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Library index

BlockTensorKit.AbstractBlockTensorMap — Type
AbstractBlockTensorMap{E,S,N₁,N₂}

Abstract supertype for tensor maps that have additional block structure, i.e. they act on vector spaces that have a direct sum structure. These behave like AbstractTensorMap but have additional methods to facilitate indexing and manipulation of the block structure.

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BlockTensorKit.BlockTensorMap — Type
struct BlockTensorMap{TT<:AbstractTensorMap{E,S,N₁,N₂}} <: AbstractTensorMap{E,S,N₁,N₂}

Dense BlockTensorMap type that stores tensors of type TT in a dense array.

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BlockTensorKit.SparseBlockTensorMap — Type
struct SparseBlockTensorMap{TT<:AbstractTensorMap{E,S,N₁,N₂}} <: AbstractBlockTensorMap{E,S,N₁,N₂}

Sparse SparseBlockTensorMap type that stores tensors of type TT in a sparse dictionary.

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BlockTensorKit.SumSpace — Type
struct SumSpace{S<:ElementarySpace} <: ElementarySpace

A (lazy) direct sum of elementary vector spaces of type S.

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BlockTensorKit.:⊞ — Function
V1 ⊞ V2...
boxplus(V1::ElementarySpace, V2::ElementarySpace...)

Create a lazy representation of the direct sum of the supplied vector spaces, which retains the order. See also SumSpace.

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BlockTensorKit.droptol! — Function
droptol!(t::AbstractBlockTensorMap, tol=eps(real(scalartype(t)))^(3/4))

Remove the tensor entries of a blocktensor that have norm ≤(tol).

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BlockTensorKit.dropzeros! — Method
dropzeros!(t::AbstractBlockTensorMap)

Remove the tensor entries of a blocktensor that have norm 0. Only applicable to sparse blocktensors.

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BlockTensorKit.eachspace — Method
eachspace(V::TensorMapSumSpace) -> SumSpaceIndices

Return an object that can be used to obtain the subspaces of a BlockTensorMap.

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BlockTensorKit.sprand — Method
sprand([rng], T::Type, W::TensorMapSumSpace, p::Real)

Construct a sparse blocktensor with entries compatible with type T and space W. Each entry is nonzero with probability p.

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BlockTensorKit.spzeros — Method
spzeros(T::Type, W::TensorMapSumSpace)
spzeros(T, W, nonzero_inds)

Construct a sparse blocktensor with entries compatible with type T and space W. By default, the tensor will be empty, but nonzero entries can be specified by passing a tuple of indices nonzero_inds.

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