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special-operators.jl
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special-operators.jl
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import Base.eltypeof, Base.promote_eltypeof, LinearAlgebra.lmul!, LinearAlgebra.rmul!
export opEye, opOnes, opZeros, opDiagonal, opRestriction, opExtension, BlockDiagonalOperator
"""`opEye()`
Identity operator.
```
opI = opEye()
v = rand(5)
@assert opI * v === v
```
"""
struct opEye <: AbstractLinearOperator{Any} end
*(::opEye, x::AbstractArray{T, 1} where {T}) = x
*(x::AbstractArray{T, 1} where {T}, ::opEye) = x
*(::opEye, A::AbstractArray{T, 2} where {T}) = A
*(A::AbstractArray{T, 2} where {T}, ::opEye) = A
*(
v::Union{LinearAlgebra.Adjoint{S, V}, LinearAlgebra.Transpose{S, V}},
::LinearOperators.opEye,
) where {S, V <: AbstractVector{S}} = v
*(::opEye, T::AbstractLinearOperator) = T
*(T::AbstractLinearOperator, ::opEye) = T
*(::opEye, T::opEye) = T
function show(io::IO, op::opEye)
println(io, "Identity operator")
end
function mulOpEye!(res, v, α, β::T, n_min) where {T}
if β == zero(T)
res[1:n_min] .= @views α .* v[1:n_min]
res[(n_min + 1):end] .= 0
else
res[1:n_min] .= @views α .* v[1:n_min] .+ β .* res[1:n_min]
res[(n_min + 1):end] .= β
end
end
"""
opEye(T, n; S = Vector{T})
opEye(n)
Identity operator of order `n` and of data type `T` (defaults to `Float64`).
Change `S` to use LinearOperators on GPU.
"""
function opEye(T::DataType, n::Int; S = Vector{T})
prod! = @closure (res, v, α, β) -> mulOpEye!(res, v, α, β, n)
LinearOperator{T}(n, n, true, true, prod!, prod!, prod!, S = S)
end
opEye(n::Int) = opEye(Float64, n)
# TODO: not type stable
"""
opEye(T, nrow, ncol; S = Vector{T})
opEye(nrow, ncol)
Rectangular identity operator of size `nrow`x`ncol` and of data type `T`
(defaults to `Float64`).
Change `S` to use LinearOperators on GPU.
"""
function opEye(T::DataType, nrow::I, ncol::I; S = Vector{T}) where {I <: Integer}
if nrow == ncol
return opEye(T, nrow)
end
prod! = @closure (res, v, α, β) -> mulOpEye!(res, v, α, β, min(nrow, ncol))
return LinearOperator{T}(nrow, ncol, false, false, prod!, prod!, prod!, S = S)
end
opEye(nrow::I, ncol::I) where {I <: Integer} = opEye(Float64, nrow, ncol)
function mulOpOnes!(res, v, α, β::T) where {T}
if β == zero(T)
res .= (α * sum(v))
else
res .= (α * sum(v)) .+ β .* res
end
end
"""
opOnes(T, nrow, ncol; S = Vector{T})
opOnes(nrow, ncol)
Operator of all ones of size `nrow`-by-`ncol` of data type `T` (defaults to
`Float64`).
Change `S` to use LinearOperators on GPU.
"""
function opOnes(T::DataType, nrow::I, ncol::I; S = Vector{T}) where {I <: Integer}
prod! = @closure (res, v, α, β) -> mulOpOnes!(res, v, α, β)
LinearOperator{T}(nrow, ncol, nrow == ncol, nrow == ncol, prod!, prod!, prod!, S = S)
end
opOnes(nrow::I, ncol::I) where {I <: Integer} = opOnes(Float64, nrow, ncol)
function mulOpZeros!(res, v, α, β::T) where {T}
if β == zero(T)
res .= 0
else
res .*= β
end
end
"""
opZeros(T, nrow, ncol; S = Vector{T})
opZeros(nrow, ncol)
Zero operator of size `nrow`-by-`ncol`, of data type `T` (defaults to
`Float64`).
Change `S` to use LinearOperators on GPU.
"""
function opZeros(T::DataType, nrow::I, ncol::I; S = Vector{T}) where {I <: Integer}
prod! = @closure (res, v, α, β) -> mulOpZeros!(res, v, α, β)
LinearOperator{T}(nrow, ncol, nrow == ncol, nrow == ncol, prod!, prod!, prod!, S = S)
end
opZeros(nrow::I, ncol::I) where {I <: Integer} = opZeros(Float64, nrow, ncol)
function mulSquareOpDiagonal!(res, d, v, α, β::T) where {T}
if β == zero(T)
res .= α .* d .* v
else
res .= α .* d .* v .+ β .* res
end
end
"""
opDiagonal(d)
Diagonal operator with the vector `d` on its main diagonal.
"""
function opDiagonal(d::AbstractVector{T}) where {T}
prod! = @closure (res, v, α, β) -> mulSquareOpDiagonal!(res, d, v, α, β)
ctprod! = @closure (res, w, α, β) -> mulSquareOpDiagonal!(res, conj.(d), w, α, β)
LinearOperator{T}(length(d), length(d), true, isreal(d), prod!, prod!, ctprod!, S = typeof(d))
end
function mulOpDiagonal!(res, d, v, α, β::T, n_min) where {T}
if β == zero(T)
res[1:n_min] .= @views α .* d[1:n_min] .* v[1:n_min]
else
res[1:n_min] .= @views α .* d[1:n_min] .* v[1:n_min] .+ β .* res[1:n_min]
end
res[(n_min + 1):end] .= 0
end
"""
opDiagonal(nrow, ncol, d)
Rectangular diagonal operator of size `nrow`-by-`ncol` with the vector `d` on
its main diagonal.
"""
function opDiagonal(nrow::I, ncol::I, d::AbstractVector{T}) where {T, I <: Integer}
nrow == ncol <= length(d) && (return opDiagonal(d[1:nrow]))
n_min = min(nrow, ncol)
prod! = @closure (res, v, α, β) -> mulOpDiagonal!(res, d, v, α, β, n_min)
tprod! = @closure (res, u, α, β) -> mulOpDiagonal!(res, d, u, α, β, n_min)
ctprod! = @closure (res, w, α, β) -> mulOpDiagonal!(res, conj.(d), w, α, β, n_min)
LinearOperator{T}(nrow, ncol, false, false, prod!, tprod!, ctprod!, S = typeof(d))
end
function mulRestrict!(res, I, v, α, β)
res .= v[I]
end
function multRestrict!(res, I, u, α, β)
res .= 0
res[I] = u
end
"""
Z = opRestriction(I, ncol)
Z = opRestriction(:, ncol)
Creates a LinearOperator restricting a `ncol`-sized vector to indices `I`.
The operation `Z * v` is equivalent to `v[I]`. `I` can be `:`.
Z = opRestriction(k, ncol)
Alias for `opRestriction([k], ncol)`.
"""
function opRestriction(Idx::LinearOperatorIndexType{I}, ncol::I) where {I <: Integer}
all(1 .≤ Idx .≤ ncol) || throw(LinearOperatorException("indices should be between 1 and $ncol"))
nrow = length(Idx)
prod! = @closure (res, v, α, β) -> mulRestrict!(res, Idx, v, α, β)
tprod! = @closure (res, u, α, β) -> multRestrict!(res, Idx, u, α, β)
return LinearOperator{I}(nrow, ncol, false, false, prod!, tprod!, tprod!)
end
opRestriction(::Colon, ncol::I) where {I <: Integer} = opEye(I, ncol)
opRestriction(k::I, ncol::I) where {I <: Integer} = opRestriction([k], ncol)
"""
Z = opExtension(I, ncol)
Z = opExtension(:, ncol)
Creates a LinearOperator extending a vector of size `length(I)` to size `ncol`,
where the position of the elements on the new vector are given by the indices
`I`.
The operation `w = Z * v` is equivalent to `w = zeros(ncol); w[I] = v`.
Z = opExtension(k, ncol)
Alias for `opExtension([k], ncol)`.
"""
opExtension(Idx::LinearOperatorIndexType{I}, ncol::I) where {I <: Integer} =
opRestriction(Idx, ncol)'
opExtension(::Colon, ncol::I) where {I <: Integer} = opEye(I, ncol)
opExtension(k::I, ncol::I) where {I <: Integer} = opExtension([k], ncol)
# indexing for linear operators
import Base.getindex
function getindex(
op::AbstractLinearOperator,
rows::Union{LinearOperatorIndexType{<:Integer}, <:Integer, Colon},
cols::Union{LinearOperatorIndexType{<:Integer}, <:Integer, Colon},
)
R = opRestriction(rows, size(op, 1))
E = opExtension(cols, size(op, 2))
return R * op * E
end
eltypeof(op::AbstractLinearOperator) = eltype(op) # need this for promote_eltypeof
"""
BlockDiagonalOperator(M1, M2, ..., Mn; S = promote_type(storage_type.(M1, M2, ..., Mn)))
Creates a block-diagonal linear operator:
[ M1 ]
[ M2 ]
[ ... ]
[ Mn ]
Change `S` to use LinearOperators on GPU.
"""
function BlockDiagonalOperator(ops...; S = promote_type(storage_type.(ops)...))
nrow = ncol = 0
for op ∈ ops
m, n = size(op)
nrow += m
ncol += n
end
T = promote_eltypeof(ops...)
function prod!(y, x, α, β)
k = 0
j = 0
for op ∈ ops
m, n = size(op)
@views mul!(y[(k + 1):(k + m)], op, x[(j + 1):(j + n)], α, β)
k += m
j += n
end
end
function tprod!(y, x, α, β)
k = 0
j = 0
for op ∈ ops
m, n = size(op)
@views mul!(y[(k + 1):(k + n)], transpose(op), x[(j + 1):(j + m)], α, β)
k += n
j += m
end
end
function ctprod!(y, x, α, β)
k = 0
j = 0
for op ∈ ops
m, n = size(op)
@views mul!(y[(k + 1):(k + n)], adjoint(op), x[(j + 1):(j + m)], α, β)
k += n
j += m
end
end
symm = all((issymmetric(op) for op ∈ ops))
herm = all((ishermitian(op) for op ∈ ops))
args5 = all((has_args5(op) for op ∈ ops))
CompositeLinearOperator(T, nrow, ncol, symm, herm, prod!, tprod!, ctprod!, args5, S = S)
end