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JuliaApproximation / MultivariateOrthogonalPolynomials.jl

Supports approximating functions and solving differential equations on various higher dimensional domains such as disks and triangles
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Lowering bug? #141

Open ioannisPApapadopoulos opened 1 year ago

ioannisPApapadopoulos commented 1 year ago

@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?

dlfivefifty commented 1 year ago

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

TSGut commented 1 year ago

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?

ioannisPApapadopoulos commented 1 year ago

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

TSGut commented 1 year ago

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

dlfivefifty commented 1 year ago

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

MikaelSlevinsky commented 1 year ago

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.