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[ITensorsNamedDimsArraysExt] Convert symmetric tensors (ITensor#1578)
* [ITensorsNamedDimsArraysExt] Convert symmetric tensors * [NDTensors] Bump to v0.3.63 * [ITensors] Bump to v0.7.5
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-11
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‎NDTensors/Project.toml

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@@ -1,7 +1,7 @@
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name = "NDTensors"
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uuid = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
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authors = ["Matthew Fishman <[email protected]>"]
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version = "0.3.62"
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version = "0.3.63"
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[deps]
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Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"

‎NDTensors/src/lib/GradedAxes/src/gradedunitrangedual.jl

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@@ -94,6 +94,21 @@ function blockedunitrange_getindices(
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return flip_blockvector(v)
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end
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# Fixes ambiguity error.
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# TODO: Write this in terms of `blockedunitrange_getindices(dual(a), indices)`.
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function blockedunitrange_getindices(
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a::GradedUnitRangeDual, indices::AbstractBlockVector{<:Block{1}}
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)
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blks = map(bs -> mortar(map(b -> a[b], bs)), blocks(indices))
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# We pass `length.(blks)` to `mortar` in order
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# to pass block labels to the axes of the output,
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# if they exist. This makes it so that
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# `only(axes(a[indices])) isa `GradedUnitRange`
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# if `a isa `GradedUnitRange`, for example.
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v = mortar(blks, labelled_length.(blks))
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return flip_blockvector(v)
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end
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function flip_blockvector(v::BlockVector)
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block_axes = flip.(axes(v))
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flipped = mortar(vec.(blocks(v)), block_axes)

‎Project.toml

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@@ -1,7 +1,7 @@
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name = "ITensors"
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uuid = "9136182c-28ba-11e9-034c-db9fb085ebd5"
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authors = ["Matthew Fishman <[email protected]>", "Miles Stoudenmire <[email protected]>"]
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version = "0.7.4"
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version = "0.7.5"
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[deps]
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Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"

‎src/lib/ITensorsNamedDimsArraysExt/examples/example_dmrg.jl

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@@ -1,6 +1,5 @@
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using Adapt: adapt
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using ITensors: MPO, dmrg, random_mps, siteinds
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using ITensors.Ops: OpSum
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using ITensorMPS: MPO, OpSum, dmrg, random_mps, siteinds
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using ITensors.ITensorsNamedDimsArraysExt: to_nameddimsarray
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function main(; n, conserve_qns=false, nsweeps=3, cutoff=1e-4, arraytype=Array)

‎src/lib/ITensorsNamedDimsArraysExt/src/to_nameddimsarray.jl

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@@ -1,5 +1,5 @@
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using ..NDTensors: data, inds
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using ITensors: ITensor
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using ..NDTensors: data, inds
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# TODO: Delete this, it is a hack to decide
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# if an Index is blocked.
@@ -34,21 +34,39 @@ function to_nameddimsarray(x::DiagTensor)
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return named(DiagonalArray(data(x), size(x)), name.(inds(x)))
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end
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using ..NDTensors: BlockSparseTensor
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using ITensors: ITensors, dir, qn
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using ..NDTensors: BlockSparseTensor, array, blockdim, datatype, nblocks, nzblocks
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using ..NDTensors.BlockSparseArrays: BlockSparseArray
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using ..NDTensors.BlockSparseArrays.BlockArrays: BlockArrays, blockedrange
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using ..NDTensors.GradedAxes: dual, gradedrange
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using ..NDTensors.TypeParameterAccessors: set_ndims
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# TODO: Delete once `BlockSparse` is removed.
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function to_nameddimsarray(x::BlockSparseTensor)
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blockinds = map(i -> [blockdim(i, b) for b in 1:nblocks(i)], inds(x))
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blockinds = map(inds(x)) do i
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r = gradedrange([qn(i, b) => blockdim(i, b) for b in 1:nblocks(i)])
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if dir(i) == ITensors.In
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return dual(r)
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end
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return r
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end
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blocktype = set_ndims(datatype(x), ndims(x))
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# TODO: Make a simpler constructor:
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# BlockSparseArray(blocktype, blockinds)
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arraystorage = BlockSparseArray{eltype(x),ndims(x),blocktype}(blockinds)
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arraystorage = BlockSparseArray{eltype(x),ndims(x),blocktype}(undef, blockinds)
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for b in nzblocks(x)
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arraystorage[BlockArrays.Block(Tuple(b)...)] = x[b]
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arraystorage[BlockArrays.Block(Int.(Tuple(b))...)] = array(x[b])
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end
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return named(arraystorage, name.(inds(x)))
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end
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using ITensors: QN
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using ..NDTensors.GradedAxes: GradedAxes
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GradedAxes.fuse_labels(l1::QN, l2::QN) = l1 + l2
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using ITensors: QN
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using ..NDTensors.SymmetrySectors: SymmetrySectors
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SymmetrySectors.dual(l::QN) = -l
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## TODO: Add this back, define `CombinerArrays` library in NDTensors!
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## using ..NDTensors: CombinerTensor, CombinerArray, storage
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## # TODO: Delete when we directly use `CombinerArray` as storage.

‎src/lib/ITensorsNamedDimsArraysExt/test/Project.toml

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@@ -0,0 +1,5 @@
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[deps]
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BlockArrays = "8e7c35d0-a365-5155-bbbb-fb81a777f24e"
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ITensors = "9136182c-28ba-11e9-034c-db9fb085ebd5"
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NDTensors = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
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Suppressor = "fd094767-a336-5f1f-9728-57cf17d0bbfb"

‎src/lib/ITensorsNamedDimsArraysExt/test/test_basics.jl

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@eval module $(gensym())
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using BlockArrays: blocklengths
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using ITensors: ITensor, Index, QN, dag, inds, plev, random_itensor
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using ITensors.ITensorsNamedDimsArraysExt: to_nameddimsarray
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using NDTensors: tensor
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using NDTensors.BlockSparseArrays: BlockSparseArray, block_nstored
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using NDTensors.GradedAxes: isdual
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using NDTensors.LabelledNumbers: label
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using NDTensors.NamedDimsArrays: NamedDimsArray, unname
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using Test: @test, @testset
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@testset "to_nameddimsarray" begin
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i = Index([QN(0) => 2, QN(1) => 3])
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a = random_itensor(i', dag(i))
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b = to_nameddimsarray(a)
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@test b isa ITensor
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@test plev(inds(b)[1]) == 1
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@test plev(inds(b)[2]) == 0
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@test inds(b)[1] == i'
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@test inds(b)[2] == dag(i)
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nb = tensor(b)
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@test nb isa NamedDimsArray{Float64}
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bb = unname(nb)
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@test bb isa BlockSparseArray{Float64}
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@test !isdual(axes(bb, 1))
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@test isdual(axes(bb, 2))
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@test blocklengths(axes(bb, 1)) == [2, 3]
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@test blocklengths(axes(bb, 2)) == [2, 3]
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@test label.(blocklengths(axes(bb, 1))) == [QN(0), QN(1)]
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@test label.(blocklengths(axes(bb, 2))) == [QN(0), QN(-1)]
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@test block_nstored(bb) == 2
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@test b' * b ≈ to_nameddimsarray(a' * a)
32+
end
33+
end

‎src/lib/ITensorsNamedDimsArraysExt/test/test_examples.jl

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@@ -1,5 +1,17 @@
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@eval module $(gensym())
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using ITensors: ITensors
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using Suppressor: @suppress
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using Test: @testset
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@testset "examples" begin
4-
include("../examples/example_readme.jl")
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@suppress include(
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joinpath(
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pkgdir(ITensors),
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"src",
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"lib",
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"ITensorsNamedDimsArraysExt",
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"examples",
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"example_readme.jl",
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),
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)
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end
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end

‎test/Project.toml

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[deps]
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BlockArrays = "8e7c35d0-a365-5155-bbbb-fb81a777f24e"
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ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
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ChainRulesTestUtils = "cdddcdb0-9152-4a09-a978-84456f9df70a"
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Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"

‎test/lib/ITensorsNamedDimsArraysExt/Project.toml

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[deps]
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ITensors = "9136182c-28ba-11e9-034c-db9fb085ebd5"
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NDTensors = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
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Suppressor = "fd094767-a336-5f1f-9728-57cf17d0bbfb"

‎test/lib/ITensorsNamedDimsArraysExt/runtests.jl

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@eval module $(gensym())
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using ITensors: ITensors
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include(
4+
joinpath(
5+
pkgdir(ITensors), "src", "lib", "ITensorsNamedDimsArraysExt", "test", "runtests.jl"
6+
),
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)
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end

‎test/runtests.jl

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@@ -19,6 +19,7 @@ ITensors.disable_threaded_blocksparse()
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"base",
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"threading",
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"lib/ContractionSequenceOptimization",
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"lib/ITensorsNamedDimsArraysExt",
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"ext/ITensorsChainRulesCoreExt",
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"ext/ITensorsVectorInterfaceExt",
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"ext/NDTensorsMappedArraysExt",

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