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factorization.jl
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factorization.jl
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## Matrix factorizations and decompositions
abstract Factorization{T}
macro assertposdef(A, info)
:(($info)==0 ? $A : throw(PosDefException($info)))
end
macro assertnonsingular(A, info)
:(($info)==0 ? $A : throw(SingularException($info)))
end
##########################
# Cholesky Factorization #
##########################
immutable Cholesky{T} <: Factorization{T}
UL::Matrix{T}
uplo::Char
end
immutable CholeskyPivoted{T} <: Factorization{T}
UL::Matrix{T}
uplo::Char
piv::Vector{BlasInt}
rank::BlasInt
tol::Real
info::BlasInt
end
function cholfact!{T<:BlasFloat}(A::StridedMatrix{T}, uplo::Symbol=:U; pivot=false, tol=0.0)
uplochar = string(uplo)[1]
if pivot
A, piv, rank, info = LAPACK.pstrf!(uplochar, A, tol)
return CholeskyPivoted{T}(A, uplochar, piv, rank, tol, info)
else
C, info = LAPACK.potrf!(uplochar, A)
return @assertposdef Cholesky(C, uplochar) info
end
end
cholfact{T<:BlasFloat}(A::StridedMatrix{T}, uplo::Symbol=:U; pivot=false, tol=0.0) = cholfact!(copy(A), uplo, pivot=pivot, tol=tol)
cholfact{T}(A::StridedMatrix{T}, uplo::Symbol=:U; pivot=false, tol=0.0) = (S = promote_type(typeof(sqrt(one(T))),Float32); S != T ? cholfact!(convert(AbstractMatrix{S},A), uplo, pivot=pivot, tol=tol) : cholfact!(copy(A), uplo, pivot=pivot, tol=tol)) # When julia Cholesky has been implemented, the promotion should be changed.
cholfact(x::Number) = @assertposdef Cholesky(fill(sqrt(x), 1, 1), :U) !(imag(x) == 0 && real(x) > 0)
chol(A::Union(Number, AbstractMatrix), uplo::Symbol) = cholfact(A, uplo)[uplo]
chol(A::Union(Number, AbstractMatrix)) = triu!(cholfact(A, :U).UL)
convert{T}(::Type{Cholesky{T}},C::Cholesky) = Cholesky(convert(AbstractMatrix{T},C.UL),C.uplo)
convert{T}(::Type{Factorization{T}}, C::Cholesky) = convert(Cholesky{T}, C)
convert{T}(::Type{CholeskyPivoted{T}},C::CholeskyPivoted) = CholeskyPivoted(convert(AbstractMatrix{T},C.UL),C.uplo,C.piv,C.rank,C.tol,C.info)
convert{T}(::Type{Factorization{T}}, C::CholeskyPivoted) = convert(CholeskyPivoted{T}, C)
function full{T<:BlasFloat}(C::Cholesky{T})
if C.uplo == 'U'
BLAS.trmm!('R', C.uplo, 'N', 'N', one(T), C.UL, tril!(C.UL'))
else
BLAS.trmm!('L', C.uplo, 'N', 'N', one(T), C.UL, triu!(C.UL'))
end
end
size(C::Union(Cholesky, CholeskyPivoted)) = size(C.UL)
size(C::Union(Cholesky, CholeskyPivoted), d::Integer) = size(C.UL,d)
function getindex(C::Cholesky, d::Symbol)
d == :U && return Triangular(triu!(symbol(C.uplo) == d ? C.UL : C.UL'),:U)
d == :L && return Triangular(tril!(symbol(C.uplo) == d ? C.UL : C.UL'),:L)
d == :UL && return Triangular(C.UL, symbol(C.uplo))
throw(KeyError(d))
end
function getindex{T<:BlasFloat}(C::CholeskyPivoted{T}, d::Symbol)
d == :U && return triu!(symbol(C.uplo) == d ? C.UL : C.UL')
d == :L && return tril!(symbol(C.uplo) == d ? C.UL : C.UL')
d == :p && return C.piv
if d == :P
n = size(C, 1)
P = zeros(T, n, n)
for i=1:n
P[C.piv[i],i] = one(T)
end
return P
end
throw(KeyError(d))
end
show(io::IO, C::Cholesky) = (println("$(typeof(C)) with factor:");show(io,C[symbol(C.uplo)]))
A_ldiv_B!{T<:BlasFloat}(C::Cholesky{T}, B::StridedVecOrMat{T}) = LAPACK.potrs!(C.uplo, C.UL, B)
A_ldiv_B!(C::Cholesky, B::StridedVecOrMat) = C.uplo=='L' ? Ac_ldiv_B!(Triangular(C.UL,C.uplo,'N'), A_ldiv_B!(Triangular(C.UL,C.uplo,'N'), B)) : A_ldiv_B!(Triangular(C.UL,C.uplo,'N'), Ac_ldiv_B!(Triangular(C.UL,C.uplo,'N'), B))
function A_ldiv_B!{T<:BlasFloat}(C::CholeskyPivoted{T}, B::StridedVector{T})
chkfullrank(C)
ipermute!(LAPACK.potrs!(C.uplo, C.UL, permute!(B, C.piv)), C.piv)
end
function A_ldiv_B!{T<:BlasFloat}(C::CholeskyPivoted{T}, B::StridedMatrix{T})
chkfullrank(C)
n = size(C, 1)
for i=1:size(B, 2)
permute!(sub(B, 1:n, i), C.piv)
end
LAPACK.potrs!(C.uplo, C.UL, B)
for i=1:size(B, 2)
ipermute!(sub(B, 1:n, i), C.piv)
end
B
end
A_ldiv_B!(C::CholeskyPivoted, B::StridedVector) = C.uplo=='L' ? Ac_ldiv_B!(Triangular(C.UL,C.uplo,'N'), A_ldiv_B!(Triangular(C.UL,C.uplo,'N'), B[C.piv]))[invperm(C.piv)] : A_ldiv_B!(Triangular(C.UL,C.uplo,'N'), Ac_ldiv_B!(Triangular(C.UL,C.uplo,'N'), B[C.piv]))[invperm(C.piv)]
A_ldiv_B!(C::CholeskyPivoted, B::StridedMatrix) = C.uplo=='L' ? Ac_ldiv_B!(Triangular(C.UL,C.uplo,'N'), A_ldiv_B!(Triangular(C.UL,C.uplo,'N'), B[C.piv,:]))[invperm(C.piv),:] : A_ldiv_B!(Triangular(C.UL,C.uplo,'N'), Ac_ldiv_B!(Triangular(C.UL,C.uplo,'N'), B[C.piv,:]))[invperm(C.piv),:]
function det{T}(C::Cholesky{T})
dd = one(T)
for i in 1:size(C.UL,1) dd *= abs2(C.UL[i,i]) end
dd
end
det{T}(C::CholeskyPivoted{T}) = C.rank<size(C.UL,1) ? real(zero(T)) : prod(abs2(diag(C.UL)))
function logdet{T}(C::Cholesky{T})
dd = zero(T)
for i in 1:size(C.UL,1) dd += log(C.UL[i,i]) end
dd + dd # instead of 2.0dd which can change the type
end
inv(C::Cholesky) = copytri!(LAPACK.potri!(C.uplo, copy(C.UL)), C.uplo, true)
function inv(C::CholeskyPivoted)
chkfullrank(C)
ipiv = invperm(C.piv)
copytri!(LAPACK.potri!(C.uplo, copy(C.UL)), C.uplo, true)[ipiv, ipiv]
end
chkfullrank(C::CholeskyPivoted) = C.rank<size(C.UL, 1) && throw(RankDeficientException(C.info))
rank(C::CholeskyPivoted) = C.rank
####################
# QR Factorization #
####################
immutable QR{T} <: Factorization{T}
factors::Matrix{T}
τ::Vector{T}
end
# Note. For QRCompactWY factorization without pivoting, the WY representation based method introduced in LAPACK 3.4
immutable QRCompactWY{S} <: Factorization{S}
factors::Matrix{S}
T::Matrix{S}
end
immutable QRPivoted{T} <: Factorization{T}
factors::Matrix{T}
τ::Vector{T}
jpvt::Vector{BlasInt}
end
qrfact!{T<:BlasFloat}(A::StridedMatrix{T}; pivot=false) = pivot ? QRPivoted{T}(LAPACK.geqp3!(A)...) : QRCompactWY(LAPACK.geqrt!(A, min(minimum(size(A)), 36))...)
function qrfact!{T}(A::AbstractMatrix{T}; pivot=false)
pivot && warn("pivoting only implemented for Float32, Float64, Complex64 and Complex128")
m, n = size(A)
τ = zeros(T, min(m,n))
@inbounds begin
for k = 1:min(m-1+!(T<:Real),n)
τk = elementaryLeft!(A, k, k)
τ[k] = τk
for j = k+1:n
vAj = A[k,j]
for i = k+1:m
vAj += conj(A[i,k])*A[i,j]
end
vAj = conj(τk)*vAj
A[k,j] -= vAj
for i = k+1:m
A[i,j] -= A[i,k]*vAj
end
end
end
end
QR(A, τ)
end
qrfact{T<:BlasFloat}(A::StridedMatrix{T}; pivot=false) = qrfact!(copy(A),pivot=pivot)
qrfact{T}(A::StridedMatrix{T}; pivot=false) = (S = typeof(one(T)/norm(one(T)));S != T ? qrfact!(convert(AbstractMatrix{S},A), pivot=pivot) : qrfact!(copy(A),pivot=pivot))
qrfact(x::Number) = qrfact(fill(x,1,1))
function qr(A::Union(Number, AbstractMatrix); pivot=false, thin::Bool=true)
F = qrfact(A, pivot=pivot)
full(F[:Q], thin=thin), F[:R]
end
convert{T}(::Type{QR{T}},A::QR) = QR(convert(AbstractMatrix{T}, A.factors), convert(Vector{T}, A.τ))
convert{T}(::Type{Factorization{T}}, A::QR) = convert(QR{T}, A)
convert{T}(::Type{QRCompactWY{T}},A::QRCompactWY) = QRCompactWY(convert(AbstractMatrix{T}, A.factors), convert(AbstractMatrix{T}, A.T))
convert{T}(::Type{Factorization{T}}, A::QRCompactWY) = convert(QRCompactWY{T}, A)
convert{T}(::Type{QRPivoted{T}},A::QRPivoted) = QRPivoted(convert(AbstractMatrix{T}, A.factors), convert(Vector{T}, A.τ), A.jpvt)
convert{T}(::Type{Factorization{T}}, A::QRPivoted) = convert(QRPivoted{T}, A)
function getindex(A::QR, d::Symbol)
m, n = size(A)
d == :R && return triu!(A.factors[1:min(m,n), 1:n])
d == :Q && return QRPackedQ(A.factors,A.τ)
throw(KeyError(d))
end
function getindex(A::QRCompactWY, d::Symbol)
m, n = size(A)
d == :R && return triu!(A.factors[1:min(m,n), 1:n])
d == :Q && return QRCompactWYQ(A.factors,A.T)
throw(KeyError(d))
end
function getindex{T}(A::QRPivoted{T}, d::Symbol)
m, n = size(A)
d == :R && return triu!(A.factors[1:min(m,n), 1:n])
d == :Q && return QRPackedQ(A.factors,A.τ)
d == :p && return A.jpvt
if d == :P
p = A[:p]
n = length(p)
P = zeros(T, n, n)
for i in 1:n
P[p[i],i] = one(T)
end
return P
end
throw(KeyError(d))
end
immutable QRPackedQ{T} <: AbstractMatrix{T}
factors::Matrix{T}
τ::Vector{T}
end
immutable QRCompactWYQ{S} <: AbstractMatrix{S}
factors::Matrix{S}
T::Matrix{S}
end
convert{T}(::Type{QRPackedQ{T}}, Q::QRPackedQ) = QRPackedQ(convert(AbstractMatrix{T}, Q.factors), convert(Vector{T}, Q.τ))
convert{T}(::Type{AbstractMatrix{T}}, Q::QRPackedQ) = convert(QRPackedQ{T}, Q)
convert{S}(::Type{QRCompactWYQ{S}}, Q::QRCompactWYQ) = QRCompactWYQ(convert(AbstractMatrix{S}, Q.factors), convert(AbstractMatrix{S}, Q.T))
convert{S}(::Type{AbstractMatrix{S}}, Q::QRCompactWYQ) = convert(QRCompactWYQ{S}, Q)
size(A::Union(QR,QRCompactWY,QRPivoted), dim::Integer) = size(A.factors, dim)
size(A::Union(QR,QRCompactWY,QRPivoted)) = size(A.factors)
size(A::Union(QRPackedQ,QRCompactWYQ), dim::Integer) = 0 < dim ? (dim <= 2 ? size(A.factors, 1) : 1) : throw(BoundsError())
size(A::Union(QRPackedQ,QRCompactWYQ)) = size(A, 1), size(A, 2)
full{T}(A::Union(QRPackedQ{T},QRCompactWYQ{T}); thin::Bool=true) = A_mul_B!(A, thin ? eye(T, size(A.factors,1), minimum(size(A.factors))) : eye(T, size(A.factors,1)))
## Multiplication by Q
### QB
A_mul_B!{T<:BlasFloat}(A::QRCompactWYQ{T}, B::StridedVecOrMat{T}) = LAPACK.gemqrt!('L','N',A.factors,A.T,B)
A_mul_B!{T<:BlasFloat}(A::QRPackedQ{T}, B::StridedVecOrMat{T}) = LAPACK.ormqr!('L','N',A.factors,A.τ,B)
function A_mul_B!{T}(A::QRPackedQ{T}, B::AbstractVecOrMat{T})
mA, nA = size(A.factors)
mB, nB = size(B,1), size(B,2)
mA == mB || throw(DimensionMismatch(""))
Afactors = A.factors
@inbounds begin
for k = min(mA,nA):-1:1
for j = 1:nB
vBj = B[k,j]
for i = k+1:mB
vBj += conj(Afactors[i,k])*B[i,j]
end
vBj = A.τ[k]*vBj
B[k,j] -= vBj
for i = k+1:mB
B[i,j] -= Afactors[i,k]*vBj
end
end
end
end
B
end
function *{TA,Tb}(A::Union(QRPackedQ{TA},QRCompactWYQ{TA}), b::StridedVector{Tb})
TAb = promote_type(TA,Tb)
Anew = convert(AbstractMatrix{TAb},A)
bnew = size(A.factors,1) == length(b) ? (Tb == TAb ? copy(b) : convert(Vector{TAb}, b)) : (size(A.factors,2) == length(b) ? [b,zeros(TAb, size(A.factors,1)-length(b))] : throw(DimensionMismatch("")))
A_mul_B!(Anew,bnew)
end
function *{TA,TB}(A::Union(QRPackedQ{TA},QRCompactWYQ{TA}), B::StridedMatrix{TB})
TAB = promote_type(TA,TB)
Anew = convert(AbstractMatrix{TAB},A)
Bnew = size(A.factors,1) == size(B,1) ? (TB == TAB ? copy(B) : convert(AbstractMatrix{TAB}, B)) : (size(A.factors,2) == size(B,1) ? [B;zeros(TAB, size(A.factors,1)-size(B,1),size(B,2))] : throw(DimensionMismatch("")))
A_mul_B!(Anew,Bnew)
end
### QcB
Ac_mul_B!{T<:BlasReal}(A::QRCompactWYQ{T}, B::StridedVecOrMat{T}) = LAPACK.gemqrt!('L','T',A.factors,A.T,B)
Ac_mul_B!{T<:BlasComplex}(A::QRCompactWYQ{T}, B::StridedVecOrMat{T}) = LAPACK.gemqrt!('L','C',A.factors,A.T,B)
Ac_mul_B!{T<:BlasReal}(A::QRPackedQ{T}, B::StridedVecOrMat{T}) = LAPACK.ormqr!('L','T',A.factors,A.τ,B)
Ac_mul_B!{T<:BlasComplex}(A::QRPackedQ{T}, B::StridedVecOrMat{T}) = LAPACK.ormqr!('L','C',A.factors,A.τ,B)
function Ac_mul_B!{T}(A::QRPackedQ{T}, B::AbstractVecOrMat{T})
mA, nA = size(A.factors)
mB, nB = size(B,1), size(B,2)
mA == mB || throw(DimensionMismatch(""))
Afactors = A.factors
@inbounds begin
for k = 1:min(mA,nA)
for j = 1:nB
vBj = B[k,j]
for i = k+1:mB
vBj += conj(Afactors[i,k])*B[i,j]
end
vBj = conj(A.τ[k])*vBj
B[k,j] -= vBj
for i = k+1:mB
B[i,j] -= Afactors[i,k]*vBj
end
end
end
end
B
end
function Ac_mul_B{TQ<:Number,TB<:Number,N}(Q::Union(QRPackedQ{TQ},QRCompactWYQ{TQ}), B::StridedArray{TB,N})
TQB = promote_type(TQ,TB)
Ac_mul_B!(convert(AbstractMatrix{TQB}, Q), TB == TQB ? copy(B) : convert(AbstractArray{TQB,N}, B))
end
### AQ
A_mul_B!{T<:BlasFloat}(A::StridedVecOrMat{T}, B::QRCompactWYQ{T}) = LAPACK.gemqrt!('R','N', B.factors, B.T, A)
A_mul_B!(A::StridedVecOrMat, B::QRPackedQ) = LAPACK.ormqr!('R', 'N', B.factors, B.τ, A)
function A_mul_B!{T}(A::StridedMatrix{T},Q::QRPackedQ{T})
mQ, nQ = size(Q.factors)
mA, nA = size(A,1), size(A,2)
nA == mQ || throw(DimensionMismatch(""))
Qfactors = Q.factors
@inbounds begin
for k = 1:min(mQ,nQ)
for i = 1:mA
vAi = A[i,k]
for j = k+1:mQ
vAi += A[i,j]*Qfactors[j,k]
end
vAi = vAi*Q.τ[k]
A[i,k] -= vAi
for j = k+1:nA
A[i,j] -= vAi*conj(Qfactors[j,k])
end
end
end
end
A
end
function *{TA,TQ,N}(A::StridedArray{TA,N}, Q::Union(QRPackedQ{TQ},QRCompactWYQ{TQ}))
TAQ = promote_type(TA, TQ)
A_mul_B!(TA==TAQ ? copy(A) : convert(AbstractArray{TAQ,N}, A), convert(AbstractMatrix{TAQ}, Q))
end
### AQc
A_mul_Bc!{T<:BlasReal}(A::StridedVecOrMat{T}, B::QRCompactWYQ{T}) = LAPACK.gemqrt!('R','T',B.factors,B.T,A)
A_mul_Bc!{T<:BlasComplex}(A::StridedVecOrMat{T}, B::QRCompactWYQ{T}) = LAPACK.gemqrt!('R','C',B.factors,B.T,A)
A_mul_Bc!{T<:BlasReal}(A::StridedVecOrMat{T}, B::QRPackedQ{T}) = LAPACK.ormqr!('R','T',B.factors,B.τ,A)
A_mul_Bc!{T<:BlasComplex}(A::StridedVecOrMat{T}, B::QRPackedQ{T}) = LAPACK.ormqr!('R','C',B.factors,B.τ,A)
function A_mul_Bc!{T}(A::AbstractMatrix{T},Q::QRPackedQ{T})
mQ, nQ = size(Q.factors)
mA, nA = size(A,1), size(A,2)
nA == mQ || throw(DimensionMismatch(""))
Qfactors = Q.factors
@inbounds begin
for k = min(mQ,nQ):-1:1
for i = 1:mA
vAi = A[i,k]
for j = k+1:mQ
vAi += A[i,j]*Qfactors[j,k]
end
vAi = vAi*conj(Q.τ[k])
A[i,k] -= vAi
for j = k+1:nA
A[i,j] -= vAi*conj(Qfactors[j,k])
end
end
end
end
A
end
function A_mul_Bc{TA,TB,N}(A::AbstractArray{TA,N}, B::Union(QRCompactWYQ{TB},QRPackedQ{TB}))
TAB = promote_type(TA,TB)
A_mul_Bc!(size(A,2)==size(B.factors,1) ? (TA == TAB ? copy(A) : convert(AbstractMatrix{TAB,N}, A)) : (size(A,2)==size(B.factors,2) ? [A zeros(TAB, size(A, 1), size(B.factors, 1) - size(B.factors, 2))] : throw(DimensionMismatch(""))),convert(AbstractMatrix{TAB}, B))
end
# Julia implementation similarly to xgelsy
function A_ldiv_B!{T<:BlasFloat}(A::Union(QRCompactWY{T},QRPivoted{T}), B::StridedMatrix{T}, rcond::Real)
mA, nA = size(A.factors)
nr = min(mA,nA)
nrhs = size(B, 2)
if nr == 0 return zeros(0, nrhs), 0 end
ar = abs(A.factors[1])
if ar == 0 return zeros(nr, nrhs), 0 end
rnk = 1
xmin = ones(T, nr)
xmax = ones(T, nr)
tmin = tmax = ar
while rnk < nr
tmin, smin, cmin = LAPACK.laic1!(2, sub(xmin, 1:rnk), tmin, sub(A.factors, 1:rnk, rnk + 1), A.factors[rnk + 1, rnk + 1])
tmax, smax, cmax = LAPACK.laic1!(1, sub(xmax, 1:rnk), tmax, sub(A.factors, 1:rnk, rnk + 1), A.factors[rnk + 1, rnk + 1])
tmax*rcond > tmin && break
xmin[1:rnk + 1] = [smin*sub(xmin, 1:rnk), cmin]
xmax[1:rnk + 1] = [smax*sub(xmin, 1:rnk), cmax]
rnk += 1
# if cond(r[1:rnk, 1:rnk])*rcond < 1 break end
end
C, τ = LAPACK.tzrzf!(A.factors[1:rnk,:])
A_ldiv_B!(Triangular(C[1:rnk,1:rnk],:U),sub(Ac_mul_B!(A[:Q],sub(B, 1:mA, 1:nrhs)),1:rnk,1:nrhs))
B[rnk+1:end,:] = zero(T)
LAPACK.ormrz!('L', iseltype(B, Complex) ? 'C' : 'T', C, τ, sub(B,1:nA,1:nrhs))
return isa(A,QRPivoted) ? B[invperm(A[:p]),:] : B[1:nA,:], rnk
end
A_ldiv_B!{T<:BlasFloat}(A::Union(QRCompactWY{T},QRPivoted{T}), B::StridedVector{T}) = A_ldiv_B!(A,reshape(B,length(B),1))[:]
A_ldiv_B!{T<:BlasFloat}(A::Union(QRCompactWY{T},QRPivoted{T}), B::StridedVecOrMat{T}) = A_ldiv_B!(A, B, sqrt(eps(real(float(one(eltype(B)))))))[1]
function A_ldiv_B!{T}(A::QR{T},B::StridedMatrix{T})
m, n = size(A)
minmn = min(m,n)
mB, nB = size(B)
Ac_mul_B!(A[:Q],sub(B,1:m,1:nB)) # Reconsider when arrayviews are merged.
R = A[:R]
@inbounds begin
if n > m # minimum norm solution
τ = zeros(T,m)
for k = m:-1:1 # Trapezoid to triangular by elementary operation
τ[k] = elementaryRightTrapezoid!(R,k)
for i = 1:k-1
vRi = R[i,k]
for j = m+1:n
vRi += R[i,j]*R[k,j]
end
vRi *= τ[k]
R[i,k] -= vRi
for j = m+1:n
R[i,j] -= vRi*R[k,j]
end
end
end
end
for k = 1:nB # solve triangular system. When array views are implemented, consider exporting to function.
for i = minmn:-1:1
for j = i+1:minmn
B[i,k] -= R[i,j]*B[j,k]
end
B[i,k] /= R[i,i]
end
end
if n > m # Apply elemenary transformation to solution
B[m+1:mB,1:nB] = zero(T)
for j = 1:nB
for k = 1:m
vBj = B[k,j]
for i = m+1:n
vBj += B[i,j]*conj(R[k,i])
end
vBj *= τ[k]
B[k,j] -= vBj
for i = m+1:n
B[i,j] -= R[k,i]*vBj
end
end
end
end
end
return B[1:n,:]
end
A_ldiv_B!(A::QR, B::StridedVector) = A_ldiv_B!(A, reshape(B, length(B), 1))[:]
A_ldiv_B!(A::QRPivoted, B::StridedVector) = A_ldiv_B!(QR(A.factors,A.τ),B)[invperm(A.jpvt)]
A_ldiv_B!(A::QRPivoted, B::StridedMatrix) = A_ldiv_B!(QR(A.factors,A.τ),B)[invperm(A.jpvt),:]
function \{TA,Tb}(A::Union(QR{TA},QRCompactWY{TA},QRPivoted{TA}),b::StridedVector{Tb})
S = promote_type(TA,Tb)
m,n = size(A)
m == length(b) || throw(DimensionMismatch("left hand side has $(m) rows, but right hand side has length $(length(b))"))
n > m ? A_ldiv_B!(convert(Factorization{S},A),[b,zeros(S,n-m)]) : A_ldiv_B!(convert(Factorization{S},A), S == Tb ? copy(b) : convert(AbstractVector{S}, b))
end
function \{TA,TB}(A::Union(QR{TA},QRCompactWY{TA},QRPivoted{TA}),B::StridedMatrix{TB})
S = promote_type(TA,TB)
m,n = size(A)
m == size(B,1) || throw(DimensionMismatch("left hand side has $(m) rows, but right hand side has $(size(B,1)) rows"))
n > m ? A_ldiv_B!(convert(Factorization{S},A),[B;zeros(S,n-m,size(B,2))]) : A_ldiv_B!(convert(Factorization{S},A), S == TB ? copy(B) : convert(AbstractMatrix{S}, B))
end
##TODO: Add methods for rank(A::QRP{T}) and adjust the (\) method accordingly
## Add rcond methods for Cholesky, LU, QR and QRP types
## Lower priority: Add LQ, QL and RQ factorizations
# FIXME! Should add balancing option through xgebal
immutable Hessenberg{T} <: Factorization{T}
factors::Matrix{T}
τ::Vector{T}
end
Hessenberg(A::StridedMatrix) = Hessenberg(LAPACK.gehrd!(A)...)
hessfact!{T<:BlasFloat}(A::StridedMatrix{T}) = Hessenberg(A)
hessfact{T<:BlasFloat}(A::StridedMatrix{T}) = hessfact!(copy(A))
hessfact{T}(A::StridedMatrix{T}) = (S = promote_type(Float32,typeof(one(T)/norm(one(T)))); S != T ? hessfact!(convert(AbstractMatrix{S},A)) : hessfact!(copy(A)))
immutable HessenbergQ{T} <: AbstractMatrix{T}
factors::Matrix{T}
τ::Vector{T}
end
HessenbergQ(A::Hessenberg) = HessenbergQ(A.factors, A.τ)
size(A::HessenbergQ, args...) = size(A.factors, args...)
function getindex(A::Hessenberg, d::Symbol)
d == :Q && return HessenbergQ(A)
d == :H && return triu(A.factors, -1)
throw(KeyError(d))
end
full(A::HessenbergQ) = LAPACK.orghr!(1, size(A.factors, 1), copy(A.factors), A.τ)
# Also printing of QRQs
print_matrix(io::IO, A::Union(QRPackedQ,QRCompactWYQ,HessenbergQ), sz::(Integer, Integer), punct...) = print_matrix(io, full(A), sz, punct...)
#######################
# Eigendecompositions #
#######################
# Eigenvalues
immutable Eigen{T,V} <: Factorization{T}
values::Vector{V}
vectors::Matrix{T}
end
# Generalized eigenvalue problem.
immutable GeneralizedEigen{T,V} <: Factorization{T}
values::Vector{V}
vectors::Matrix{T}
end
function getindex(A::Union(Eigen,GeneralizedEigen), d::Symbol)
d == :values && return A.values
d == :vectors && return A.vectors
throw(KeyError(d))
end
isposdef(A::Union(Eigen,GeneralizedEigen)) = all(A.values .> 0)
function eigfact!{T<:BlasReal}(A::StridedMatrix{T}; permute::Bool=true, scale::Bool=true)
n = size(A, 2)
n==0 && return Eigen(zeros(T, 0), zeros(T, 0, 0))
issym(A) && return eigfact!(Symmetric(A))
A, WR, WI, VL, VR, _ = LAPACK.geevx!(permute ? (scale ? 'B' : 'P') : (scale ? 'S' : 'N'), 'N', 'V', 'N', A)
all(WI .== 0.) && return Eigen(WR, VR)
evec = zeros(Complex{T}, n, n)
j = 1
while j <= n
if WI[j] == 0.0
evec[:,j] = VR[:,j]
else
evec[:,j] = VR[:,j] + im*VR[:,j+1]
evec[:,j+1] = VR[:,j] - im*VR[:,j+1]
j += 1
end
j += 1
end
return Eigen(complex(WR, WI), evec)
end
function eigfact!{T<:BlasComplex}(A::StridedMatrix{T}; permute::Bool=true, scale::Bool=true)
n = size(A, 2)
n == 0 && return Eigen(zeros(T, 0), zeros(T, 0, 0))
ishermitian(A) && return eigfact!(Hermitian(A))
return Eigen(LAPACK.geevx!(permute ? (scale ? 'B' : 'P') : (scale ? 'S' : 'N'), 'N', 'V', 'N', A)[[2,4]]...)
end
eigfact{T}(A::AbstractMatrix{T}, args...; kwargs...) = (S = promote_type(Float32,typeof(one(T)/norm(one(T)))); S != T ? eigfact!(convert(AbstractMatrix{S}, A), args...; kwargs...) : eigfact!(copy(A), args...; kwargs...))
eigfact(x::Number) = Eigen([x], fill(one(x), 1, 1))
# function eig(A::Union(Number, AbstractMatrix); permute::Bool=true, scale::Bool=true)
# F = eigfact(A, permute=permute, scale=scale)
# F[:values], F[:vectors]
# end
function eig(A::Union(Number, AbstractMatrix), args...; kwargs...)
F = eigfact(A, args..., kwargs...)
F[:values], F[:vectors]
end
#Calculates eigenvectors
eigvecs(A::Union(Number, AbstractMatrix), args...; kwargs...) = eigfact(A, args...; kwargs...)[:vectors]
function eigvals!{T<:BlasReal}(A::StridedMatrix{T}; permute::Bool=true, scale::Bool=true)
issym(A) && return eigvals!(Symmetric(A))
_, valsre, valsim, _ = LAPACK.geevx!(permute ? (scale ? 'B' : 'P') : (scale ? 'S' : 'N'), 'N', 'N', 'N', A)
return all(valsim .== 0) ? valsre : complex(valsre, valsim)
end
function eigvals!{T<:BlasComplex}(A::StridedMatrix{T}; permute::Bool=true, scale::Bool=true)
ishermitian(A) && return eigvals(Hermitian(A))
return LAPACK.geevx!(permute ? (scale ? 'B' : 'P') : (scale ? 'S' : 'N'), 'N', 'N', 'N', A)[2]
end
eigvals{T}(A::AbstractMatrix{T}, args...; kwargs...) = (S = promote_type(Float32,typeof(one(T)/norm(one(T)))); S != T ? eigvals!(convert(AbstractMatrix{S}, A), args...; kwargs...) : eigvals!(copy(A), args...; kwargs...))
eigvals{T<:Number}(x::T; kwargs...) = (val = convert(promote_type(Float32,typeof(one(T)/norm(one(T)))),x); imag(val) == 0 ? [real(val)] : [val])
#Computes maximum and minimum eigenvalue
function eigmax(A::Union(Number, AbstractMatrix); kwargs...)
v = eigvals(A; kwargs...)
iseltype(v,Complex) ? error("DomainError: complex eigenvalues cannot be ordered") : maximum(v)
end
function eigmin(A::Union(Number, AbstractMatrix); kwargs...)
v = eigvals(A; kwargs...)
iseltype(v,Complex) ? error("DomainError: complex eigenvalues cannot be ordered") : minimum(v)
end
inv(A::Eigen) = A.vectors/Diagonal(A.values)*A.vectors'
det(A::Eigen) = prod(A.values)
# Generalized eigenproblem
function eigfact!{T<:BlasReal}(A::StridedMatrix{T}, B::StridedMatrix{T})
issym(A) && isposdef(B) && return eigfact!(Symmetric(A), Symmetric(B))
n = size(A, 1)
alphar, alphai, beta, _, vr = LAPACK.ggev!('N', 'V', A, B)
all(alphai .== 0) && return GeneralizedEigen(alphar ./ beta, vr)
vecs = zeros(Complex{T}, n, n)
j = 1
while j <= n
if alphai[j] == 0.0
vecs[:,j] = vr[:,j]
else
vecs[:,j ] = vr[:,j] + im*vr[:,j+1]
vecs[:,j+1] = vr[:,j] - im*vr[:,j+1]
j += 1
end
j += 1
end
return GeneralizedEigen(complex(alphar, alphai)./beta, vecs)
end
function eigfact!{T<:BlasComplex}(A::StridedMatrix{T}, B::StridedMatrix{T})
ishermitian(A) && isposdef(B) && return eigfact!(Hermitian(A), Hermitian(B))
alpha, beta, _, vr = LAPACK.ggev!('N', 'V', A, B)
return GeneralizedEigen(alpha./beta, vr)
end
eigfact{TA,TB}(A::AbstractMatrix{TA}, B::AbstractMatrix{TB}) = (S = promote_type(Float32,typeof(one(TA)/norm(one(TA))),TB); eigfact!(S != TA ? convert(AbstractMatrix{S},A) : copy(A), S != TB ? convert(AbstractMatrix{S},B) : copy(B)))
function eigvals!{T<:BlasReal}(A::StridedMatrix{T}, B::StridedMatrix{T})
issym(A) && isposdef(B) && return eigvals!(Symmetric(A), Symmetric(B))
alphar, alphai, beta, vl, vr = LAPACK.ggev!('N', 'N', A, B)
(all(alphai .== 0) ? alphar : complex(alphar, alphai))./beta
end
function eigvals!{T<:BlasComplex}(A::StridedMatrix{T}, B::StridedMatrix{T})
ishermitian(A) && isposdef(B) && return eigvals!(Hermitian(A), Hermitian(B))
alpha, beta, vl, vr = LAPACK.ggev!('N', 'N', A, B)
alpha./beta
end
eigvals{TA,TB}(A::AbstractMatrix{TA}, B::AbstractMatrix{TB}) = (S = promote_type(Float32,typeof(one(TA)/norm(one(TA))),TB); eigvals!(S != TA ? convert(AbstractMatrix{S},A) : copy(A), S != TB ? convert(AbstractMatrix{S},B) : copy(B)))
# SVD
immutable SVD{T<:BlasFloat,Tr} <: Factorization{T}
U::Matrix{T}
S::Vector{Tr}
Vt::Matrix{T}
end
function svdfact!{T<:BlasFloat}(A::StridedMatrix{T}; thin::Bool=true)
m,n = size(A)
if m == 0 || n == 0
u,s,vt = (eye(T, m, thin ? n : m), real(zeros(T,0)), eye(T,n,n))
else
u,s,vt = LAPACK.gesdd!(thin ? 'S' : 'A', A)
end
SVD(u,s,vt)
end
svdfact{T<:BlasFloat}(A::StridedMatrix{T};thin=true) = svdfact!(copy(A),thin=thin)
svdfact{T}(A::StridedVecOrMat{T};thin=true) = (S = promote_type(Float32,typeof(one(T)/norm(one(T)))); S != T ? svdfact!(convert(AbstractMatrix{S},A),thin=thin) : svdfact!(copy(A),thin=thin))
svdfact(x::Number; thin::Bool=true) = SVD(x == 0 ? fill(one(x), 1, 1) : fill(x/abs(x), 1, 1), [abs(x)], fill(one(x), 1, 1))
svdfact(x::Integer; thin::Bool=true) = svdfact(float(x), thin=thin)
function svd(A::Union(Number, AbstractArray); thin::Bool=true)
F = svdfact(A, thin=thin)
F.U, F.S, F.Vt'
end
function getindex(F::SVD, d::Symbol)
d == :U && return F.U
d == :S && return F.S
d == :Vt && return F.Vt
d == :V && return F.Vt'
throw(KeyError(d))
end
svdvals!{T<:BlasFloat}(A::StridedMatrix{T}) = any([size(A)...].==0) ? zeros(T, 0) : LAPACK.gesdd!('N', A)[2]
svdvals{T<:BlasFloat}(A::StridedMatrix{T}) = svdvals!(copy(A))
svdvals{T}(A::StridedMatrix{T}) = (S = promote_type(Float32,typeof(one(T)/norm(one(T)))); S != T ? svdvals!(convert(AbstractMatrix{S}, A)) : svdvals!(copy(A)))
svdvals(x::Number) = [abs(x)]
# SVD least squares
function \{T<:BlasFloat}(A::SVD{T}, B::StridedVecOrMat{T})
n = length(A.S)
Sinv = zeros(T, n)
Sinv[A.S .> sqrt(eps())] = 1.0 ./ A.S
scale(A.Vt', Sinv) * A.U[:,1:n]'B
end
# Generalized svd
immutable GeneralizedSVD{T} <: Factorization{T}
U::Matrix{T}
V::Matrix{T}
Q::Matrix{T}
a::Vector
b::Vector
k::Int
l::Int
R::Matrix{T}
end
function svdfact!{T<:BlasFloat}(A::StridedMatrix{T}, B::StridedMatrix{T})
U, V, Q, a, b, k, l, R = LAPACK.ggsvd!('U', 'V', 'Q', A, B)
GeneralizedSVD(U, V, Q, a, b, int(k), int(l), R)
end
svdfact{T<:BlasFloat}(A::StridedMatrix{T}, B::StridedMatrix{T}) = svdfact!(copy(A),copy(B))
svdfact{TA,TB}(A::StridedMatrix{TA}, B::StridedMatrix{TB}) = (S = promote_type(Float32,typeof(one(TA)/norm(one(TA))),TB); svdfact!(S != TA ? convert(AbstractMatrix{S},A) : copy(A), S != TB ? convert(AbstractMatrix{S},B) : copy(B)))
function svd(A::AbstractMatrix, B::AbstractMatrix)
F = svdfact(A, B)
F[:U], F[:V], F[:Q], F[:D1], F[:D2], F[:R0]
end
function getindex{T}(obj::GeneralizedSVD{T}, d::Symbol)
d == :U && return obj.U
d == :V && return obj.V
d == :Q && return obj.Q
(d == :alpha || d == :a) && return obj.a
(d == :beta || d == :b) && return obj.b
(d == :vals || d == :S) && return obj.a[1:obj.k + obj.l] ./ obj.b[1:obj.k + obj.l]
if d == :D1
m = size(obj.U, 1)
if m - obj.k - obj.l >= 0
return [eye(T, obj.k) zeros(T, obj.k, obj.l); zeros(T, obj.l, obj.k) diagm(obj.a[obj.k + 1:obj.k + obj.l]); zeros(T, m - obj.k - obj.l, obj.k + obj.l)]
else
return [eye(T, m, obj.k) [zeros(T, obj.k, m - obj.k); diagm(obj.a[obj.k + 1:m])] zeros(T, m, obj.k + obj.l - m)]
end
end
if d == :D2
m = size(obj.U, 1)
p = size(obj.V, 1)
if m - obj.k - obj.l >= 0
return [zeros(T, obj.l, obj.k) diagm(obj.b[obj.k + 1:obj.k + obj.l]); zeros(T, p - obj.l, obj.k + obj.l)]
else
return [zeros(T, p, obj.k) [diagm(obj.b[obj.k + 1:m]); zeros(T, obj.k + p - m, m - obj.k)] [zeros(T, m - obj.k, obj.k + obj.l - m); eye(T, obj.k + p - m, obj.k + obj.l - m)]]
end
end
d == :R && return obj.R
if d == :R0
n = size(obj.Q, 1)
return [zeros(T, obj.k + obj.l, n - obj.k - obj.l) obj.R]
end
throw(KeyError(d))
end
function svdvals!{T<:BlasFloat}(A::StridedMatrix{T}, B::StridedMatrix{T})
_, _, _, a, b, k, l, _ = LAPACK.ggsvd!('N', 'N', 'N', A, B)
a[1:k + l] ./ b[1:k + l]
end
svdvals{T<:BlasFloat}(A::StridedMatrix{T},B::StridedMatrix{T}) = svdvals!(copy(A),copy(B))
svdvals{TA,TB}(A::StridedMatrix{TA}, B::StridedMatrix{TB}) = (S = promote_type(Float32,typeof(one(T)/norm(one(TA))),TB); svdvals!(S != TA ? convert(AbstractMatrix{S}, A) : copy(A), S != TB ? convert(AbstractMatrix{S}, B) : copy(B)))
immutable Schur{Ty<:BlasFloat} <: Factorization{Ty}
T::Matrix{Ty}
Z::Matrix{Ty}
values::Vector
end
schurfact!{T<:BlasFloat}(A::StridedMatrix{T}) = Schur(LinAlg.LAPACK.gees!('V', A)...)
schurfact{T<:BlasFloat}(A::StridedMatrix{T}) = schurfact!(copy(A))
schurfact{T}(A::StridedMatrix{T}) = (S = promote_type(Float32,typeof(one(T)/norm(one(T)))); S != T ? schurfact!(convert(AbstractMatrix{S},A)) : schurfact!(copy(A)))
function getindex(F::Schur, d::Symbol)
(d == :T || d == :Schur) && return F.T
(d == :Z || d == :vectors) && return F.Z
d == :values && return F.values
throw(KeyError(d))
end
function schur(A::AbstractMatrix)
SchurF = schurfact(A)
SchurF[:T], SchurF[:Z], SchurF[:values]
end
immutable GeneralizedSchur{Ty<:BlasFloat} <: Factorization{Ty}
S::Matrix{Ty}
T::Matrix{Ty}
alpha::Vector
beta::Vector{Ty}
Q::Matrix{Ty}
Z::Matrix{Ty}
end
schurfact!{T<:BlasFloat}(A::StridedMatrix{T}, B::StridedMatrix{T}) = GeneralizedSchur(LinAlg.LAPACK.gges!('V', 'V', A, B)...)
schurfact{T<:BlasFloat}(A::StridedMatrix{T},B::StridedMatrix{T}) = schurfact!(copy(A),copy(B))
schurfact{TA,TB}(A::StridedMatrix{TA}, B::StridedMatrix{TB}) = (S = promote_type(Float32,typeof(one(TA)/norm(one(TA))),TB); schurfact!(S != TA ? convert(AbstractMatrix{S},A) : copy(A), S != TB ? convert(AbstractMatrix{S},B) : copy(B)))
function getindex(F::GeneralizedSchur, d::Symbol)
d == :S && return F.S
d == :T && return F.T
d == :alpha && return F.alpha
d == :beta && return F.beta
d == :values && return F.alpha./F.beta
(d == :Q || d == :left) && return F.Q
(d == :Z || d == :right) && return F.Z
throw(KeyError(d))
end
function schur(A::AbstractMatrix, B::AbstractMatrix)
SchurF = schurfact(A, B)
SchurF[:S], SchurF[:T], SchurF[:Q], SchurF[:Z]
end
### General promotion rules
convert{T}(::Type{Factorization{T}}, F::Factorization{T}) = F
inv{T}(F::Factorization{T}) = A_ldiv_B!(F, eye(T, size(F,1)))
function \{TF<:Number,TB<:Number,N}(F::Factorization{TF}, B::AbstractArray{TB,N})
TFB = typeof(one(TF)/one(TB))
A_ldiv_B!(convert(Factorization{TFB}, F), TB == TFB ? copy(B) : convert(AbstractArray{TFB,N}, B))
end
function Ac_ldiv_B{TF<:Number,TB<:Number,N}(F::Factorization{TF}, B::AbstractArray{TB,N})
TFB = typeof(one(TF)/one(TB))
Ac_ldiv_B!(convert(Factorization{TFB}, F), TB == TFB ? copy(B) : convert(AbstractArray{TFB,N}, B))
end
function At_ldiv_B{TF<:Number,TB<:Number,N}(F::Factorization{TF}, B::AbstractArray{TB,N})
TFB = typeof(one(TF)/one(TB))
At_ldiv_B!(convert(Factorization{TFB}, F), TB == TFB ? copy(B) : convert(AbstractArray{TFB,N}, B))
end