Merge pull request #49 from HolyLab/teh/streamline_deps

* Streamline dependencies
* Bump minimum Julia version to 1.6
* `abs2` transition

.github/workflows/CI.yml

@@ -13,7 +13,6 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.1'
           - '1.6'
           - '1'
 #          - 'nightly'

Project.toml

@@ -1,11 +1,13 @@
 name = "RegisterQD"
 uuid = "ac24ea0c-1830-11e9-18d4-81f172323054"
-version = "0.3.1"
+version = "0.3.2"
 
 [deps]
 CenterIndexedArrays = "46a7138f-0d70-54e1-8ada-fb8296f91f24"
 CoordinateTransformations = "150eb455-5306-5404-9cee-2592286d6298"
-Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0"
+ImageCore = "a09fc81d-aa75-5fe9-8630-4744c3626534"
+ImageFiltering = "6a3955dd-da59-5b1f-98d4-e7296123deb5"
+ImageTransformations = "02fcd773-0e25-5acc-982a-7f6622650795"
 Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MappedArrays = "dbb5928d-eab1-5f90-85c2-b9b0edb7c900"
@@ -23,22 +25,23 @@ AxisArrays = "0.3, 0.4"
 CenterIndexedArrays = "0.2"
 CoordinateTransformations = "0.5, 0.6"
 Distributions = "0.20, 0.21, 0.22, 0.23, 0.24, 0.25"
+ImageCore = "0.10"
 ImageMagick = "0.7, 1"
 ImageMetadata = "0.9"
-Images = "0.20, 0.21, 0.22, 0.23, 0.24, 0.25"
-Interpolations = "0.12, 0.13, 0.14"
+ImageTransformations = "0.10"
+Interpolations = "0.12, 0.13, 0.14, 0.15"
 MappedArrays = "0.2, 0.3, 0.4"
 OffsetArrays = "0.11, 1"
 PaddedViews = "0.4, 0.5"
-QuadDIRECT = "0.0, 0.1"
+QuadDIRECT = "0.1"
 RegisterCore = "0.1, 0.2"
 RegisterDeformation = "0.3, 0.4"
 RegisterMismatch = "0.3, 0.4"
 Rotations = "0.12, 0.13, 1"
 StaticArrays = "0.11, 0.12, 1"
 TestImages = "0.5, 0.6, 1"
 Unitful = "0.17, 0.18, 1"
-julia = "1"
+julia = "1.6"
 
 [extras]
 AxisArrays = "39de3d68-74b9-583c-8d2d-e117c070f3a9"

src/RegisterQD.jl

@@ -1,14 +1,16 @@
 module RegisterQD
 
-using Images, CoordinateTransformations, QuadDIRECT
-using RegisterMismatchCommon 
-using RegisterCore 
+using ImageCore, ImageTransformations, ImageFiltering
+using CoordinateTransformations
+using QuadDIRECT
+using RegisterMismatchCommon
+using RegisterCore
 using RegisterDeformation, PaddedViews, MappedArrays
 using Rotations
 using Interpolations, CenterIndexedArrays, StaticArrays, OffsetArrays
 using LinearAlgebra
 
-using Images.ImageTransformations: CornerIterator
+using ImageTransformations: CornerIterator
 
 const VecLike = Union{AbstractVector{<:Number}, Tuple{Number, Vararg{Number}}}
 
@@ -35,7 +37,7 @@ function qd_rigid(fixed, moving, mxshift::VecLike, mxrot::Union{Number,VecLike},
 end
 
 function qd_affine(fixed, moving, mxshift, linmins, linmaxs, SD;
-                   thresh=0.5*sum(_abs2.(fixed[.!(isnan.(fixed))])),
+                   thresh=0.5*sum(abs2.(fixed[.!(isnan.(fixed))])),
                    initial_tfm=IdentityTransformation(),
                    print_interval=100,
                    kwargs...)

src/affine.jl

@@ -84,7 +84,7 @@ which is why this is "coarse" optimization.
 function qd_affine_coarse(fixed, moving, mxshift, linmins, linmaxs;
                           SD=I,
                           initial_tfm=IdentityTransformation(),
-                          thresh=0.1*sum(_abs2.(fixed[.!(isnan.(fixed))])),
+                          thresh=0.1*sum(abs2.(fixed[.!(isnan.(fixed))])),
                           minwidth=default_lin_minwidths(moving),
                           maxevals=5e4,
                           kwargs...)
@@ -117,7 +117,7 @@ As a consequence, any large translations must be supplied with reasonable accura
 function qd_affine_fine(fixed, moving, linmins, linmaxs;
                         SD=I,
                         initial_tfm=IdentityTransformation(),
-                        thresh=0.1*sum(_abs2.(fixed[.!(isnan.(fixed))])),
+                        thresh=0.1*sum(abs2.(fixed[.!(isnan.(fixed))])),
                         minwidth_mat=default_lin_minwidths(fixed)./10,
                         maxevals=5e4,
                         kwargs...)
@@ -184,7 +184,7 @@ overlap between the two images; with non-zero `thresh`, it is not permissible to
 function qd_affine(fixed, moving, mxshift, linmins, linmaxs;
                    presmoothed=false,
                    SD=I,
-                   thresh=0.5*sum(_abs2.(fixed[.!(isnan.(fixed))])),
+                   thresh=0.5*sum(abs2.(fixed[.!(isnan.(fixed))])),
                    initial_tfm=IdentityTransformation(),
                    print_interval=100,
                    kwargs...)

src/rigid.jl

@@ -86,7 +86,7 @@ end
 function qd_rigid_coarse(fixed, moving, mxshift, mxrot, minwidth_rot;
                          SD=I,
                          initial_tfm=IdentityTransformation(),
-                         thresh=0.1*sum(_abs2.(fixed[.!(isnan.(fixed))])),
+                         thresh=0.1*sum(abs2.(fixed[.!(isnan.(fixed))])),
                          kwargs...)
     #note: if a trial rotation results in image overlap < thresh for all possible shifts then QuadDIRECT throws an error
     f(x) = rigid_mm_fast(x, mxshift, fixed, moving, thresh, SD; initial_tfm=initial_tfm)
@@ -104,7 +104,7 @@ end
 function qd_rigid_fine(fixed, moving, mxrot, minwidth_rot;
                        SD=I,
                        initial_tfm=IdentityTransformation(),
-                       thresh=0.1*sum(_abs2.(fixed[.!(isnan.(fixed))])),
+                       thresh=0.1*sum(abs2.(fixed[.!(isnan.(fixed))])),
                        kwargs...)
     f(x) = rigid_mm_slow(x, fixed, moving, thresh, SD; initial_tfm=initial_tfm)
     upper_shft = fill(2.0, ndims(fixed))
@@ -179,15 +179,14 @@ function qd_rigid(fixed, moving, mxshift::VecLike, mxrot::Union{Number,VecLike};
                   presmoothed=false,
                   SD=I,
                   minwidth_rot=default_minwidth_rot(CartesianIndices(fixed), SD),
-                  thresh=0.1*sum(_abs2.(fixed[.!(isnan.(fixed))])),
+                  thresh=0.1*sum(abs2.(fixed[.!(isnan.(fixed))])),
                   initial_tfm=IdentityTransformation(),
                   print_interval=100,
                   kwargs...)
     #TODO make sure isrotation(initial_tfm.linear) returns true, else throw a warning and an option to terminate? do I still allow the main block to run?
     if initial_tfm == IdentityTransformation() || isrotation(initial_tfm.linear)
     else
-        @show "WARNING: initial_tfm is not a rigid transformation"
-        # @warn "initial_tfm is not a rigid transformation"
+        @warn "initial_tfm is not a rigid transformation"
     end
     fixed, moving = float(fixed), float(moving)
     if presmoothed

src/translations.jl

@@ -16,7 +16,7 @@ end
 function qd_translate_fine(fixed, moving;
                            initial_tfm=IdentityTransformation(),
                            minwidth=fill(0.01, ndims(fixed)),
-                           thresh=0.1*sum(_abs2.(fixed[.!(isnan.(fixed))])),
+                           thresh=0.1*sum(abs2.(fixed[.!(isnan.(fixed))])),
                            kwargs...)
     f(x) = translate_mm_slow(x, fixed, moving, thresh; initial_tfm=initial_tfm)
     upper = fill(1.0, ndims(fixed))
@@ -56,7 +56,7 @@ that can occur due to normalization when the transformed `moving` doesn't fully
 """
 function qd_translate(fixed, moving, mxshift;
                       presmoothed=false,
-                      thresh=0.1*sum(_abs2.(fixed[.!(isnan.(fixed))])),
+                      thresh=0.1*sum(abs2.(fixed[.!(isnan.(fixed))])),
                       initial_tfm=IdentityTransformation(),
                       minwidth=fill(0.01, ndims(fixed)), print_interval=100, crop=false, kwargs...)
     fixed, moving = float(fixed), float(moving)

src/util.jl

@@ -241,7 +241,3 @@ function _analyze(f, lower, upper; kwargs...)
     QuadDIRECT.analyze(f, splits, lower, upper; kwargs...)
 end
 
-# abs2 was removed in https://github.com/JuliaGraphics/ColorVectorSpace.jl/pull/131
-# this is the current recommended replacement
-# TODO: follow https://github.com/JuliaGraphics/ColorVectorSpace.jl/issues/157 and adjust for changes
-_abs2(c) = mapreducec(v->float(v)^2, +, float(zero(eltype(c))), c)

test/gpu_tests.jl

@@ -4,7 +4,9 @@ using ImageMagick
 using Distributions #what is this?
 using RegisterQD.StaticArrays
 using RegisterQD.Interpolations
-using RegisterQD.Images
+using RegisterQD.ImageCore
+using RegisterQD.ImageTransformations
+using RegisterQD.ImageFiltering
 using RegisterQD.CoordinateTransformations
 using RegisterQD.Rotations
 using RegisterQD.OffsetArrays
@@ -32,7 +34,7 @@ to_affine(tfm::Translation) = AffineMap(Matrix{Float64}(LinearAlgebra.I, length(
 to_affine(tfm::LinearMap) = AffineMap(Matrix{Float64}(LinearAlgebra.I, length(tfm.translation), length(tfm.translation)), tfm.translation)
 to_affine(tfm::AffineMap) = tfm
 
-#Helper to test that a found transform is (roughly) the inverse of the original transform. 
+#Helper to test that a found transform is (roughly) the inverse of the original transform.
 function tfmtest(tfm, tfminv)
     comp = to_affine(tfm ∘ tfminv)  #should be the identity transform
     diagtol = 0.005
@@ -47,7 +49,7 @@ end
 # cu_wrap(img::OffsetArray) = OffsetArray(CuArray(img.parent), img.offsets)
 # cu_wrap(img) = CuArray(img)
 
-#rigid tests 
+#rigid tests
 img = Float32.(testimage("cameraman"))
 SD = Matrix{Float64}(LinearAlgebra.I, 2, 2)
 tfm = Translation(@SVector([14, 17]))∘LinearMap(RotMatrix(0.3)) #no distortion for now
@@ -60,7 +62,7 @@ minwidth_rot = fill(0.002, 3)
 
 tform, mm = qd_rigid(fixed, moving, mxshift, mxrot; SD=SD, maxevals=1000, rtol=0, fvalue=0.0002);
 
-tfmtest(tfm, tform) 
+tfmtest(tfm, tform)
 @test mm<0.001
 
 
@@ -70,10 +72,10 @@ tfm3D = Translation(@SVector([15, 10, 2]))∘LinearMap(RotXYZ(0.05, 0.02, 0)) #n
 fixed, moving = fixedmov(centered(img3D), tfm3D)
 mxshift = (30, 30, 5) #make sure this isn't too small
 mxrot = (0.1, 0.1, 0.1)
-minwidth_rot = fill(0.002, 3) 
+minwidth_rot = fill(0.002, 3)
 
 tform2, mm2 = qd_rigid(fixed, moving, mxshift, mxrot; SD=SD3D, maxevals=1000, rtol=0, fvalue=0.0002);
-tfmtest(tfm3D, tform2) 
+tfmtest(tfm3D, tform2)
 @test mm2<0.01
 
 #Coppied over from qd_random

test/initial_tfm.jl

@@ -2,9 +2,12 @@ using RegisterQD
 using LinearAlgebra
 using RegisterQD.StaticArrays
 using RegisterQD.Interpolations
-using RegisterQD.Images
+using RegisterQD.ImageCore
+using RegisterQD.ImageTransformations
+using RegisterQD.ImageFiltering
 using RegisterQD.CoordinateTransformations
 using RegisterQD.Rotations
+using Test
 
 g = 0.2:0.2:1.2
 gradcube = g .* reshape(g, 1, 6) .* reshape(g, 1, 1, 6)
@@ -144,21 +147,13 @@ end
     @test !isrotation(SD*tformtest77.linear*inv(SD))
     #fails due to specific error in qd_rigid_fine
 
-    # a non rigid initial_tfm does not return a rigid transformation and prints an error message (?)
-    tformtest8, mm8 = qd_rigid(testimage6, testimage5, mxshift, mxrot2; SD=SD, print_interval=typemax(Int), initial_tfm = AffineMap(SD\tformtest5.linear*SD, SD\tformtest5.translation))
+    # a non rigid initial_tfm does not return a rigid transformation and prints a warning
+    tformtest8, mm8 = @test_logs (:warn, "initial_tfm is not a rigid transformation") begin
+        qd_rigid(testimage6, testimage5, mxshift, mxrot2; SD=SD, print_interval=typemax(Int), initial_tfm = AffineMap(SD\tformtest5.linear*SD, SD\tformtest5.translation))
+    end
     @test mm8 <1e-4
     @test isapprox(tformtest8, mytform, atol = 1)
     @test !isrotation(tformtest8.linear)
-
-    mktemp() do path, io
-        redirect_stdout(io) do
-            tformtest8, mm8 = qd_rigid(testimage6, testimage5, mxshift, mxrot2; SD=SD, print_interval=typemax(Int), initial_tfm = AffineMap(SD\tformtest5.linear*SD, SD\tformtest5.translation))
-        end
-        flush(io)
-        str = read(path, String)
-        @test !isempty(str)
-    end
-
 end
 
 @testset "Test initial_tfm improves translational alignment for affine" begin

test/qd_random.jl

@@ -1,10 +1,11 @@
 using RegisterQD
 using RegisterQD.StaticArrays
 using RegisterQD.Interpolations
-using RegisterQD.Images
+using RegisterQD.ImageCore
+using RegisterQD.ImageTransformations
+using RegisterQD.ImageFiltering
 using RegisterQD.CoordinateTransformations
 using RegisterQD.Rotations
-using RegisterQD: _abs2
 using Random
 
 #import BlockRegistration, RegisterOptimize
@@ -23,7 +24,7 @@ using Test, TestImages
     itp = interpolate(newfixed, BSpline(Linear()))
     etp = extrapolate(itp, NaN)
     fixed = etp(Base.axes(moving)...) #often the warped array has one-too-many pixels in one or more dimensions due to extrapolation
-    thresh = 0.1 * sum(_abs2.(fixed[.!(isnan.(fixed))]))
+    thresh = 0.1 * sum(abs2.(fixed[.!(isnan.(fixed))]))
     mxshift = (10,10)
 
     tfm, mm = qd_translate(fixed, moving, mxshift; maxevals=1000, thresh=thresh, rtol=0)
@@ -41,7 +42,7 @@ using Test, TestImages
     itp = interpolate(newfixed, BSpline(Linear()))
     etp = extrapolate(itp, NaN)
     fixed = etp(axes(moving)...) #often the warped array has one-too-many pixels in one or more dimensions due to extrapolation
-    thresh = 0.1 * sum(_abs2.(fixed[.!(isnan.(fixed))]))
+    thresh = 0.1 * sum(abs2.(fixed[.!(isnan.(fixed))]))
     mxshift = (5,5,5)
 
     tfm, mm = qd_translate(fixed, moving, mxshift; maxevals=1000, thresh=thresh, rtol=0)
@@ -56,7 +57,7 @@ using Test, TestImages
     itp = interpolate(newfixed, BSpline(Linear()))
     etp = extrapolate(itp, NaN)
     fixed = etp(axes(moving)...) #often the warped array has one-too-many pixels in one or more dimensions due to extrapolation
-    thresh = 0.1 * sum(_abs2.(fixed[.!(isnan.(fixed))]))
+    thresh = 0.1 * sum(abs2.(fixed[.!(isnan.(fixed))]))
     mxshift = (10,10)
     mxrot = pi/90
     minwidth_rot = [0.0002]
@@ -73,7 +74,7 @@ using Test, TestImages
     itp = interpolate(newfixed, BSpline(Linear()))
     etp = extrapolate(itp, NaN)
     fixed = etp(axes(moving)...) #often the warped array has one-too-many pixels in one or more dimensions due to extrapolation
-    thresh = 0.1 * sum(_abs2.(fixed[.!(isnan.(fixed))]))
+    thresh = 0.1 * sum(abs2.(fixed[.!(isnan.(fixed))]))
     mxshift = (5,5,5)
     mxrot = [pi/90; pi/90; pi/90]
     minwidth_rot = fill(0.0002, 3)
@@ -95,7 +96,7 @@ using Test, TestImages
     itp = interpolate(newfixed, BSpline(Linear()))
     etp = extrapolate(itp, NaN)
     fixed = etp(axes(moving)...) #often the warped array has one-too-many pixels in one or more dimensions due to extrapolation
-    thresh = 0.5 * sum(_abs2.(fixed[.!(isnan.(fixed))]))
+    thresh = 0.5 * sum(abs2.(fixed[.!(isnan.(fixed))]))
     mxshift = (5,5)
     SD = SDiagonal(@SVector(ones(ndims(fixed))))
 
@@ -118,7 +119,7 @@ using Test, TestImages
         #inds = intersect.(axes(moving), axes(newfixed))
         #fixed = newfixed[inds...]
         #moving = moving[inds...]
-        #thresh = 0.1 * (sum(_abs2.(fixed[.!(isnan.(fixed))]))+sum(_abs2.(moving[.!(isnan.(moving))])));
+        #thresh = 0.1 * (sum(abs2.(fixed[.!(isnan.(fixed))]))+sum(abs2.(moving[.!(isnan.(moving))])));
         #mxshift = (10,10,10)
         #SD = eye(ndims(fixed));
 
@@ -141,7 +142,7 @@ using Test, TestImages
         #inds = intersect.(axes(moving), axes(newfixed))
         #fixed = newfixed[inds...]
         #moving = moving[inds...]
-        #thresh = 0.5 * sum(_abs2.(fixed[.!(isnan.(fixed))]));
+        #thresh = 0.5 * sum(abs2.(fixed[.!(isnan.(fixed))]));
         #mxshift = (5,5,5)
         #SD = eye(ndims(fixed));
         #@test RegisterOptimize.aff(vcat(tfm00.translation[:], tfm00.linear[:]), fixed, SD) == tfm0

test/qd_standard.jl

@@ -4,7 +4,9 @@ using ImageMagick
 using Distributions
 using RegisterQD.StaticArrays
 using RegisterQD.Interpolations
-using RegisterQD.Images
+using RegisterQD.ImageCore
+using RegisterQD.ImageTransformations
+using RegisterQD.ImageFiltering
 using RegisterQD.CoordinateTransformations
 using RegisterQD.Rotations
 using RegisterQD.OffsetArrays