modified to use EvalMultiPoly.jl

Project.toml

@@ -4,6 +4,7 @@ authors = ["RainerHeintzmann <[email protected]>"]
 version = "0.1.0"
 
 [deps]
+EvalMultiPoly = "c78649ec-f9ed-405e-be6d-0472f43586aa"
 FourierTools = "b18b359b-aebc-45ac-a139-9c0ccbb2871e"
 Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"

examples/Project.toml

@@ -4,6 +4,8 @@ CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 CoordinateTransformations = "150eb455-5306-5404-9cee-2592286d6298"
 DataToFunctions = "64cfdffa-4d02-49ee-ae8b-a805370874f5"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
+Enzyme = "7da242da-08ed-463a-9acd-ee780be4f1d9"
+EvalMultiPoly = "c78649ec-f9ed-405e-be6d-0472f43586aa"
 FindShift = "643ec891-bf64-479f-8088-26ff5ce1b396"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 FourierTools = "b18b359b-aebc-45ac-a139-9c0ccbb2871e"

examples/deform_testimage.jl

@@ -1,5 +1,5 @@
 ### A Pluto.jl notebook ###
-# v0.19.43
+# v0.19.42
 
 using Markdown
 using InteractiveUtils
@@ -20,11 +20,14 @@ using Pkg
 # ╔═╡ 0ae2da4f-3f75-47bb-a899-9e89c5c3f17c
 Pkg.activate(".")
 
+# ╔═╡ 4af0c13d-fc42-4fe7-97e6-2248e36b63e2
+Pkg.add("PlutoUI");
+
 # ╔═╡ a2d75cfb-feab-4130-8439-30c543618d04
 using DataToFunctions, ImageShow, TestImages, PlutoUI, Images
 
-# ╔═╡ 4af0c13d-fc42-4fe7-97e6-2248e36b63e2
-# Pkg.add("PlutoUI")
+# ╔═╡ 1c744bec-f085-4812-ab1a-40a32c2ac176
+import PlutoUI: combine
 
 # ╔═╡ 5ac1123d-5df3-4c9d-aff1-ffe91d931497
 data = Float32.(testimage("resolution_test_512"))
@@ -33,7 +36,7 @@ data = Float32.(testimage("resolution_test_512"))
 simshow(data)
 
 # ╔═╡ 2fce0208-732f-4259-a47d-7f78921bfd87
-f = get_function(data, super_sampling=1)
+f = get_interpolated_function(data, AffineMode, super_sampling=1)
 
 # ╔═╡ dd535378-3f2a-4429-914c-8b7608b99706
 @bind shift_x Slider(-100:0.02:100, default=0)
@@ -48,57 +51,68 @@ f = get_function(data, super_sampling=1)
 @bind zoom_y Slider(0.2:0.02:4, default=1)
 
 # ╔═╡ 64b64d3b-092f-4553-916d-f7db1fdfa428
-f((shift_x, shift_y), (1/zoom_x, 1/zoom_y))
+simshow(f((shift_x, shift_y, 1/zoom_x, 1/zoom_y, 0.0, 0.0, 0.0)))
 
 # ╔═╡ c3fe6b25-f4c0-4a80-9d15-9ee30136d43b
-typeof(f((shift_x, shift_y), (1/zoom_x, 1/zoom_y)))
+typeof(f((shift_x, shift_y, 1/zoom_x, 1/zoom_y, 0.0, 0.0, 0.0)))
 
 # ╔═╡ ff143f0d-b070-4220-8fa6-0b5a93a56303
 typeof(data)
 
-# ╔═╡ 1bed34fb-b29a-4042-a493-4835fdb69a9d
-g =DataToFunctions.get_function_affine(data, super_sampling=1)
+# ╔═╡ 6676ba35-3efd-49f5-9819-411ad8f8a95c
+md"""
+# Polynomial transformations
+"""
 
-# ╔═╡ c287fa80-426b-11ef-125e-5fda207e605c
-# ╠═╡ disabled = true
-#=╠═╡
-g()
-  ╠═╡ =#
-
-# ╔═╡ 87be45c0-8b2e-4d49-abd1-a274b3c1815e
-h = get_function_poly(data, 1)
+# ╔═╡ 13461a95-95ea-4bad-8673-e94e06776254
+md"""
+First order polynomial transformation which is as follows:
 
-# ╔═╡ 473d635e-d06d-4cdb-991f-22c82a06b491
-@bind c1 Slider(-20f0:0.05f0:20f0, default=0)
+``x^{\prime} = c_{1} + c_{2}{x}^{1} + c_{3}{y}^{1}``
 
-# ╔═╡ 7fb3ef17-d0a0-4919-b4d5-8e66b4a0fe60
-@bind c2 Slider(0.2f0:0.05f0:2f0, default=1)
+``y^{\prime} = c_{4} + c_{5}{x}^{1} + c_{6}{y}^{1}``
+"""
 
-# ╔═╡ 200bab4d-b444-47c6-b4d8-d5d3c450e5f9
-@bind c3 Slider(-2f0:0.05f0:2f0, default=0)
-
-# ╔═╡ f17402a6-ba63-44e9-8e22-da027b07ffc3
-@bind c4 Slider(-20f0:0.05f0:20f0, default=0)
-
-# ╔═╡ d913278e-1658-4bee-9e12-ad778e530c1b
-@bind c5 Slider(-2f0:0.05f0:2f0, default=0)
-
-# ╔═╡ cee301da-2b3e-432f-9551-0fe83bf6c8ec
-@bind c6 Slider(0.2f0:0.05f0:2f0, default=1)
+# ╔═╡ 87be45c0-8b2e-4d49-abd1-a274b3c1815e
+h = get_interpolated_function(data, PolynomialMode, 1);
+
+# ╔═╡ 68f771aa-2cde-41cd-990c-9ec7dc2146a4
+function coeffs_input(coeffs::Vector)
+
+	return combine() do Child
+
+		inputs = [
+			md""" $(name): $(
+				Child(name, Slider(-2f0:0.05f0:2f0, default=0, show_value=true))
+			)"""
+
+			for name in coeffs
+		]
+
+		md"""
+		#### Transfrorm coefficients
+		$(inputs)
+		"""
+	end
+end;
+
+# ╔═╡ 69331d73-75a3-4727-acda-e79779a2bd03
+@bind c coeffs_input(["c1", "c2", "c3", "c4", "c5", "c6"])
 
 # ╔═╡ 74228a9d-6cc2-4aaf-97da-67f32670341e
-simshow(h((c1, c2, c3, c4, c5, c6)), cmap=:turbo)#,0f0,0f0,0f0,0f0,0f0,0f0,0f0,0f0,0f0)))
+simshow(h((c.c1, c.c2, c.c3, c.c4, c.c5, c.c6)), cmap=:turbo)#,0f0,0f0,0f0,0f0,0f0,0f0,0f0,0f0,0f0)))
 
 # ╔═╡ 687a198b-9020-4959-8e27-fd0896d4b1fc
-maximum(h((c1,c2,c3,c4,c5,c6)))
+maximum(h((c.c1,c.c2,c.c3,c.c4,c.c5,c.c6)))
 
 # ╔═╡ 6584aacc-440e-457b-bf52-83f8db40c999
-h((c1,c2,c3,c4,c5,c6))
+h((c.c1,c.c2,c.c3,c.c4,c.c5,c.c6))
 
 # ╔═╡ Cell order:
 # ╠═28975586-853e-4e19-b9eb-65c41fa61a43
 # ╠═0ae2da4f-3f75-47bb-a899-9e89c5c3f17c
 # ╠═4af0c13d-fc42-4fe7-97e6-2248e36b63e2
+# ╠═1c744bec-f085-4812-ab1a-40a32c2ac176
 # ╠═a2d75cfb-feab-4130-8439-30c543618d04
 # ╠═5ac1123d-5df3-4c9d-aff1-ffe91d931497
 # ╠═b0c8d15e-1bd3-4e66-b2b9-57885636eb48
@@ -110,15 +124,11 @@ h((c1,c2,c3,c4,c5,c6))
 # ╠═64b64d3b-092f-4553-916d-f7db1fdfa428
 # ╠═c3fe6b25-f4c0-4a80-9d15-9ee30136d43b
 # ╠═ff143f0d-b070-4220-8fa6-0b5a93a56303
-# ╠═1bed34fb-b29a-4042-a493-4835fdb69a9d
-# ╠═c287fa80-426b-11ef-125e-5fda207e605c
+# ╟─6676ba35-3efd-49f5-9819-411ad8f8a95c
+# ╟─13461a95-95ea-4bad-8673-e94e06776254
 # ╠═87be45c0-8b2e-4d49-abd1-a274b3c1815e
-# ╠═473d635e-d06d-4cdb-991f-22c82a06b491
-# ╠═7fb3ef17-d0a0-4919-b4d5-8e66b4a0fe60
-# ╠═200bab4d-b444-47c6-b4d8-d5d3c450e5f9
-# ╠═f17402a6-ba63-44e9-8e22-da027b07ffc3
-# ╠═d913278e-1658-4bee-9e12-ad778e530c1b
-# ╠═cee301da-2b3e-432f-9551-0fe83bf6c8ec
-# ╠═74228a9d-6cc2-4aaf-97da-67f32670341e
+# ╟─69331d73-75a3-4727-acda-e79779a2bd03
+# ╟─68f771aa-2cde-41cd-990c-9ec7dc2146a4
+# ╟─74228a9d-6cc2-4aaf-97da-67f32670341e
 # ╠═687a198b-9020-4959-8e27-fd0896d4b1fc
 # ╠═6584aacc-440e-457b-bf52-83f8db40c999

examples/polynomial_apply.jl

@@ -29,45 +29,42 @@ function poly_test(;sz=64, dtype=Float64, n_photons=1000)
     #sample_data = p_psf ./ maximum(p_psf)
 
     # normalizing the sample data
-    sample_data = p_psf ./ maximum(p_psf)
+    sample_data = p_psf ./ maximum(p_psf) * n_photons
 
     #sample_data = make_grid();
-    f_1 = get_function_poly(Float64.(sample_data), 1); # get_function_affine(sample_data);
-    true_vals = dtype[2.1, 1.05, 0.02, 1.5, 0.05, 1.02] # dtype[2.0, 1.0, 1.01, 1.0, 0.0, 0.0, 0.0]
+    f_1 = get_interpolated_function(Float64.(sample_data), PolynomialMode, 1); # get_function_affine(sample_data);
+    true_vals = (1.6, 1.05, 0.1, 1.5, 0.01, 1.02) # dtype[2.0, 1.0, 1.01, 1.0, 0.0, 0.0, 0.0]
     # true_vals = dtype[rand(-4.0:0.001:4.0), rand(-4.0:0.001:4.0), rand(0.5:0.001:1.5),rand(0.5:0.001:1.5), 0.0, 0.0, rand(0.001:0.001:pi/2.001)]
-    dat2 = f_1(Tuple(true_vals))
 
-    p_img = n_photons .* (dat2 ./ maximum(dat2))
-    n_img = dtype.(poisson(Float64.(p_img)))
+    dat2 = f_1(true_vals)
 
-    s_data = Float64.(sample_data .* n_photons)
     #sample_data = dtype.(TestImages.shepp_logan(sz)) 
-    f = get_function_poly(Float64.(s_data), 1);
+    f = get_interpolated_function(Float64.(sample_data), PolynomialMode, 1);
 
 
 
-    loss_m(p1::AbstractVector) = sum(abs2.(f(Tuple(p1)) .- n_img))
-    st_vals = dtype[2.1, 1.01, 0.01, 1.5, 0.01, 0.9] #ones(Float64, 6)./10
+    loss_p(p1::AbstractArray) = (sum(abs2.(f(Tuple(p1)) .- dat2)))
+    st_vals = [2.1, 1.00, 0.00, 1.5, 0.00, 1.0] #ones(Float64, 6)./10
     #st_vals = Float64[1.0, 0, 0, 0, 0, 0, 1.0, 0, 0,  1.0, 0, 0, 1.0, 0, 0, 0, 0, 0]
     # Float64[9.0, 0, 0, 0, 0, 0, 1, 0, 0,  5.0, 0, 0, 1, 0, 0, 0, 0, 0]
     # @vv f(Tuple(st_vals))
     # loss_m(st_vals)
 
 
     function g!(G, x)  # (G, x)
-        G .= gradient(loss_m, x)[1]
+        G .= gradient(loss_p, x)[1]
     end
-    od = OnceDifferentiable(loss_m, g!, st_vals)
+    od = OnceDifferentiable(loss_p, g!, st_vals)
     res = optimize(
-        od, 
+        loss_p,
         st_vals,
         #Newton(),
         BFGS(; initial_stepnorm = 1e-2),#; linesearch=LineSearches.BackTracking(order=2)),
         #LBFGS(),#; linesearch=LineSearches.BackTracking(order=3)),
         #lower, upper, 
         #init_x,
         #Fminbox(inner_optimizer), 
-        Optim.Options(store_trace = true, extended_trace = true, iterations=5000, g_tol=1e-3), 
+        #Optim.Options(store_trace = true, extended_trace = true, iterations=5000, g_tol=1e-3), 
         autodiff = :forward
     )
 

src/DataToFunctions.jl

@@ -1,7 +1,6 @@
 module DataToFunctions
 
-include("utils.jl")
-include("polynomials.jl")
+include("transformation_types.jl")
 include("transformators.jl")
 
 end # module DataToFunctions