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Add code for Fraunhofer optimization
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| ### A Pluto.jl notebook ### | ||
| # v0.19.41 | ||
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| using Markdown | ||
| using InteractiveUtils | ||
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| # This Pluto notebook uses @bind for interactivity. When running this notebook outside of Pluto, the following 'mock version' of @bind gives bound variables a default value (instead of an error). | ||
| macro bind(def, element) | ||
| quote | ||
| local iv = try Base.loaded_modules[Base.PkgId(Base.UUID("6e696c72-6542-2067-7265-42206c756150"), "AbstractPlutoDingetjes")].Bonds.initial_value catch; b -> missing; end | ||
| local el = $(esc(element)) | ||
| global $(esc(def)) = Core.applicable(Base.get, el) ? Base.get(el) : iv(el) | ||
| el | ||
| end | ||
| end | ||
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| # ╔═╡ d551f366-0213-11ef-176b-7fcf5b47315e | ||
| begin | ||
| using Pkg | ||
| Pkg.activate(".") | ||
| Pkg.instantiate() | ||
| using Revise | ||
| end | ||
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| # ╔═╡ 9e6d909f-06de-46e7-929a-61bfd67bea26 | ||
| using Zygote, WaveOpticsPropagation, FFTW, ImageShow, FiniteDifferences, CUDA, Optim, IndexFunArrays, FourierTools, TestImages | ||
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| # ╔═╡ ef79854f-0ae9-41aa-8f92-aae8d7023d71 | ||
| using Plots | ||
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| # ╔═╡ f9a13d72-f904-467c-8346-a9ef272693ff | ||
| using PlutoUI | ||
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| # ╔═╡ 20c5faa9-5694-42fd-b1bb-0c5093f6c93c | ||
| begin | ||
| # use CUDA if functional | ||
| use_CUDA = Ref(true && CUDA.functional()) | ||
| var"@mytime" = use_CUDA[] ? CUDA.var"@time" : var"@time" | ||
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| togoc(x) = use_CUDA[] ? CuArray(x) : x | ||
| end | ||
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| # ╔═╡ b8cf117e-d084-4d42-8022-03fd6ac4c417 | ||
| TableOfContents() | ||
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| # ╔═╡ 94ea2891-db37-477e-b535-1a6d402d4af2 | ||
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| # ╔═╡ a971769f-1215-4422-a209-fad710be16dd | ||
| sz = (1024, 1024) | ||
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| # ╔═╡ bdf3b801-28e0-41cf-9dc4-92fe8fdaca0e | ||
| beam = togoc(0im .+ gaussian(Float32, sz, sigma=100)) .* togoc(cispi.(conv((normal(Float32, (sz), sigma=5)), 3 .* rand(Float32, (sz))))); | ||
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| # ╔═╡ 36b798c9-feee-43b7-b9ec-4f0558a44d2c | ||
| simshow(Array(beam)) | ||
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| # ╔═╡ ad4ef631-841d-412e-a09a-4db60fa7e4a9 | ||
| z = 100f-3 | ||
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| # ╔═╡ 15011619-f26a-4858-b0a0-d5dbcad49824 | ||
| λ = 633f-9 | ||
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| # ╔═╡ 48048a82-5bbf-4f16-a7d9-15993c83f905 | ||
| L = 10f-3 | ||
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| # ╔═╡ 3f791571-2a36-4479-a853-c6ed4e8a270d | ||
| md"# Forward model" | ||
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| # ╔═╡ e52cfcd8-eec8-4a8b-b953-f1c6ef2be959 | ||
| N = 3 | ||
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| # ╔═╡ 42c00ce2-d1e4-4f84-84be-a7e4cd6551ce | ||
| begin | ||
| diffuser = cispi.(conv((normal(Float32, (sz), sigma=1)), 10 .* rand(Float32, (sz..., N)))) | ||
| diffuser_c = togoc(diffuser)# .* box(sz, (120, 150)) | ||
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| diffuser_c[:, :, 1] .= cis.(0.7 .* rr2(sz, scale=0.05)) .+ 0.1f0 .* diffuser_c[:, :, 1] | ||
| diffuser_c[:, :, 2] .= cis.(0.7 .*rr2(sz, scale=0.05)) .+ 0.1f0 .* diffuser_c[:, :, 2] | ||
| diffuser_c[:, :, 3] .= cis.(0.7 .*rr2(sz, scale=0.05)) .+ 0.1f0 .* diffuser_c[:, :, 3] | ||
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| #diffuser_c[:, :, 3] .= 1 | ||
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| # diffuser_c[:, :, 4] .*= cis.(0.3 .* xx((sz))) | ||
| # diffuser_c[:, :, 5] .*= cis.(.- 0.3 .* xx((sz))) | ||
| # diffuser_c[:, :, 6] .*= cis.(0.3 .* yy((sz))) | ||
| # diffuser_c[:, :, 7] .*= cis.(.- 0.3 .* yy((sz))) | ||
| end | ||
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| # ╔═╡ d058c9ba-82ec-4f1e-8938-eb9e1e95b713 | ||
| fraunhofer = Fraunhofer(beam .* diffuser_c, z, λ, L) | ||
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| # ╔═╡ 5d21e0bc-ea6e-4b2c-8977-d1761d1b3c65 | ||
| fraunhofer(beam .* diffuser_c) ./ 0.00195312 ≈ fftshift(fft(ifftshift(beam .* diffuser_c, (1,2)), (1,2)), (1,2)) | ||
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| # ╔═╡ df72f725-8464-46b0-a291-8503ea4e563f | ||
| size(diffuser_c) | ||
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| # ╔═╡ 90d78713-0d4d-48b2-b590-a79d4e7c12d5 | ||
| simshow(Array(diffuser_c[:, :, 1])) | ||
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| # ╔═╡ f9c4d5ca-a35a-462a-b5f4-4120012f5a1b | ||
| fwd(x) = begin | ||
| return abs2.(fraunhofer(x .* diffuser_c)) | ||
| end | ||
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| # ╔═╡ d84457d3-30ae-4711-b47f-7d2a7376a237 | ||
| md"# Optimizer" | ||
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| # ╔═╡ d219be8b-2d22-4fbe-b022-217edfeec5dc | ||
| function make_fg!(fwd, measured, loss=:L2) | ||
| L2 = let measured=measured, fwd=fwd | ||
| function L2(x) | ||
| return sum(abs2, fwd(x) .- measured) | ||
| end | ||
| end | ||
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| f = let | ||
| if loss == :L2 | ||
| L2 | ||
| end | ||
| end | ||
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| g! = let f=f | ||
| function g!(G, rec) | ||
| if !isnothing(G) | ||
| return G .= Zygote.gradient(f, rec)[1] | ||
| end | ||
| end | ||
| end | ||
| return f, g! | ||
| end | ||
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| # ╔═╡ 692e0263-8273-45a6-b3e6-c30bbeaeb649 | ||
| measurement_c = fwd(beam); | ||
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| # ╔═╡ 5c550775-a614-44dc-a81d-638448d23067 | ||
| @bind iz Slider(1:N) | ||
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| # ╔═╡ 56a03baf-3873-43d5-b8c1-8569de6026b0 | ||
| simshow(Array(measurement_c)[:, :, iz], γ=1) | ||
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| # ╔═╡ fc9bb298-5b46-4585-9ea5-4df59405d18b | ||
| fraunhofer.params.Lp | ||
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| # ╔═╡ de16936c-7774-4aab-9702-f0cf4fa660fd | ||
| md"# Optimize" | ||
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| # ╔═╡ ee5260f3-d3a4-4bf2-8b54-31723c3c516f | ||
| rec0 = togoc(ones(ComplexF32, sz)); | ||
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| # ╔═╡ d90bff7e-150d-407d-a510-385fd5a32df3 | ||
| f, g! = make_fg!(fwd, measurement_c) | ||
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| # ╔═╡ eadee3cb-1302-4f1a-a21c-17265d9a2e6b | ||
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| # ╔═╡ 05b63595-61dd-416f-8610-0f6ee1919a6f | ||
| @mytime res = Optim.optimize(f, g!, rec0, LBFGS(), | ||
| Optim.Options(iterations = 80, | ||
| store_trace=true)) | ||
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| # ╔═╡ 9ed4c43f-1ad5-43b1-bef6-40faf027207d | ||
| plot([t.iteration for t in res.trace], [t.value for t in res.trace], label="LBFGS", yaxis=:log) | ||
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| # ╔═╡ 5372b296-75d6-497d-b6c9-e2f104e76522 | ||
| [simshow(Array(res.minimizer) .* cispi(1.5), γ=1) simshow(Array(Array(beam)), γ=1)] | ||
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| # ╔═╡ 82273df3-554e-43f9-a881-63609c239648 | ||
| cat(simshow(Array(res.minimizer) .* cispi(1.5), γ=1), simshow(Array(Array(beam)), γ=1), dims=3)[:, :, 1] | ||
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| # ╔═╡ 02feb5a2-d43d-4191-b9cd-8d3946c05332 | ||
| simshow(Array(beam)) | ||
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| # ╔═╡ 980e4c15-7a04-4aad-89f1-119c33693288 | ||
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| # ╔═╡ Cell order: | ||
| # ╠═d551f366-0213-11ef-176b-7fcf5b47315e | ||
| # ╠═9e6d909f-06de-46e7-929a-61bfd67bea26 | ||
| # ╠═20c5faa9-5694-42fd-b1bb-0c5093f6c93c | ||
| # ╠═b8cf117e-d084-4d42-8022-03fd6ac4c417 | ||
| # ╠═ef79854f-0ae9-41aa-8f92-aae8d7023d71 | ||
| # ╠═f9a13d72-f904-467c-8346-a9ef272693ff | ||
| # ╠═94ea2891-db37-477e-b535-1a6d402d4af2 | ||
| # ╠═a971769f-1215-4422-a209-fad710be16dd | ||
| # ╠═bdf3b801-28e0-41cf-9dc4-92fe8fdaca0e | ||
| # ╠═36b798c9-feee-43b7-b9ec-4f0558a44d2c | ||
| # ╠═ad4ef631-841d-412e-a09a-4db60fa7e4a9 | ||
| # ╠═15011619-f26a-4858-b0a0-d5dbcad49824 | ||
| # ╠═48048a82-5bbf-4f16-a7d9-15993c83f905 | ||
| # ╠═d058c9ba-82ec-4f1e-8938-eb9e1e95b713 | ||
| # ╠═5d21e0bc-ea6e-4b2c-8977-d1761d1b3c65 | ||
| # ╟─3f791571-2a36-4479-a853-c6ed4e8a270d | ||
| # ╠═e52cfcd8-eec8-4a8b-b953-f1c6ef2be959 | ||
| # ╠═df72f725-8464-46b0-a291-8503ea4e563f | ||
| # ╠═42c00ce2-d1e4-4f84-84be-a7e4cd6551ce | ||
| # ╠═90d78713-0d4d-48b2-b590-a79d4e7c12d5 | ||
| # ╠═f9c4d5ca-a35a-462a-b5f4-4120012f5a1b | ||
| # ╠═d84457d3-30ae-4711-b47f-7d2a7376a237 | ||
| # ╠═d219be8b-2d22-4fbe-b022-217edfeec5dc | ||
| # ╠═692e0263-8273-45a6-b3e6-c30bbeaeb649 | ||
| # ╠═5c550775-a614-44dc-a81d-638448d23067 | ||
| # ╠═56a03baf-3873-43d5-b8c1-8569de6026b0 | ||
| # ╠═fc9bb298-5b46-4585-9ea5-4df59405d18b | ||
| # ╠═de16936c-7774-4aab-9702-f0cf4fa660fd | ||
| # ╠═ee5260f3-d3a4-4bf2-8b54-31723c3c516f | ||
| # ╠═d90bff7e-150d-407d-a510-385fd5a32df3 | ||
| # ╠═eadee3cb-1302-4f1a-a21c-17265d9a2e6b | ||
| # ╠═05b63595-61dd-416f-8610-0f6ee1919a6f | ||
| # ╠═9ed4c43f-1ad5-43b1-bef6-40faf027207d | ||
| # ╠═5372b296-75d6-497d-b6c9-e2f104e76522 | ||
| # ╠═82273df3-554e-43f9-a881-63609c239648 | ||
| # ╠═02feb5a2-d43d-4191-b9cd-8d3946c05332 | ||
| # ╠═980e4c15-7a04-4aad-89f1-119c33693288 |
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@JuliaRegistrator register
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Registration pull request created: JuliaRegistries/General/105527
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