Merge pull request #40 from bionanoimaging/updated_main_for_pullrequest

to update the make-cuda-work branch

Project.toml

@@ -1,7 +1,7 @@
 name = "FourierTools"
 uuid = "b18b359b-aebc-45ac-a139-9c0ccbb2871e"
 authors = ["Felix Wechsler (roflmaostc) <[email protected]>", "rheintzmann <[email protected]>"]
-version = "0.4.1"
+version = "0.4.2"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"

docs/src/czt.md

@@ -1,11 +1,14 @@
 # CZTs
 Chirp Z Transformations: Allows Fourier-transformation and at the same time zooming into the result,
 which is why it is also called the Zoomed-FFT algorithm.
-The algorithm is loosely based on a publication [Rabiner, Schafer, Rader, The Cirp z-Transform Algorithm, IEEE Trans AU 17(1969) p. 86] and a 2D Matlab Version written by N.G. Worku & H. Gross, with their consent (28. Oct. 2020) to make it openly available. It currently needs three FFTs to perform its work.
-As one of these FFTs only depends on the datasize and zoom parameters, it can be moved to a plan in future implementations.
-
+The algorithm is loosely based on a publication [Rabiner, Schafer, Rader, The Chirp z-Transform Algorithm, IEEE Trans AU 17(1969) p. 86]. It needs three FFTs to perform its work but one can be precalculated by using `plan_czt`.
+Variable zooms, transform dimensions, array center positions as well as output sizes are supported along wiht a low-level interface by specifingy `a` and `w`. 
 ```@docs
 FourierTools.czt
+FourierTools.plan_czt
 FourierTools.iczt
 FourierTools.czt_1d
+FourierTools.plan_czt_1d
+FourierTools.CZTPlan_1D
+FourierTools.CZTPlan_ND
 ```

src/convolutions.jl

@@ -74,18 +74,6 @@ function conv_psf(u::AbstractArray{T, N}, psf::AbstractArray{D, M}, dims=ntuple(
     return conv(u, ifftshift(psf, dims), dims)
 end
 
- # define custom adjoint for conv
- # so far only defined for the derivative regarding the first component
-function ChainRulesCore.rrule(::typeof(conv), u::AbstractArray{T, N}, v::AbstractArray{D, M},
-                              dims=ntuple(+, min(N, M))) where {T, D, N, M}
-    Y = conv(u, v, dims)
-    function conv_pullback(barx)
-        z = zero(eltype(u))
-        return NoTangent(), conv(barx, conj(v), dims), z, z
-    end 
-    return Y, conv_pullback
-end
-
 
 
 """
@@ -219,15 +207,6 @@ function p_conv_aux(P, P_inv, u, v_ft)
     return (P_inv.p * ((P * u) .* v_ft .* P_inv.scale))
 end
 
-function ChainRulesCore.rrule(::typeof(p_conv_aux), P, P_inv, u, v)
-    Y = p_conv_aux(P, P_inv, u, v) 
-    function conv_pullback(barx)
-        z = zero(eltype(u))
-        ∇ = p_conv_aux(P, P_inv, barx, conj(v))
-        return NoTangent(), z, z, ∇, z
-    end 
-    return Y, conv_pullback
-end
 
 """
     fft_or_rfft(T)