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May 14, 2025
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Unexport gradient, hessian #623

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2abfb3f
Unexport gradient, hessian; Fix #605
mkitti May 14, 2025
7e5ac1a
Do not export gradient and hessian
mkitti May 14, 2025
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1 change: 1 addition & 0 deletions src/Interpolations.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -35,6 +35,7 @@ export
# extrapolation/extrapolation.jl
# monotonic/monotonic.jl
# scaling/scaling.jl
# hermite/cubic.jl

using LinearAlgebra, SparseArrays
using StaticArrays, WoodburyMatrices, Ratios, AxisAlgorithms, OffsetArrays
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7 changes: 2 additions & 5 deletions src/hermite/cubic.jl
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@@ -1,3 +1,5 @@
export CubicHermite

"""
CubicHermite

Expand Down Expand Up @@ -148,8 +150,3 @@ function hessian(ch::CubicHermite, x::Float64)::Float64
d2 = 2 * (3x - 2x1 - x2) / (h * h)
c1 * (y1 - y2) + d1 * dydx1 + d2 * dydx2
end


export CubicHermite
export gradient
export hessian
50 changes: 25 additions & 25 deletions test/cubic_hermite.jl
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Expand Up @@ -25,25 +25,25 @@ function cubic_hermite_test()
for i = 1:length(xs)-1
x = Float64(i)
@test ch(x) == 1.0
@test gradient(ch, x) == 0.0
@test hessian(ch, x) == 0.0
@test Interpolations.gradient(ch, x) == 0.0
@test Interpolations.hessian(ch, x) == 0.0
x = x + 0.25
@test ch(x) == 1.0
@test gradient(ch, x) == 0.0
@test hessian(ch, x) == 0.0
@test Interpolations.gradient(ch, x) == 0.0
@test Interpolations.hessian(ch, x) == 0.0
x = x + 0.25
@test ch(x) == 1.0
@test gradient(ch, x) == 0.0
@test hessian(ch, x) == 0.0
@test Interpolations.gradient(ch, x) == 0.0
@test Interpolations.hessian(ch, x) == 0.0
x = x + 0.25
@test ch(x) == 1.0
@test gradient(ch, x) == 0.0
@test hessian(ch, x) == 0.0
@test Interpolations.gradient(ch, x) == 0.0
@test Interpolations.hessian(ch, x) == 0.0
end
# Ensure that the ight endpoint query doesn't read past the end of the array:
@test ch(5.0) == 1.0
@test gradient(ch, 5.0) == 0.0
@test hessian(ch, 5.0) == 0.0
@test Interpolations.gradient(ch, 5.0) == 0.0
@test Interpolations.hessian(ch, 5.0) == 0.0

# Now linear functions:
a = 7.2
Expand All @@ -56,24 +56,24 @@ function cubic_hermite_test()
for i = 1:length(xs)-1
x = Float64(i)
@test ch(x) ≈ a * x + b
@test gradient(ch, x) ≈ a
@test abs(hessian(ch, x)) < 3e-14
@test Interpolations.gradient(ch, x) ≈ a
@test abs(Interpolations.hessian(ch, x)) < 3e-14
x = x + 0.25
@test ch(x) ≈ a * x + b
@test gradient(ch, x) ≈ a
@test abs(hessian(ch, x)) < 3e-14
@test Interpolations.gradient(ch, x) ≈ a
@test abs(Interpolations.hessian(ch, x)) < 3e-14
x = x + 0.25
@test ch(x) ≈ a * x + b
@test gradient(ch, x) ≈ a
@test abs(hessian(ch, x)) < 3e-14
@test Interpolations.gradient(ch, x) ≈ a
@test abs(Interpolations.hessian(ch, x)) < 3e-14
x = x + 0.25
@test ch(x) ≈ a * x + b
@test gradient(ch, x) ≈ a
@test abs(hessian(ch, x)) < 3e-14
@test Interpolations.gradient(ch, x) ≈ a
@test abs(Interpolations.hessian(ch, x)) < 3e-14
end
@test ch(last(xs)) ≈ a * last(xs) + b
@test gradient(ch, last(xs)) ≈ a
@test abs(hessian(ch, last(xs))) < 3e-14
@test Interpolations.gradient(ch, last(xs)) ≈ a
@test abs(Interpolations.hessian(ch, last(xs))) < 3e-14

# Now the interpolation condition:
xs = zeros(50)
Expand All @@ -92,7 +92,7 @@ function cubic_hermite_test()

for i = 1:50
@test ch(xs[i]) ≈ ys[i]
@test gradient(ch, xs[i]) ≈ dydxs[i]
@test Interpolations.gradient(ch, xs[i]) ≈ dydxs[i]
end

# Now quadratics:
Expand All @@ -107,13 +107,13 @@ function cubic_hermite_test()
for i = 1:200
x = rand() * last(xs)
@test ch(x) ≈ a * x * x + b * x + c
@test gradient(ch, x) ≈ 2 * a * x + b
@test hessian(ch, x) ≈ 2 * a
@test Interpolations.gradient(ch, x) ≈ 2 * a * x + b
@test Interpolations.hessian(ch, x) ≈ 2 * a
end
x = last(xs)
@test ch(x) ≈ a * x * x + b * x + c
@test gradient(ch, x) ≈ 2 * x * a + b
@test hessian(ch, x) ≈ 2 * a
@test Interpolations.gradient(ch, x) ≈ 2 * x * a + b
@test Interpolations.hessian(ch, x) ≈ 2 * a
# Cannot extrapolate:
@test_throws DomainError ch(x + 0.1)
@test_throws DomainError ch(xs[1] - 0.1)
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64 changes: 32 additions & 32 deletions test/gpu_support.jl
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Expand Up @@ -9,37 +9,37 @@ JLArrays.allowscalar(false)
idx = 2.0:0.17:19.0
jlidx = jl(collect(idx))
@test itp.(idx) == collect(jlitp.(idx)) == collect(jlitp.(jlidx))
@test gradient.(Ref(itp), idx) ==
collect(gradient.(Ref(jlitp), idx)) ==
collect(gradient.(Ref(jlitp), jlidx))
@test Interpolations.gradient.(Ref(itp), idx) ==
collect(Interpolations.gradient.(Ref(jlitp), idx)) ==
collect(Interpolations.gradient.(Ref(jlitp), jlidx))

sitp = scale(itp, A_x)
jlsitp = jl(sitp)
idx = 1.0:0.4:39.0
jlidx = jl(collect(idx))
@test sitp.(idx) == collect(jlsitp.(idx)) == collect(jlsitp.(jlidx))
@test gradient.(Ref(sitp), idx) ==
collect(gradient.(Ref(jlsitp), idx)) ==
collect(gradient.(Ref(jlsitp), jlidx))
@test Interpolations.gradient.(Ref(sitp), idx) ==
collect(Interpolations.gradient.(Ref(jlsitp), idx)) ==
collect(Interpolations.gradient.(Ref(jlsitp), jlidx))


esitp = extrapolate(sitp, Flat())
jlesitp = jl(esitp)
idx = -1.0:0.84:41.0
jlidx = jl(collect(idx))
@test esitp.(idx) == collect(jlesitp.(idx)) == collect(jlesitp.(jlidx))
@test gradient.(Ref(esitp), idx) ==
collect(gradient.(Ref(jlesitp), idx)) ==
collect(gradient.(Ref(jlesitp), jlidx))
@test Interpolations.gradient.(Ref(esitp), idx) ==
collect(Interpolations.gradient.(Ref(jlesitp), idx)) ==
collect(Interpolations.gradient.(Ref(jlesitp), jlidx))

esitp = extrapolate(sitp, 0.0)
jlesitp = jl(esitp)
idx = -1.0:0.84:41.0
jlidx = jl(collect(idx))
@test esitp.(idx) == collect(jlesitp.(idx)) == collect(jlesitp.(jlidx))
@test gradient.(Ref(esitp), idx) ==
collect(gradient.(Ref(jlesitp), idx)) ==
collect(gradient.(Ref(jlesitp), jlidx))
@test Interpolations.gradient.(Ref(esitp), idx) ==
collect(Interpolations.gradient.(Ref(jlesitp), idx)) ==
collect(Interpolations.gradient.(Ref(jlesitp), jlidx))
end

@testset "2d GPU Interpolation" begin
Expand All @@ -50,44 +50,44 @@ end
idx = 2.0:0.17:19.0
jlidx = jl(collect(idx))
@test itp.(idx, idx') == collect(jlitp.(idx, idx')) == collect(jlitp.(jlidx, jlidx'))
@test gradient.(Ref(itp), idx, idx') ==
collect(gradient.(Ref(jlitp), idx, idx')) ==
collect(gradient.(Ref(jlitp), jlidx, jlidx'))
@test hessian.(Ref(itp), idx, idx') ==
collect(hessian.(Ref(jlitp), idx, idx')) ==
collect(hessian.(Ref(jlitp), jlidx, jlidx'))
@test Interpolations.gradient.(Ref(itp), idx, idx') ==
collect(Interpolations.gradient.(Ref(jlitp), idx, idx')) ==
collect(Interpolations.gradient.(Ref(jlitp), jlidx, jlidx'))
@test Interpolations.hessian.(Ref(itp), idx, idx') ==
collect(Interpolations.hessian.(Ref(jlitp), idx, idx')) ==
collect(Interpolations.hessian.(Ref(jlitp), jlidx, jlidx'))

sitp = scale(itp, A_x, A_x)
jlsitp = jl(sitp)
idx = 1.0:0.4:39.0
jlidx = jl(collect(idx))
@test sitp.(idx, idx') == collect(jlsitp.(idx, idx')) == collect(jlsitp.(jlidx, jlidx'))
@test gradient.(Ref(sitp), idx, idx') ==
collect(gradient.(Ref(jlsitp), idx, idx')) ==
collect(gradient.(Ref(jlsitp), jlidx, jlidx'))
@test hessian.(Ref(sitp), idx, idx') ==
collect(hessian.(Ref(jlsitp), idx, idx')) ==
collect(hessian.(Ref(jlsitp), jlidx, jlidx'))
@test Interpolations.gradient.(Ref(sitp), idx, idx') ==
collect(Interpolations.gradient.(Ref(jlsitp), idx, idx')) ==
collect(Interpolations.gradient.(Ref(jlsitp), jlidx, jlidx'))
@test Interpolations.hessian.(Ref(sitp), idx, idx') ==
collect(Interpolations.hessian.(Ref(jlsitp), idx, idx')) ==
collect(Interpolations.hessian.(Ref(jlsitp), jlidx, jlidx'))

esitp = extrapolate(sitp, Flat())
jlesitp = jl(esitp)
idx = -1.0:0.84:41.0
jlidx = jl(collect(idx))
@test esitp.(idx, idx') == collect(jlesitp.(idx, idx')) == collect(jlesitp.(jlidx, jlidx'))
# gradient for `extrapolation` is currently broken under CUDA
@test gradient.(Ref(esitp), idx, idx') ==
collect(gradient.(Ref(jlesitp), idx, idx')) ==
collect(gradient.(Ref(jlesitp), jlidx, jlidx'))
# Interpolations.gradient for `extrapolation` is currently broken under CUDA
@test Interpolations.gradient.(Ref(esitp), idx, idx') ==
collect(Interpolations.gradient.(Ref(jlesitp), idx, idx')) ==
collect(Interpolations.gradient.(Ref(jlesitp), jlidx, jlidx'))

esitp = extrapolate(sitp, 0.0)
jlesitp = jl(esitp)
idx = -1.0:0.84:41.0
jlidx = jl(collect(idx))
@test esitp.(idx, idx') == collect(jlesitp.(idx, idx')) == collect(jlesitp.(jlidx, jlidx'))
# gradient for `extrapolation` is currently broken under CUDA
@test gradient.(Ref(esitp), idx, idx') ==
collect(gradient.(Ref(jlesitp), idx, idx')) ==
collect(gradient.(Ref(jlesitp), jlidx, jlidx'))
# Interpolations.gradient for `extrapolation` is currently broken under CUDA
@test Interpolations.gradient.(Ref(esitp), idx, idx') ==
collect(Interpolations.gradient.(Ref(jlesitp), idx, idx')) ==
collect(Interpolations.gradient.(Ref(jlesitp), jlidx, jlidx'))
end

@testset "Lanczos on gpu" begin
Expand Down
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