Mercurial > repos > PredictPDPS / changeset

--- a/src/OpticalFlow.jl	Thu May 02 21:26:49 2024 +0300
+++ b/src/OpticalFlow.jl	Fri May 03 17:16:21 2024 +0300
@@ -198,15 +198,16 @@
     C = similar(y)
     cc = abs.(x-oldx)
     cm = max(flow.threshold,maximum(cc))
-    c = 1 .* (1 .- cc./ cm) .^flow.exponent
+    # c = 1 .* (1 .- cc./ cm) .^flow.exponent
+    c = 1.0 .- 0.75.*activation.(cc./cm)
     C[1,:,:] .= c
     C[2,:,:] .= c
     y .= C.*y
 end
 
-function activation(x)
-    return (1/(1 + exp(-10000(x - 0.05))))  # best for shepp logan
-    # return -abs(x-1)^1/5 + 1     # best for lighthouse and brainphantom    
+function activation(x :: Real)
+    return (1/(1 + exp(-1000(x - 0.05))))    # best for shepp logan
+    #return -abs(x-1)^1/5 + 1                  # best for lighthouse and brainphantom    
     # return x^(5) 
     # return (1/(1 + exp(-1000(x - 0.075))))  
     # return 4*(x-0.5)^3 + 0.5  
@@ -214,30 +215,24 @@
     # return -3(x-0.5)^2 + 0.75    
     # return (x-1)^51 + 1 
     # return -abs(x-1)^1/3 + 1
-    # return 16*(x-0.5)^5 + 0.5         
-end
-
-function activationD(x) 
-    # return (1/(1 + exp(-500(x - 0.1))))
-    # return 4*(x-0.5)^3 + 0.5   
-    #return (1/(1 + exp(-1000(x - 0.1))))  
-    return 1.0                  
+    # return 16*(x-0.5)^5 + 0.5
 end
 
-# Experimental predictor for dual scaling based on activation
-function pdflow!(x, Δx, y, Δy, u, flow :: ActivatedDual; threads=:none)
-    @assert(size(u)==(2,))
-    oldx = copy(x)
-    flow!(x, u; threads=(threads==:inner))
-    C = similar(y)
-    cc = abs.(x-oldx)
-    cm = max(1e-12,maximum(cc))
-    c = activation.(cc ./ cm)
-    C[1,:,:] .= c
-    C[2,:,:] .= c
-    # y .= C.*y
-    y .= y .- 0.75.*C.*y  # 0.75 for brain phantom and shepp logan
-end
+
+# # Experimental predictor for dual scaling based on activation
+# function pdflow!(x, Δx, y, Δy, u, flow :: ActivatedDual; threads=:none)
+#     @assert(size(u)==(2,))
+#     oldx = copy(x)
+#     flow!(x, u; threads=(threads==:inner))
+#     C = similar(y)
+#     cc = abs.(x-oldx)
+#     cm = max(1e-12,maximum(cc))
+#     c = 1.0 .- 0.75.*activation.(cc./cm)
+#     C[1,:,:] .= c
+#     C[2,:,:] .= c
+#     y .= C.*y 
+#     #y .= y .- C.*y  # 0.75 for brain phantom and shepp logan
+# end
 
 function pdflow!(x, Δx, y, Δy, u, :: ZeroDual; threads=:none)
     @assert(size(u)==(2,))
@@ -306,33 +301,35 @@
     C = similar(y)
     cc = abs.(x-oldx)
     cm = max(flow.threshold,maximum(cc))
-    c = 1 .* (1 .- cc./ cm) .^flow.exponent
+    # c = 1 .* (1 .- cc./ cm) .^flow.exponent   # Original dual scaling
+    # c = 1.0 .- 0.75.*activation.(cc./cm)      # Best for brain phantom
+    c = 1.0 .- 1.0.*activation.(cc./cm)         # Best for shepp logan phantom
     C[1,:,:] .= c
     C[2,:,:] .= c
     y .= C.*y
 end
 
-# Experimental predictor for dual scaling based on activation
-function petpdflow!(x, Δx, y, Δy, u, theta_known, flow :: ActivatedDual; threads=:none)
-    oldx = copy(x)
-    center_point = center(x) .+ u
-    tform = recenter(RotMatrix(theta_known[1]), center_point)
-    Δx = warp(x, tform, axes(x), fillvalue=Flat())
-    @. x = Δx
-    C = similar(y)
-    cc = abs.(x-oldx)
-    cm = max(1e-12,maximum(cc))
-    c = activation.(cc ./ cm)
-    C[1,:,:] .= c
-    C[2,:,:] .= c
-    # Δx .= activation.(sqrt.(abs.(y[1,:,:]).^2 + abs.(y[2,:,:]).^2))./0.25
-    # D = similar(y)
-    # D[1,:,:] .= Δx
-    # D[2,:,:] .= Δx
-    # y .= C.*y
-    # y .= y .- 1.0.*C.*D.*y 
-    y .= y .- 1.0.*C.*y 
-end
+# # Experimental predictor for dual scaling based on activation
+# function petpdflow!(x, Δx, y, Δy, u, theta_known, flow :: ActivatedDual; threads=:none)
+#     oldx = copy(x)
+#     center_point = center(x) .+ u
+#     tform = recenter(RotMatrix(theta_known[1]), center_point)
+#     Δx = warp(x, tform, axes(x), fillvalue=Flat())
+#     @. x = Δx
+#     C = similar(y)
+#     cc = abs.(x-oldx)
+#     cm = max(1e-12,maximum(cc))
+#     c = activation.(cc ./ cm)
+#     C[1,:,:] .= c
+#     C[2,:,:] .= c
+#     # Δx .= activation.(sqrt.(abs.(y[1,:,:]).^2 + abs.(y[2,:,:]).^2))./0.25
+#     # D = similar(y)
+#     # D[1,:,:] .= Δx
+#     # D[2,:,:] .= Δx
+#     # y .= C.*y
+#     # y .= y .- 1.0.*C.*D.*y 
+#     #y .= y .- 1.0.*C.*y 
+# end
 
 # Method for rotation prediction (exploiting property of inverse rotation)
 function petpdflow!(x, Δx, y, Δy, u, theta_known, flow :: Rotation; threads=:none)

--- a/src/PET/PET.jl	Thu May 02 21:26:49 2024 +0300
+++ b/src/PET/PET.jl	Fri May 03 17:16:21 2024 +0300
@@ -122,8 +122,8 @@
                p_known₀_pets ⬿ (predictor=Rotation(),)),
     Experiment(AlgorithmNew, DisplacementConstant, shepplogan,
                p_known₀_pets ⬿ (predictor=ZeroDual(),)),
-    Experiment(AlgorithmNew, DisplacementConstant, shepplogan,
-               p_known₀_pets ⬿ (predictor=ActivatedDual(),)),
+    # Experiment(AlgorithmNew, DisplacementConstant, shepplogan,
+    #            p_known₀_pets ⬿ (predictor=ActivatedDual(),)),
 )
 
 const brainphantom_experiments_pdps_known = (
@@ -141,8 +141,8 @@
                p_known₀_petb ⬿ (predictor=Rotation(),)),
     Experiment(AlgorithmNew, DisplacementConstant, brainphantom,
                p_known₀_petb ⬿ (predictor=ZeroDual(),)),
-    Experiment(AlgorithmNew, DisplacementConstant, brainphantom,
-               p_known₀_petb ⬿ (predictor=ActivatedDual(),)),
+    # Experiment(AlgorithmNew, DisplacementConstant, brainphantom,
+    #            p_known₀_petb ⬿ (predictor=ActivatedDual(),)),
 )
 
 

--- a/src/PredictPDPS.jl	Thu May 02 21:26:49 2024 +0300
+++ b/src/PredictPDPS.jl	Fri May 03 17:16:21 2024 +0300
@@ -55,7 +55,7 @@
        batchrun_denoising,
        batchrun_predictors,
        demo_denoising1, demo_denoising2, demo_denoising3,
-       demo_denoising4, demo_denoising5, demo_denoising6, demo_denoising7, demo_denoising8,
+       demo_denoising4, demo_denoising5, demo_denoising6, demo_denoising7, #demo_denoising8,
        demo_petS1, demo_petS2, demo_petS3,
        demo_petS4, demo_petS5, demo_petS6, demo_petS7,
        demo_petB1, demo_petB2, demo_petB3,
@@ -183,8 +183,8 @@
                p_known₀_denoising ⬿ (predictor=Rotation(),)),
     Experiment(AlgorithmNew, DisplacementConstant, lighthouse,
                p_known₀_denoising ⬿ (predictor=ZeroDual(),)),
-    Experiment(AlgorithmNew, DisplacementConstant, lighthouse,
-               p_known₀_denoising ⬿ (predictor=ActivatedDual(),)),
+    # Experiment(AlgorithmNew, DisplacementConstant, lighthouse,
+    #            p_known₀_denoising ⬿ (predictor=ActivatedDual(),)),
 )
 
 const denoising_experiments_all = Iterators.flatten((
@@ -222,7 +222,7 @@
 demo_denoising5 = () -> demo(denoising_experiments_pdps_known[5]) # Proximal (old)
 demo_denoising6 = () -> demo(denoising_experiments_pdps_known[6]) # Rotation
 demo_denoising7 = () -> demo(denoising_experiments_pdps_known[7]) # Zero dual
-demo_denoising8 = () -> demo(denoising_experiments_pdps_known[8])
+
 
 function batchrun_article(kwargs...)
     run_experiments(;experiments=experiments_all,