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fix ACA bug for vector problems #79

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Merged
maltezfaria merged 1 commit into from
Apr 10, 2025
Merged

fix ACA bug for vector problems #79

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2 changes: 1 addition & 1 deletion src/hmatrix.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -567,7 +567,7 @@ function _axpy!(a, X::AbstractSparseArray, Y::HMatrix)
a = zeros(T, m)
b = zeros(T, n)
a[i-irange.start+1] = vals[idx]
b[j-jrange.start+1] = 1
b[j-jrange.start+1] = one(T)
R.A = hcat(R.A, a)
R.B = hcat(R.B, b)
else
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65 changes: 56 additions & 9 deletions test/hmatrix_test.jl
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Expand Up @@ -37,7 +37,7 @@ include(joinpath(HMatrices.PROJECT_ROOT, "test", "testutils.jl"))
end
end

@testset "Sparse arrays" begin
@testset "Band sparse arrays" begin
m = 1000
n = 1000

Expand All @@ -49,12 +49,59 @@ end
adm = StrongAdmissibilityStd(; eta = 3)
rtol = 1e-5
comp = PartialACA(; rtol = rtol)
K = laplace_matrix(X, Y)
H = assemble_hmatrix(K, Xclt, Yclt; adm, comp, threads = false, distributed = false)
H_full = Matrix(H)
T = eltype(H)
m, n = size(H)
S = spdiagm(0 => rand(T, n))
Hnew = axpy!(true, S, deepcopy(H))
@test Matrix(Hnew) == (H_full + Matrix(S))
@testset "Scalar problem (laplace)" begin
K = laplace_matrix(X, Y)
H = assemble_hmatrix(K, Xclt, Yclt; adm, comp, threads = false, distributed = false)
H_full = Matrix(H)
T = eltype(H)
m, n = size(H)
S = spdiagm(0 => rand(T, n))
Hnew = axpy!(true, S, deepcopy(H))
@test Matrix(Hnew) == (H_full + Matrix(S))
end
@testset "Vector problem (elasticity)" begin
K = elastostatic_matrix(X, Y, 1, 1)
H = assemble_hmatrix(K, Xclt, Yclt; adm, comp, threads = false, distributed = false)
H_full = Matrix(H)
T = eltype(H)
m, n = size(H)
S = spdiagm(0 => rand(T, n))
Hnew = axpy!(true, S, deepcopy(H))
@test Matrix(Hnew) == (H_full + Matrix(S))
end
end

@testset "Precision of adding any sparse matrix to an H-matrix with regard to the matrix - vector multiplication" begin
m = 1000
n = 1000

X = rand(SVector{3,Float64}, m)
Y = X
splitter = CardinalitySplitter(; nmax = 40)
Xclt = ClusterTree(X, splitter)
Yclt = ClusterTree(Y, splitter)
adm = StrongAdmissibilityStd(; eta = 3)
rtol = 1e-5
comp = PartialACA(; rtol = rtol)
U = rand(SVector{3,Float64}, m)
@testset "Scalar problem (laplace)" begin
K = laplace_matrix(X, Y)
H = assemble_hmatrix(K, Xclt, Yclt; adm, comp, threads = false, distributed = false)
H_full = Matrix(H)
T = eltype(H)
m, n = size(H)
S = sprand(T, m, n, 0.01)
Hnew = axpy!(true, S, deepcopy(H))
@test norm(Hnew * U - (H_full + Matrix(S)) * U) < 1e-5 * norm(Hnew * U)
end
@testset "Vector problem (elasticity)" begin
K = elastostatic_matrix(X, Y, 1, 1)
H = assemble_hmatrix(K, Xclt, Yclt; adm, comp, threads = false, distributed = false)
H_full = Matrix(H)
T = eltype(H)
m, n = size(H)
S = sprand(T, m, n, 0.1)
Hnew = axpy!(true, S, deepcopy(H))
@test norm(Hnew * U - (H_full + Matrix(S)) * U) < 1e-5 * norm(Hnew * U)
end
end
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