> >>> w = stats.norm.pdf(np.linspace(-3, 3, 5))
> >>> np.column_stack((x, np.convolve(x, w, mode='same')))[8:13]
> array([[ -2.00000000e-01, -1.33368234e-01],
> [ -1.00000000e-01, -6.66841169e-02],
> [ 0.00000000e+00, 1.51788304e-17],
> [ 1.00000000e-01, 6.66841169e-02],
> [ 2.00000000e-01, 1.33368234e-01]])
>
>
> >>> x = np.abs(np.linspace(-1, 1, 21))
> >>> w = stats.norm.pdf(np.linspace(-3, 3, 4))
> >>> np.column_stack((x, np.convolve(x, w, mode='same')))[8:13]
> array([[ 0.2 , 0.12320129],
> [ 0.1 , 0.07392077],
> [ 0. , 0.02552663],
> [ 0.1 , 0.02552663],
> [ 0.2 , 0.07392077]])
>
>
> >>> w = stats.norm.pdf(np.linspace(-3, 3, 5))
> >>> np.column_stack((x, np.convolve(x, w, mode='same')))[8:13]
> array([[ 0.2 , 0.13336823],
> [ 0.1 , 0.06757049],
> [ 0. , 0.02767626],
> [ 0.1 , 0.06757049],
> [ 0.2 , 0.13336823]])
>
> Josef
>
>
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