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The thing is that I'm not sure how to add this variables $\tau_1, \tau_2$ through the block structure that comes in approx fun. If there was not any dummy variables, I was writing the system as
Another issue, is that there is a missmatch on how many coefficients I can enforce each of the equations, and not sure how to resolve that either using the notation of the library
I think ClassicalOrthogonalPolynomials.jl might be a better package for finite-dimensional truncations. I've added an example implementing your operator:
Thank you! Yeah the optimal for each equation is different (which makes it quite annoying tbh), $u,v$ need to be discretized in $N+4$ modes and $q$ in $N+1$ modes, and each equation is discretized in a different number of modes as well, as
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dlfivefifty commentedon Dec 9, 2025
I think ClassicalOrthogonalPolynomials.jl might be a better package for finite-dimensional truncations. I've added an example implementing your operator:
https://github.com/JuliaApproximation/ClassicalOrthogonalPolynomials.jl/blob/dl/taumethod/examples/taumethod.jl
Though probably the truncartion sizes need to be modified as this doesn't result in a square discretization
Veenty commentedon Dec 11, 2025
Thank you! Yeah the optimal for each equation is different (which makes it quite annoying tbh),$u,v$ need to be discretized in $N+4$ modes and $q$ in $N+1$ modes, and each equation is discretized in a different number of modes as well, as
dlfivefifty commentedon Dec 11, 2025
Ok hopefully it's clear how to modify the code for that situation but let me know if not