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Sep 25, 2025
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Delete truncerr #88

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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "TensorAlgebra"
uuid = "68bd88dc-f39d-4e12-b2ca-f046b68fcc6a"
authors = ["ITensor developers <[email protected]> and contributors"]
version = "0.4.1"
version = "0.4.2"

[deps]
ArrayLayouts = "4c555306-a7a7-4459-81d9-ec55ddd5c99a"
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40 changes: 1 addition & 39 deletions src/MatrixAlgebra.jl
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Expand Up @@ -17,8 +17,7 @@ export eigen,
svd,
svd!,
svdvals,
svdvals!,
truncerr
svdvals!

using LinearAlgebra: LinearAlgebra, norm
using MatrixAlgebraKit
Expand Down Expand Up @@ -143,43 +142,6 @@ end

using MatrixAlgebraKit: MatrixAlgebraKit, TruncationStrategy

struct TruncationError{T<:Real} <: TruncationStrategy
atol::T
rtol::T
p::Int
end

"""
truncerr(; atol::Real=0, rtol::Real=0, p::Int=2)

Create a truncation strategy for truncating such that the error in the factorization
is smaller than `max(atol, rtol * norm)`, where the error is determined using the `p`-norm.
"""
function truncerr(; atol::Real=0, rtol::Real=0, p::Int=2)
return TruncationError(promote(atol, rtol)..., p)
end

function MatrixAlgebraKit.findtruncated(values::AbstractVector, strategy::TruncationError)
Base.require_one_based_indexing(values)
issorted(values; rev=true) || error("Not sorted.")
# norm(values, p) ^ p
normᵖ = sum(Base.Fix2(^, strategy.p) ∘ abs, values)
ϵᵖ = max(strategy.atol ^ strategy.p, strategy.rtol ^ strategy.p * normᵖ)
if ϵᵖ ≥ normᵖ
return Base.OneTo(0)
end
truncerrᵖ = zero(real(eltype(values)))
rank = length(values)
for i in reverse(eachindex(values))
truncerrᵖ += abs(values[i]) ^ strategy.p
if truncerrᵖ ≥ ϵᵖ
rank = i
break
end
end
return Base.OneTo(rank)
end

struct TruncationDegenerate{Strategy<:TruncationStrategy,T<:Real} <: TruncationStrategy
strategy::Strategy
atol::T
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4 changes: 2 additions & 2 deletions test/Project.toml
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Expand Up @@ -16,14 +16,14 @@ TestExtras = "5ed8adda-3752-4e41-b88a-e8b09835ee3a"
[compat]
Aqua = "0.8.9"
BlockArrays = "1.6.1"
EllipsisNotation = "1.8.0"
EllipsisNotation = "1.8"
LinearAlgebra = "<0.0.1, 1"
MatrixAlgebraKit = "0.2, 0.3"
Random = "1.10"
SafeTestsets = "0.1"
StableRNGs = "1.0.2"
Suppressor = "0.2"
TensorAlgebra = "0.4.0"
TensorAlgebra = "0.4"
TensorOperations = "5.1.4"
Test = "1.10"
TestExtras = "0.3.1"
1 change: 0 additions & 1 deletion test/test_exports.jl
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Expand Up @@ -45,7 +45,6 @@ using TensorAlgebra: TensorAlgebra
:svd!,
:svdvals,
:svdvals!,
:truncerr,
]
@test issetequal(names(TensorAlgebra.MatrixAlgebra), exports)
end
154 changes: 1 addition & 153 deletions test/test_matrixalgebra.jl
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
using LinearAlgebra: Diagonal, I, diag, isposdef, norm
using MatrixAlgebraKit: qr_compact, svd_trunc, truncrank
using StableRNGs: StableRNG
using TensorAlgebra.MatrixAlgebra: MatrixAlgebra, truncdegen, truncerr
using TensorAlgebra.MatrixAlgebra: MatrixAlgebra, truncdegen
using Test: @test, @testset

elts = (Float32, Float64, ComplexF32, ComplexF64)
Expand Down Expand Up @@ -152,158 +152,6 @@ elts = (Float32, Float64, ComplexF32, ComplexF64)
@test V' * V ≈ I
@test MatrixAlgebra.svdvals(A) ≈ diag(S)
end
@testset "Truncation" begin
s = Diagonal(real(elt)[1.2, 0.9, 0.3, 0.2, 0.01])
n = length(diag(s))
rng = StableRNG(123)
u, _ = qr_compact(randn(rng, elt, n, n); positive=true)
v, _ = qr_compact(randn(rng, elt, n, n); positive=true)
a = u * s * v

# p = 2, relative = true
ũ, s̃, ṽ = svd_trunc(
a; trunc=truncerr(; rtol=norm([0.3, 0.2, 0.01]) / norm(diag(s)) + 10eps(real(elt)))
)
@test size(ũ) == (n, 2)
@test size(s̃) == (2, 2)
@test size(ṽ) == (2, n)
@test norm(ũ * s̃ * ṽ - a) ≈ norm([0.3, 0.2, 0.01])
ũ, s̃, ṽ = svd_trunc(
a; trunc=truncerr(; rtol=norm([0.3, 0.2, 0.01]) / norm(diag(s)) - 10eps(real(elt)))
)
@test size(ũ) == (n, 3)
@test size(s̃) == (3, 3)
@test size(ṽ) == (3, n)
@test norm(ũ * s̃ * ṽ - a) ≈ norm([0.2, 0.01])
ũ, s̃, ṽ = svd_trunc(a; trunc=truncerr(; rtol=0))
@test size(ũ) == (n, n)
@test size(s̃) == (n, n)
@test size(ṽ) == (n, n)
@test ũ * s̃ * ṽ ≈ a
ũ, s̃, ṽ = svd_trunc(a; trunc=truncerr(; rtol=1))
@test size(ũ) == (n, 0)
@test size(s̃) == (0, 0)
@test size(ṽ) == (0, n)
@test norm(ũ * s̃ * ṽ) ≈ 0

# p = 2, relative = false
ũ, s̃, ṽ = svd_trunc(
a; trunc=truncerr(; atol=norm([0.3, 0.2, 0.01]) + 10eps(real(elt)))
)
@test size(ũ) == (n, 2)
@test size(s̃) == (2, 2)
@test size(ṽ) == (2, n)
@test norm(ũ * s̃ * ṽ - a) ≈ norm([0.3, 0.2, 0.01])
ũ, s̃, ṽ = svd_trunc(
a; trunc=truncerr(; atol=norm([0.3, 0.2, 0.01]) - 10eps(real(elt)))
)
@test size(ũ) == (n, 3)
@test size(s̃) == (3, 3)
@test size(ṽ) == (3, n)
@test norm(ũ * s̃ * ṽ - a) ≈ norm([0.2, 0.01])
ũ, s̃, ṽ = svd_trunc(a; trunc=truncerr(; atol=0))
@test size(ũ) == (n, n)
@test size(s̃) == (n, n)
@test size(ṽ) == (n, n)
@test ũ * s̃ * ṽ ≈ a
ũ, s̃, ṽ = svd_trunc(
a; trunc=truncerr(; atol=(norm(diag(s)) * (one(real(elt)) + 10eps(real(elt)))))
)
@test size(ũ) == (n, 0)
@test size(s̃) == (0, 0)
@test size(ṽ) == (0, n)
@test norm(ũ * s̃ * ṽ) ≈ 0

# p = 1, relative = true
ũ, s̃, ṽ = svd_trunc(
a;
trunc=truncerr(;
rtol=(norm([0.3, 0.2, 0.01], 1) / norm(diag(s), 1) + 10eps(real(elt))), p=1
),
)
@test size(ũ) == (n, 2)
@test size(s̃) == (2, 2)
@test size(ṽ) == (2, n)
@test norm(ũ * s̃ * ṽ - a) ≈ norm([0.3, 0.2, 0.01])
ũ, s̃, ṽ = svd_trunc(
a;
trunc=truncerr(;
rtol=(norm([0.3, 0.2, 0.01], 1) / norm(diag(s), 1) - 10eps(real(elt))), p=1
),
)
@test size(ũ) == (n, 3)
@test size(s̃) == (3, 3)
@test size(ṽ) == (3, n)
@test norm(ũ * s̃ * ṽ - a) ≈ norm([0.2, 0.01])
ũ, s̃, ṽ = svd_trunc(a; trunc=truncerr(; rtol=0, p=1))
@test size(ũ) == (n, n)
@test size(s̃) == (n, n)
@test size(ṽ) == (n, n)
@test ũ * s̃ * ṽ ≈ a
ũ, s̃, ṽ = svd_trunc(a; trunc=truncerr(; rtol=1, p=1))
@test size(ũ) == (n, 0)
@test size(s̃) == (0, 0)
@test size(ṽ) == (0, n)
@test norm(ũ * s̃ * ṽ) ≈ 0

# p = 1, relative = false
ũ, s̃, ṽ = svd_trunc(
a; trunc=truncerr(; atol=(norm([0.3, 0.2, 0.01], 1) + 10eps(real(elt))), p=1)
)
@test size(ũ) == (n, 2)
@test size(s̃) == (2, 2)
@test size(ṽ) == (2, n)
@test norm(ũ * s̃ * ṽ - a) ≈ norm([0.3, 0.2, 0.01])
ũ, s̃, ṽ = svd_trunc(
a; trunc=truncerr(; atol=(norm([0.3, 0.2, 0.01], 1) - 10eps(real(elt))), p=1)
)
@test size(ũ) == (n, 3)
@test size(s̃) == (3, 3)
@test size(ṽ) == (3, n)
@test norm(ũ * s̃ * ṽ - a) ≈ norm([0.2, 0.01])
ũ, s̃, ṽ = svd_trunc(a; trunc=truncerr(; atol=0, p=1))
@test size(ũ) == (n, n)
@test size(s̃) == (n, n)
@test size(ṽ) == (n, n)
@test ũ * s̃ * ṽ ≈ a
ũ, s̃, ṽ = svd_trunc(
a;
trunc=truncerr(; atol=(norm(diag(s), 1) * (one(real(elt)) + 10eps(real(elt)))), p=1),
)
@test size(ũ) == (n, 0)
@test size(s̃) == (0, 0)
@test size(ṽ) == (0, n)
@test norm(ũ * s̃ * ṽ) ≈ 0

# Specifying both `atol` and `rtol`.
s = Diagonal(real(elt)[0.1, 0.01, 0.001])
n = length(diag(s))
rng = StableRNG(123)
u, _ = qr_compact(randn(rng, elt, n, n); positive=true)
v, _ = qr_compact(randn(rng, elt, n, n); positive=true)
a = u * s * v

ũ, s̃, ṽ = svd_trunc(a; trunc=truncerr(; rtol=0.002))
@test size(ũ) == (n, n)
@test size(s̃) == (n, n)
@test size(ṽ) == (n, n)
@test ũ * s̃ * ṽ ≈ a
@test ũ * s̃ * ṽ ≈ a rtol = 0.002

ũ, s̃, ṽ = svd_trunc(a; trunc=truncerr(; atol=0.002))
@test size(ũ) == (n, 2)
@test size(s̃) == (2, 2)
@test size(ṽ) == (2, n)
@test norm(ũ * s̃ * ṽ - a) ≈ norm([0.001])
@test ũ * s̃ * ṽ ≈ a atol = 0.002

ũ, s̃, ṽ = svd_trunc(a; trunc=truncerr(; atol=0.002, rtol=0.002))
@test size(ũ) == (n, 2)
@test size(s̃) == (2, 2)
@test size(ṽ) == (2, n)
@test norm(ũ * s̃ * ṽ - a) ≈ norm([0.001])
@test ũ * s̃ * ṽ ≈ a atol = 0.002 rtol = 0.002
end
@testset "Truncate degenerate" begin
s = Diagonal(real(elt)[2.0, 0.32, 0.3, 0.29, 0.01, 0.01])
n = length(diag(s))
Expand Down
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