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Exchangable NFFT backends #17

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485faec
Move NFFTOp to trigger on AbstractNFFTs instead
nHackel Sep 1, 2025
5157276
Remove fixed precompute plan keyword argument and instead pass in giv…
nHackel Sep 1, 2025
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5 changes: 3 additions & 2 deletions Project.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -24,14 +24,15 @@ julia = "1.9"
GPUArrays = "11"
KernelAbstractions = "0.9"
JLArrays = "0.2"
NFFT = "0.13"
AbstractNFFTs = "0.9"
LinearOperators = "2"
RadonKA = "0.6"
Wavelets = "0.9, 0.10"
Reexport = "1.0"
FFTW = "1.0"

[weakdeps]
AbstractNFFTs = "7f219486-4aa7-41d6-80a7-e08ef20ceed7"
GPUArrays = "0c68f7d7-f131-5f86-a1c3-88cf8149b2d7"
KernelAbstractions = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
NFFT = "efe261a4-0d2b-5849-be55-fc731d526b0d"
Expand All @@ -43,7 +44,7 @@ RadonKA = "86de8297-835b-47df-b249-c04e8db91db5"
test = ["Test", "FFTW", "Wavelets", "NFFT", "JLArrays", "RadonKA"]

[extensions]
LinearOperatorNFFTExt = ["NFFT", "FFTW"]
LinearOperatorNFFTExt = ["AbstractNFFTs", "FFTW"]
LinearOperatorFFTWExt = "FFTW"
LinearOperatorWaveletExt = "Wavelets"
LinearOperatorGPUArraysExt = "GPUArrays"
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2 changes: 1 addition & 1 deletion ext/LinearOperatorNFFTExt/LinearOperatorNFFTExt.jl
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@@ -1,6 +1,6 @@
module LinearOperatorNFFTExt

using LinearOperatorCollection, NFFT, NFFT.AbstractNFFTs, FFTW, FFTW.AbstractFFTs
using LinearOperatorCollection, AbstractNFFTs, FFTW, FFTW.AbstractFFTs

include("NFFTOp.jl")

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6 changes: 3 additions & 3 deletions ext/LinearOperatorNFFTExt/NFFTOp.jl
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Expand Up @@ -8,7 +8,7 @@ generates a `NFFTOpImpl` which evaluates the MRI Fourier signal encoding operato
* `shape::NTuple{D,Int64}` - size of image to encode/reconstruct
* `tr` - Either a `Trajectory` object, or a `ND x Nsamples` matrix for an ND-dimenensional (e.g. 2D or 3D) NFFT with `Nsamples` k-space samples
* (`nodes=nothing`) - Array containg the trajectory nodes (redundant)
* (`kargs`) - additional keyword arguments
* (`kargs`) - additional keyword arguments for the NFFT plan
"""
function LinearOperatorCollection.NFFTOp(::Type{T};
shape::Tuple, nodes::AbstractMatrix{U}, toeplitz=false, oversamplingFactor=1.25,
Expand Down Expand Up @@ -41,8 +41,8 @@ LinearOperators.storage_type(op::NFFTOpImpl) = typeof(op.Mv5)
function NFFTOpImpl(shape::Tuple, tr::AbstractMatrix{T}; toeplitz=false, oversamplingFactor=1.25, kernelSize=3, S = Vector{Complex{T}}, kargs...) where {T}

baseArrayType = Base.typename(S).wrapper # https://github.com/JuliaLang/julia/issues/35543
plan = plan_nfft(baseArrayType, tr, shape, m=kernelSize, σ=oversamplingFactor, precompute=NFFT.TENSOR,
fftflags=FFTW.ESTIMATE, blocking=true)
plan = plan_nfft(baseArrayType, tr, shape, m=kernelSize, σ=oversamplingFactor,
fftflags=FFTW.ESTIMATE, blocking=true, kargs...)

return NFFTOpImpl{eltype(S), S, typeof(plan)}(size(tr,2), prod(shape), false, false
, (res,x) -> produ!(res,plan,x)
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