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:rocket: Julia package for orthogonal polynomial transforms :snowboarder:

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Removing DSP from FastTransforms reduces the load time from 3.7 s to 2.8 s for me, a 25% savings. @dlfivefifty, is there any downstream reason not to remove DSP?

I am seeing a crash due to an illegal instruction when running `jac2cheb`. FastTransforms: v0.14.0 Julia: v1.7.2 System: macOS Monterey 12.0.1 Chip: Apple M1 Pro ``` julia> using FastTransforms julia>...

```julia julia> n = 10 10 julia> pts = chebyshevpoints(Float64, n+1, Val(2)) 11-element FastTransforms.ChebyshevGrid{2, Float64}: 1.0 0.9510565162951536 0.8090169943749475 0.5877852522924731 0.30901699437494745 0.0 -0.30901699437494745 -0.5877852522924731 -0.8090169943749475 -0.9510565162951536 -1.0 julia> cos.(n.*acos.(pts)) 11-element Vector{Float64}:...

I notice that `generic_fft` allows me to `fft` BigFloat, which is great! I found however that I couldn't do the usual thing with FFTW, e.g. ```julia generic_fft(X,2) ``` for only...

Currently loading `FastTransforms` for the first time in a new session takes around 9s on my laptop. ```julia julia> @time using FastTransforms 8.874037 seconds (12.01 M allocations: 893.960 MiB, 3.89%...

I have a beginner question: I would like to compute some vector spherical harmonic transforms, specifically I want to be able to compute vorticity and divergence from eastward and northward...

```julia julia> plan_chebyshevutransform(big.([1.,2.])) ERROR: MethodError: no method matching plan_chebyshevutransform(::Vector{BigFloat}, ::Val{1}) Closest candidates are: plan_chebyshevutransform(::AbstractVector{T}, ::Val{1}) where T

Hi, I noticed that 2D nufft’s of types I-I and II-II are mentioned in the [discourse](https://discourse.julialang.org/t/nonuniform-fast-fourier-transforms/4858/2) in 2017. As I looked at the code, it seems that the interface of...

I wonder if it would be realistic and/or a goal to make the library GPU compatible. With that I mean only the crucial part of applying a pre-computed plan to...