NFFT.jl
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Julia implementation of the Non-equidistant Fast Fourier Transform (NFFT)
```julia using NFFT, NFFTTools J = 11 y = rand(J) .- 0.5 N = (16,20) p1 = plan_nfft(y, N, dims=1) f = randn(ComplexF64, N) fHat = p1 * f w=sdc(p1)...
Bumps [actions/checkout](https://github.com/actions/checkout) from 3 to 4. Release notes Sourced from actions/checkout's releases. v4.0.0 What's Changed Update default runtime to node20 by @takost in actions/checkout#1436 Support fetching without the --progress option...
Sorry for spamming :laughing: But copy of a CUDA plan does not work: ``` p = NFFT.plan_nfft(coords, (size(x,1), size(x,2))) MethodError: no method matching copy(::CuNFFT.CuNFFTPlan{Float32, 2}) Closest candidates are: copy(!Matched::LinearAlgebra.Hessenberg{
Hi! I wanted to disable threading such that I can calculate the NFFT along the first two dimensions, and loop myself along the third dim. The for loop should be...
Hi! I didn't find a `dims` kwarg to perform an NFFT along first and second dimension of a 3D array. Is there any? Especially on GPUs that's usually faster than...
I added the NNFFT in AbstractNFFTs but actually `NFFT.jl` is missing an implementation. So this is the feature request issue.
I've got a case where subsequent (adjoint) NFFTs on GPU are giving different results. I don't have a MWE yet but just to prove it:  Is...
Right now NFFT.jl gives the user no hint on how to chose the kernel size and the oversampling parameter. This was on purpose since I don't want too much "magic"...
If I understand correctly, the current approach is that user decides between cpu and gpu versions by either * CPU: `p = plan_nfft(x, N)` or (currently equivalently I think) `p...
I made several major performance improvements over the last couple of weeks and thought that it makes sense to open an issue to describe where we stand and what I...