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Make logkernel at a vector of points fast (#41)
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* Make logkernel at a vector of points fast

* Update ci.yml
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@dlfivefifty
dlfivefifty authored Apr 20, 2024
1 parent 1b55e9c commit a45cec1
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6 changes: 3 additions & 3 deletions .github/workflows/ci.yml
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Expand Up @@ -29,11 +29,11 @@ jobs:
- x64
steps:
- uses: actions/checkout@v2
- uses: julia-actions/setup-julia@v1
- uses: julia-actions/setup-julia@v2
with:
version: ${{ matrix.version }}
arch: ${{ matrix.arch }}
- uses: actions/cache@v1
- uses: actions/cache@v4
env:
cache-name: cache-artifacts
with:
Expand All @@ -46,6 +46,6 @@ jobs:
- uses: julia-actions/julia-buildpkg@v1
- uses: julia-actions/julia-runtest@v1
- uses: julia-actions/julia-processcoverage@v1
- uses: codecov/codecov-action@v1
- uses: codecov/codecov-action@v4
with:
file: lcov.info
4 changes: 2 additions & 2 deletions Project.toml
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@@ -1,7 +1,7 @@
name = "SingularIntegrals"
uuid = "d7440221-8b5e-42fc-909c-0567823f424a"
authors = ["Sheehan Olver <[email protected]>"]
version = "0.3"
version = "0.3.1"

[deps]
ArrayLayouts = "4c555306-a7a7-4459-81d9-ec55ddd5c99a"
Expand All @@ -22,7 +22,7 @@ SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
ArrayLayouts = "1.4"
BandedMatrices = "1"
ClassicalOrthogonalPolynomials = "0.12"
ContinuumArrays = "0.17"
ContinuumArrays = "0.17.2"
FastTransforms = "0.15, 0.16"
FillArrays = "1"
HypergeometricFunctions = "0.3.4"
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19 changes: 17 additions & 2 deletions src/logkernel.jl
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@@ -1,5 +1,7 @@
const ComplexLogKernelPoint{T,C,W<:Number,V,D} = BroadcastQuasiMatrix{T,typeof(log),Tuple{ConvKernel{C,W,V,D}}}
const ComplexLogKernelPoints{T,C,W<:AbstractVector{<:Number},V,D} = BroadcastQuasiMatrix{T,typeof(log),Tuple{ConvKernel{C,W,V,D}}}
const LogKernelPoint{T<:Real,C,W<:Number,V,D} = BroadcastQuasiMatrix{T,typeof(log),Tuple{BroadcastQuasiMatrix{T,typeof(abs),Tuple{ConvKernel{C,W,V,D}}}}}
const LogKernelPoints{T<:Real,C,W<:AbstractVector{<:Number},V,D} = BroadcastQuasiMatrix{T,typeof(log),Tuple{BroadcastQuasiMatrix{T,typeof(abs),Tuple{ConvKernel{C,W,V,D}}}}}
const LogKernel{T,D1,D2} = BroadcastQuasiMatrix{T,typeof(log),Tuple{BroadcastQuasiMatrix{T,typeof(abs),Tuple{ConvKernel{T,Inclusion{T,D1},T,D2}}}}}


Expand All @@ -14,12 +16,25 @@ end
logkernel(convert(AbstractQuasiArray{T}, P), z)
end

@simplify function *(L::LogKernelPoints, P::AbstractQuasiVecOrMat)
T = promote_type(eltype(L), eltype(P))
z, xc = L.args[1].args[1].args
logkernel(convert(AbstractQuasiArray{T}, P), z)
end


@simplify function *(L::ComplexLogKernelPoint, P::AbstractQuasiVecOrMat)
z, xc = L.args[1].args
T = promote_type(eltype(L), eltype(P))
complexlogkernel(convert(AbstractQuasiArray{T}, P), z)
end

@simplify function *(L::ComplexLogKernelPoints, P::AbstractQuasiVecOrMat)
z, xc = L.args[1].args
T = promote_type(eltype(L), eltype(P))
complexlogkernel(convert(AbstractQuasiArray{T}, P), z)
end

###
# LogKernel
###
Expand Down Expand Up @@ -61,11 +76,11 @@ function logkernel_demap(wT, z)
c = inv(kr.A)
LP = logkernel(P, z̃)
Σ = sum(P; dims=1)
transpose(c*transpose(LP) + c*log(c)*vec(Σ))
transpose(c*transpose(LP) .+ c*log(c)*vec(Σ))
end


logkernel_layout(::Union{MappedBasisLayouts, MappedOPLayouts}, wT, z::Number) = logkernel_demap(wT, z)
logkernel_layout(::Union{MappedBasisLayouts, MappedOPLayouts}, wT, z...) = logkernel_demap(wT, z...)
logkernel_layout(::WeightedOPLayout{MappedOPLayout}, wT, z::Real) = logkernel_demap(wT, z)


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30 changes: 29 additions & 1 deletion src/recurrence.jl
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Expand Up @@ -21,6 +21,8 @@ end
const RecurrenceVector{T, A<:AbstractVector, B<:AbstractVector, C<:AbstractVector} = RecurrenceArray{T, 1, T, A, B, C}
const RecurrenceMatrix{T, Z<:AbstractVector, A<:AbstractVector, B<:AbstractVector, C<:AbstractVector} = RecurrenceArray{T, 2, Z, A, B, C}

RecurrenceArray(z, A, B, C, data::Array{T,N}, datasize, p0, p1) where {T,N} = RecurrenceArray{T,N,typeof(z),typeof(A),typeof(B),typeof(C)}(z, A, B, C, data, datasize, p0, p1, T[])

function RecurrenceArray(z::Number, (A,B,C), data::AbstractVector{T}) where T
N = length(data)
p0, p1 = initiateforwardrecurrence(N, A, B, C, z, one(z))
Expand Down Expand Up @@ -176,4 +178,30 @@ end
###
# broadcasted
###
broadcasted(::LazyArrayStyle, op, A::Transpose{<:Any,<:RecurrenceArray}) = transpose(op.(parent(A)))
broadcasted(::LazyArrayStyle, op, A::Transpose{<:Any,<:RecurrenceArray}) = transpose(op.(parent(A)))

broadcasted(::LazyArrayStyle, ::typeof(*), c::Number, A::RecurrenceArray) = RecurrenceArray(A.z, A.A, A.B, A.C, c .* A.data, A.datasize, c .* A.p0, c .* A.p1)
function recurrence_broadcasted(op, A::RecurrenceMatrix, x::AbstractVector)
p = paddeddata(x)
n = size(p,1)
resizedata!(A, n, size(p,2))
data = copy(A.data)
data[1:n,:] .+= p
RecurrenceArray(A.z, A.A, A.B, A.C, data, A.datasize, A.p0, A.p1)
end

function recurrence_broadcasted(op, A::RecurrenceVector, x::AbstractVector)
p = paddeddata(x)
n = size(p,1)
resizedata!(A, n)
data = copy(A.data)
data[1:n] .+= p
RecurrenceArray(A.z, A.A, A.B, A.C, data, A.datasize, A.p0, A.p1)
end

for op in (:+, :-)
@eval begin
broadcasted(::LazyArrayStyle, ::typeof($op), A::RecurrenceArray, x::AbstractVector) = recurrence_broadcasted($op, A, x)
broadcasted(::LazyArrayStyle, ::typeof($op), A::RecurrenceVector, x::Vcat{<:Any,1}) = recurrence_broadcasted($op, A, x)
end
end
13 changes: 13 additions & 0 deletions test/test_logkernel.jl
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Expand Up @@ -13,6 +13,10 @@ using ClassicalOrthogonalPolynomials: affine
for z in (5, 1+2im, -1+2im, 1-2im, -3+0.0im, -3-0.0im)
@test (log.(z .- x') * P)[1:5] ≈ L.(z, 0:4)
end

for z in ([2.1,3.], [2.1+im,-3-im])
@test (log.(z .- x') * P)[:,1:5] ≈ L.(z, (0:4)')
end

for z in (-5,-1,0,0.1)
@test_throws DomainError log.(z .- x') * P
Expand Down Expand Up @@ -74,6 +78,15 @@ end
wU = Weighted(chebyshevu(1..2))
f = wU / wU \ @.(sqrt(2-x)sqrt(x-1)exp(x))
@test L*f ≈ 2.2374312398976586 # MAthematica

@testset "vector" begin
z = [3.1,4]
wU = Weighted(ChebyshevU())[affine(x, axes(ChebyshevU(),1)),:]
c = wU \ @.(sqrt(2-x)sqrt(x-1)exp(x))
x = axes(wU,1)
@test logkernel(wU, z)[:,1:1000] == (log.(abs.(z .- x')) * wU)[:,1:1000]
@test logkernel(wU, z) * c ≈ [logkernel(wU, 3.1)*c, logkernel(wU, 4)*c]
end
end

@testset "Legendre" begin
Expand Down

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Registration pull request created: JuliaRegistries/General/105293

Tip: Release Notes

Did you know you can add release notes too? Just add markdown formatted text underneath the comment after the text
"Release notes:" and it will be added to the registry PR, and if TagBot is installed it will also be added to the
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Release notes:

## Breaking changes

- blah

To add them here just re-invoke and the PR will be updated.

Tagging

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.3.1 -m "<description of version>" a45cec1ee25bff17affdadf4e1792d21d017daa5
git push origin v0.3.1

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