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change factorization calling syntax; bump patch
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@Jutho
Jutho committed Sep 21, 2023
1 parent 5ae3811 commit 81a2b57
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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 = "TensorKit"
uuid = "07d1fe3e-3e46-537d-9eac-e9e13d0d4cec"
authors = ["Jutho Haegeman"]
version = "0.11.1"
version = "0.11.2"

[deps]
HalfIntegers = "f0d1745a-41c9-11e9-1dd9-e5d34d218721"
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24 changes: 24 additions & 0 deletions src/auxiliary/deprecate.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -6,4 +6,28 @@ import Base: eltype, transpose
@deprecate permute(t::AbstractTensorMap, p1::IndexTuple, p2::IndexTuple; copy::Bool=false) permute(t, (p1, p2); copy=copy)
@deprecate transpose(t::AbstractTensorMap, p1::IndexTuple, p2::IndexTuple; copy::Bool=false) transpose(t, (p1, p2); copy=copy)
@deprecate braid(t::AbstractTensorMap, p1::IndexTuple, p2::IndexTuple, levels; copy::Bool=false) braid(t, (p1, p2), levels; copy=copy)


Base.@deprecate(svd(t::AbstractTensorMap, leftind::IndexTuple, rightind::IndexTuple;
trunc::TruncationScheme=notrunc(), p::Real=2, alg::SVDAlg=SDD()),
tsvd(t, (leftind, rightind); trunc=trunc, p=p, alg=alg))
Base.@deprecate(svd(t::AbstractTensorMap;
trunc::TruncationScheme=notrunc(), p::Real=2, alg::SVDAlg=SDD()),
tsvd(t; trunc=trunc, p=p, alg=alg))
Base.@deprecate(svd!(t::AbstractTensorMap;
trunc::TruncationScheme=notrunc(), p::Real=2, alg::SVDAlg=SDD()),
tsvd(t; trunc=trunc, p=p, alg=alg))


# TODO: deprecate

tsvd(t::AbstractTensorMap, p₁::IndexTuple, p₂::IndexTuple; kwargs...) = tsvd(t, (p₁, p₂); kwargs...)
leftorth(t::AbstractTensorMap, p₁::IndexTuple, p₂::IndexTuple; kwargs...) = leftorth(t, (p₁, p₂); kwargs...)
rightorth(t::AbstractTensorMap, p₁::IndexTuple, p₂::IndexTuple; kwargs...) = rightorth(t, (p₁, p₂); kwargs...)
leftnull(t::AbstractTensorMap, p₁::IndexTuple, p₂::IndexTuple; kwargs...) = leftnull(t, (p₁, p₂); kwargs...)
rightnull(t::AbstractTensorMap, p₁::IndexTuple, p₂::IndexTuple; kwargs...) = rightnull(t, (p₁, p₂); kwargs...)
LinearAlgebra.eigen(t::AbstractTensorMap, p₁::IndexTuple, p₂::IndexTuple; kwargs...) = LinearAlgebra.eigen(t, (p₁, p₂); kwargs...)
eig(t::AbstractTensorMap, p₁::IndexTuple, p₂::IndexTuple; kwargs...) = eig(t, (p₁, p₂); kwargs...)
eigh(t::AbstractTensorMap, p₁::IndexTuple, p₂::IndexTuple; kwargs...) = eigh(t, (p₁, p₂); kwargs...)

#! format: on
69 changes: 28 additions & 41 deletions src/tensors/factorizations.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -5,18 +5,8 @@ const OFA = OrthogonalFactorizationAlgorithm
import LinearAlgebra: svd!, svd
const SVDAlg = Union{SVD,SDD}

Base.@deprecate(svd(t::AbstractTensorMap, leftind::IndexTuple, rightind::IndexTuple;
trunc::TruncationScheme=notrunc(), p::Real=2, alg::SVDAlg=SDD()),
tsvd(t, leftind, rightind; trunc=trunc, p=p, alg=alg))
Base.@deprecate(svd(t::AbstractTensorMap;
trunc::TruncationScheme=notrunc(), p::Real=2, alg::SVDAlg=SDD()),
tsvd(t; trunc=trunc, p=p, alg=alg))
Base.@deprecate(svd!(t::AbstractTensorMap;
trunc::TruncationScheme=notrunc(), p::Real=2, alg::SVDAlg=SDD()),
tsvd(t; trunc=trunc, p=p, alg=alg))

"""
tsvd(t::AbstractTensorMap, leftind::Tuple, rightind::Tuple;
tsvd(t::AbstractTensorMap, (leftind, rightind)::Index2Tuple;
trunc::TruncationScheme = notrunc(), p::Real = 2, alg::Union{SVD, SDD} = SDD())
-> U, S, V, ϵ
Expand Down Expand Up @@ -47,12 +37,12 @@ algorithm that computes the decomposition (`_gesvd` or `_gesdd`).
Orthogonality requires `InnerProductStyle(t) <: HasInnerProduct`, and `tsvd(!)`
is currently only implemented for `InnerProductStyle(t) === EuclideanProduct()`.
"""
function tsvd(t::AbstractTensorMap, p1::IndexTuple, p2::IndexTuple; kwargs...)
return tsvd!(permute(t, (p1, p2); copy=true); kwargs...)
function tsvd(t::AbstractTensorMap, (p₁, p₂)::Index2Tuple; kwargs...)
return tsvd!(permute(t, (p₁, p₂); copy=true); kwargs...)
end

"""
leftorth(t::AbstractTensorMap, leftind::Tuple, rightind::Tuple;
leftorth(t::AbstractTensorMap, (leftind, rightind)::Index2Tuple;
alg::OrthogonalFactorizationAlgorithm = QRpos()) -> Q, R
Create orthonormal basis `Q` for indices in `leftind`, and remainder `R` such that
Expand All @@ -73,12 +63,12 @@ Orthogonality requires `InnerProductStyle(t) <: HasInnerProduct`, and
`leftorth(!)` is currently only implemented for
`InnerProductStyle(t) === EuclideanProduct()`.
"""
function leftorth(t::AbstractTensorMap, p1::IndexTuple, p2::IndexTuple; kwargs...)
return leftorth!(permute(t, (p1, p2); copy=true); kwargs...)
function leftorth(t::AbstractTensorMap, (p₁, p₂)::Index2Tuple; kwargs...)
return leftorth!(permute(t, (p₁, p₂); copy=true); kwargs...)
end

"""
rightorth(t::AbstractTensorMap, leftind::Tuple, rightind::Tuple;
rightorth(t::AbstractTensorMap, (leftind, rightind)::Index2Tuple;
alg::OrthogonalFactorizationAlgorithm = LQpos()) -> L, Q
Create orthonormal basis `Q` for indices in `rightind`, and remainder `L` such that
Expand All @@ -101,12 +91,12 @@ Orthogonality requires `InnerProductStyle(t) <: HasInnerProduct`, and
`rightorth(!)` is currently only implemented for
`InnerProductStyle(t) === EuclideanProduct()`.
"""
function rightorth(t::AbstractTensorMap, p1::IndexTuple, p2::IndexTuple; kwargs...)
return rightorth!(permute(t, (p1, p2); copy=true); kwargs...)
function rightorth(t::AbstractTensorMap, (p₁, p₂)::Index2Tuple; kwargs...)
return rightorth!(permute(t, (p₁, p₂); copy=true); kwargs...)
end

"""
leftnull(t::AbstractTensor, leftind::Tuple, rightind::Tuple;
leftnull(t::AbstractTensor, (leftind, rightind)::Index2Tuple;
alg::OrthogonalFactorizationAlgorithm = QRpos()) -> N
Create orthonormal basis for the orthogonal complement of the support of the indices in
Expand All @@ -127,12 +117,12 @@ Orthogonality requires `InnerProductStyle(t) <: HasInnerProduct`, and
`leftnull(!)` is currently only implemented for
`InnerProductStyle(t) === EuclideanProduct()`.
"""
function leftnull(t::AbstractTensorMap, p1::IndexTuple, p2::IndexTuple; kwargs...)
return leftnull!(permute(t, (p1, p2); copy=true); kwargs...)
function leftnull(t::AbstractTensorMap, (p₁, p₂)::Index2Tuple; kwargs...)
return leftnull!(permute(t, (p₁, p₂); copy=true); kwargs...)
end

"""
rightnull(t::AbstractTensor, leftind::Tuple, rightind::Tuple;
rightnull(t::AbstractTensor, (leftind, rightind)::Index2Tuple;
alg::OrthogonalFactorizationAlgorithm = LQ(),
atol::Real = 0.0,
rtol::Real = eps(real(float(one(scalartype(t)))))*iszero(atol)) -> N
Expand All @@ -155,12 +145,12 @@ Orthogonality requires `InnerProductStyle(t) <: HasInnerProduct`, and
`rightnull(!)` is currently only implemented for
`InnerProductStyle(t) === EuclideanProduct()`.
"""
function rightnull(t::AbstractTensorMap, p1::IndexTuple, p2::IndexTuple; kwargs...)
return rightnull!(permute(t, (p1, p2); copy=true); kwargs...)
function rightnull(t::AbstractTensorMap, (p₁, p₂)::Index2Tuple; kwargs...)
return rightnull!(permute(t, (p₁, p₂); copy=true); kwargs...)
end

"""
eigen(t::AbstractTensor, leftind::Tuple, rightind::Tuple; kwargs...) -> D, V
eigen(t::AbstractTensor, (leftind, rightind)::Index2Tuple; kwargs...) -> D, V
Compute eigenvalue factorization of tensor `t` as linear map from `rightind` to `leftind`.
Expand All @@ -178,13 +168,13 @@ matrices. See the corresponding documentation for more information.
See also `eig` and `eigh`
"""
function LinearAlgebra.eigen(t::AbstractTensorMap, p1::IndexTuple, p2::IndexTuple;
function LinearAlgebra.eigen(t::AbstractTensorMap, (p₁, p₂)::Index2Tuple;
kwargs...)
return eigen!(permute(t, (p1, p2); copy=true); kwargs...)
return eigen!(permute(t, (p₁, p₂); copy=true); kwargs...)
end

"""
eig(t::AbstractTensor, leftind::Tuple, rightind::Tuple; kwargs...) -> D, V
eig(t::AbstractTensor, (leftind, rightind)::Index2Tuple; kwargs...) -> D, V
Compute eigenvalue factorization of tensor `t` as linear map from `rightind` to `leftind`.
The function `eig` assumes that the linear map is not hermitian and returns type stable
Expand All @@ -204,12 +194,12 @@ Accepts the same keyword arguments `scale`, `permute` and `sortby` as `eigen` of
See also `eigen` and `eigh`.
"""
function eig(t::AbstractTensorMap, p1::IndexTuple, p2::IndexTuple; kwargs...)
return eig!(permute(t, (p1, p2); copy=true); kwargs...)
function eig(t::AbstractTensorMap, (p₁, p₂)::Index2Tuple; kwargs...)
return eig!(permute(t, (p₁, p₂); copy=true); kwargs...)
end

"""
eigh(t::AbstractTensorMap, leftind::Tuple, rightind::Tuple) -> D, V
eigh(t::AbstractTensorMap, (leftind, rightind)::Index2Tuple) -> D, V
Compute eigenvalue factorization of tensor `t` as linear map from `rightind` to `leftind`.
The function `eigh` assumes that the linear map is hermitian and `D` and `V` tensors with
Expand All @@ -228,26 +218,23 @@ permute(t, (leftind, rightind)) * V = V * D
See also `eigen` and `eig`.
"""
function eigh(t::AbstractTensorMap, p1::IndexTuple, p2::IndexTuple)
return eigh!(permute(t, (p1, p2); copy=true))
function eigh(t::AbstractTensorMap, (p₁, p₂)::Index2Tuple)
return eigh!(permute(t, (p₁, p₂); copy=true))
end

"""
isposdef(t::AbstractTensor, leftind::Tuple, rightind::Tuple) -> ::Bool
isposdef(t::AbstractTensor, (leftind, rightind)::Index2Tuple) -> ::Bool
Test whether a tensor `t` is positive definite as linear map from `rightind` to `leftind`.
If `leftind` and `rightind` are not specified, the current partition of left and right
indices of `t` is used. In that case, less memory is allocated if one allows the data in
`t` to be destroyed/overwritten, by using `isposdef!(t)`. Note that the permuted tensor on
which `isposdef!` is called should have equal domain and codomain, as otherwise it is
meaningless
Accepts the same keyword arguments `scale`, `permute` and `sortby` as `eigen` of dense
matrices. See the corresponding documentation for more information.
meaningless.
"""
function LinearAlgebra.isposdef(t::AbstractTensorMap, p1::IndexTuple, p2::IndexTuple)
return isposdef!(permute(t, (p1, p2); copy=true))
function LinearAlgebra.isposdef(t::AbstractTensorMap, (p₁, p₂)::Index2Tuple)
return isposdef!(permute(t, (p₁, p₂); copy=true))
end

function tsvd(t::AbstractTensorMap; trunc::TruncationScheme=NoTruncation(),
Expand Down
14 changes: 7 additions & 7 deletions test/tensors.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -347,7 +347,7 @@ for V in spacelist
TensorKit.QL(), TensorKit.QLpos(),
TensorKit.Polar(), TensorKit.SVD(),
TensorKit.SDD())
Q, R = @constinferred leftorth(t, (3, 4, 2), (1, 5); alg=alg)
Q, R = @constinferred leftorth(t, ((3, 4, 2), (1, 5)); alg=alg)
QdQ = Q' * Q
@test QdQ ≈ one(QdQ)
@test Q * R ≈ permute(t, ((3, 4, 2), (1, 5)))
Expand All @@ -359,7 +359,7 @@ for V in spacelist
@testset "leftnull with $alg" for alg in
(TensorKit.QR(), TensorKit.SVD(),
TensorKit.SDD())
N = @constinferred leftnull(t, (3, 4, 2), (1, 5); alg=alg)
N = @constinferred leftnull(t, ((3, 4, 2), (1, 5)); alg=alg)
NdN = N' * N
@test NdN ≈ one(NdN)
@test norm(N' * permute(t, ((3, 4, 2), (1, 5)))) <
Expand All @@ -370,7 +370,7 @@ for V in spacelist
TensorKit.LQ(), TensorKit.LQpos(),
TensorKit.Polar(), TensorKit.SVD(),
TensorKit.SDD())
L, Q = @constinferred rightorth(t, (3, 4), (2, 1, 5); alg=alg)
L, Q = @constinferred rightorth(t, ((3, 4), (2, 1, 5)); alg=alg)
QQd = Q * Q'
@test QQd ≈ one(QQd)
@test L * Q ≈ permute(t, ((3, 4), (2, 1, 5)))
Expand All @@ -382,14 +382,14 @@ for V in spacelist
@testset "rightnull with $alg" for alg in
(TensorKit.LQ(), TensorKit.SVD(),
TensorKit.SDD())
M = @constinferred rightnull(t, (3, 4), (2, 1, 5); alg=alg)
M = @constinferred rightnull(t, ((3, 4), (2, 1, 5)); alg=alg)
MMd = M * M'
@test MMd ≈ one(MMd)
@test norm(permute(t, ((3, 4), (2, 1, 5))) * M') <
100 * eps(norm(t))
end
@testset "tsvd with $alg" for alg in (TensorKit.SVD(), TensorKit.SDD())
U, S, V = @constinferred tsvd(t, (3, 4, 2), (1, 5); alg=alg)
U, S, V = @constinferred tsvd(t, ((3, 4, 2), (1, 5)); alg=alg)
UdU = U' * U
@test UdU ≈ one(UdU)
VVd = V * V'
Expand Down Expand Up @@ -440,8 +440,8 @@ for V in spacelist

t = Tensor(rand, T, V1 ⊗ V1' ⊗ V2 ⊗ V2')
@testset "eig and isposdef" begin
D, V = eigen(t, (1, 3), (2, 4))
D̃, Ṽ = @constinferred eig(t, (1, 3), (2, 4))
D, V = eigen(t, ((1, 3), (2, 4)))
D̃, Ṽ = @constinferred eig(t, ((1, 3), (2, 4)))
@test D ≈ D̃
@test V ≈ Ṽ
VdV = V' * V
Expand Down

2 comments on commit 81a2b57

@Jutho
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@Jutho Jutho commented on 81a2b57 Sep 21, 2023

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Registration pull request created: JuliaRegistries/General/91920

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 v0.11.2 -m "<description of version>" 81a2b571e6d481efb79c05b18e99760bfc1749e7
git push origin v0.11.2

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