MultivariateOrthogonalPolynomials.jl icon indicating copy to clipboard operation
MultivariateOrthogonalPolynomials.jl copied to clipboard
verified publisher icon JuliaApproximation

Lowering bug?

Open ioannisPApapadopoulos opened this issue 3 years ago • 8 comments

@dlfivefifty The lowering Zernike(0,1) \ Weighted(Zernike(0,1)) is a factor of 2 off. This also seems to be confirmed in the tests..?

https://github.com/JuliaApproximation/MultivariateOrthogonalPolynomials.jl/blob/cb0fb241eecc49fbdb873a5cd2b7de098897d355/test/test_disk.jl#L303

Is there a reason for this?

ioannisPApapadopoulos avatar Feb 17 '23 16:02 ioannisPApapadopoulos

No clue... maybe the weight has that factor of 2 in it?

dlfivefifty avatar Feb 26 '23 20:02 dlfivefifty

There's a factor 2 to some power in the polynomials defined im FastTransforms, see https://mikaelslevinsky.github.io/FastTransforms/transforms.html#disk2cxf

Maybe that's where this originates, some difference in conventions?

TSGut avatar Feb 27 '23 10:02 TSGut

Convenctions in Weighted vs. what the weighted is defined as? Should we change this to be consistent?

ioannisPApapadopoulos avatar Feb 27 '23 14:02 ioannisPApapadopoulos

I think so. This can lead to really nasty untraceable errors and doesn't make sense syntax wise.

TSGut avatar Feb 27 '23 14:02 TSGut

I think we should really focus on making things less consistent, not more

dlfivefifty avatar Feb 27 '23 21:02 dlfivefifty

Was gonna propose random complex phases to improve stability with a seed based on the SHA256 checksum of the user's System folder, but maybe that's still too consistent.

MikaelSlevinsky avatar Feb 28 '23 11:02 MikaelSlevinsky