#### Specialized matrix types ####

## Hermitian tridiagonal matrices
immutable SymTridiagonal{T} <: AbstractMatrix{T}
    dv::Vector{T}                        # diagonal
    ev::Vector{T}                        # subdiagonal
    function SymTridiagonal(dv::Vector{T}, ev::Vector{T})
        length(ev)==length(dv)-1 || throw(DimensionMismatch(""))
        new(dv,ev)
    end
end

SymTridiagonal{T}(dv::Vector{T}, ev::Vector{T}) = SymTridiagonal{T}(dv, ev)

function SymTridiagonal{Td,Te}(dv::Vector{Td}, ev::Vector{Te})
    T = promote_type(Td,Te)
    SymTridiagonal(convert(Vector{T}, dv), convert(Vector{T}, ev))
end

SymTridiagonal(A::AbstractMatrix) = diag(A,1)==diag(A,-1)?SymTridiagonal(diag(A), diag(A,1)):throw(DimensionMismatch("matrix is not symmetric; cannot convert to SymTridiagonal"))
full{T}(M::SymTridiagonal{T}) = convert(Matrix{T}, M)
convert{T}(::Type{SymTridiagonal{T}}, S::SymTridiagonal) = SymTridiagonal(convert(Vector{T}, S.dv), convert(Vector{T}, S.ev))
convert{T}(::Type{AbstractMatrix{T}}, S::SymTridiagonal) = SymTridiagonal(convert(Vector{T}, S.dv), convert(Vector{T}, S.ev))
convert{T}(::Type{Matrix{T}}, M::SymTridiagonal{T})=diagm(M.dv)+diagm(M.ev,-1)+conj(diagm(M.ev,1))

size(m::SymTridiagonal) = (length(m.dv), length(m.dv))
size(m::SymTridiagonal, d::Integer) = d<1 ? error("dimension out of range") : (d<=2 ? length(m.dv) : 1)

#Elementary operations
for func in (:copy, :round, :iround, :conj)
    @eval begin
        ($func)(M::SymTridiagonal) = SymTridiagonal(($func)(M.dv), ($func)(M.ev))
    end
end

transpose(M::SymTridiagonal) = M #Identity operation
ctranspose(M::SymTridiagonal) = conj(M)

function diag{T}(M::SymTridiagonal{T}, n::Integer=0)
    absn = abs(n)
    absn==0 ? M.dv : absn==1 ? M.ev : absn<size(M,1) ? zeros(T,size(M,1)-absn) : throw(BoundsError())
end

+(A::SymTridiagonal, B::SymTridiagonal) = SymTridiagonal(A.dv+B.dv, A.ev+B.ev)
-(A::SymTridiagonal, B::SymTridiagonal) = SymTridiagonal(A.dv-B.dv, A.ev-B.ev)
*(A::SymTridiagonal, B::Number) = SymTridiagonal(A.dv*B, A.ev*B)
*(B::Number, A::SymTridiagonal) = A*B
/(A::SymTridiagonal, B::Number) = SymTridiagonal(A.dv/B, A.ev/B)
==(A::SymTridiagonal, B::SymTridiagonal) = (A.dv==B.dv) && (A.ev==B.ev)

## Solver
function \{T<:BlasFloat}(M::SymTridiagonal{T}, rhs::StridedVecOrMat{T})
    if stride(rhs, 1) == 1
        return LAPACK.gtsv!(copy(M.ev), copy(M.dv), copy(M.ev), copy(rhs))
    end
    solve(Tridiagonal(M), rhs)  # use the Julia "fallback"
end

#Wrap LAPACK DSTE{GR,BZ} to compute eigenvalues
eigfact!{T<:BlasFloat}(m::SymTridiagonal{T}) = Eigen(LAPACK.stegr!('V', m.dv, m.ev)...)
eigfact!{T<:BlasFloat}(m::SymTridiagonal{T}, irange::UnitRange) = Eigen(LAPACK.stegr!('V', 'I', m.dv, m.ev, 0.0, 0.0, irange.start, irange.stop)...)
eigfact!{T<:BlasFloat}(m::SymTridiagonal{T}, vl::Real, vu::Real) = Eigen(LAPACK.stegr!('V', m.dv, m.ev, convert(T, vl), convert(T, vu), 0, 0)...)
eigvals!{T<:BlasFloat}(m::SymTridiagonal{T}) = LAPACK.stegr!('N', 'A', m.dv, m.ev, 0.0, 0.0, 0, 0)[1]
eigvals!{T<:BlasFloat}(m::SymTridiagonal{T}, irange::UnitRange) = LAPACK.stegr!('N', 'I', m.dv, m.ev, 0.0, 0.0, irange.start, irange.stop)[1]
eigvals!{T<:BlasFloat}(m::SymTridiagonal{T}, vl::Real, vu::Real) = LAPACK.stegr!('N', 'V', m.dv, m.ev, vl, vu, 0, 0)[1]

#Computes largest and smallest eigenvalue
eigmax(m::SymTridiagonal) = eigvals(m, size(m, 1), size(m, 1))[1]
eigmin(m::SymTridiagonal) = eigvals(m, 1, 1)[1]

#Compute selected eigenvectors only corresponding to particular eigenvalues
eigvecs(m::SymTridiagonal) = eigfact(m)[:vectors]
eigvecs{T<:BlasFloat,Eigenvalue<:Real}(m::SymTridiagonal{T}, eigvals::Vector{Eigenvalue}) = LAPACK.stein!(m.dv, m.ev, eigvals)

###################
# Generic methods #
###################

#Needed for inv_usmani()
type ZeroOffsetVector
    data::Vector
end
getindex (a::ZeroOffsetVector, i) = a.data[i+1] 
setindex!(a::ZeroOffsetVector, x, i) = a.data[i+1]=x

#Implements the inverse using the recurrence relation between principal minors
# a, b, c are assumed to be the subdiagonal, diagonal, and superdiagonal of
# a tridiagonal matrix.
#Ref:
#    R. Usmani, "Inversion of a tridiagonal Jacobi matrix",
#    Linear Algebra and its Applications 212-213 (1994), pp.413-414
#    doi:10.1016/0024-3795(94)90414-6
function inv_usmani{T}(a::Vector{T}, b::Vector{T}, c::Vector{T})
    n = length(b)
    θ = ZeroOffsetVector(zeros(T, n+1)) #principal minors of A
    θ[0] = 1
    n>=1 && (θ[1] = b[1])
    for i=2:n
        θ[i] = b[i]*θ[i-1]-a[i-1]*c[i-1]*θ[i-2]
    end
    φ = zeros(T, n+1)
    φ[n+1] = 1
    n>=1 && (φ[n] = b[n])
    for i=n-1:-1:1
        φ[i] = b[i]*φ[i+1]-a[i]*c[i]*φ[i+2]
    end
    α = Array(T, n, n)
    for i=1:n, j=1:n
        sign = (i+j)%2==0 ? (+) : (-)
        if i<j
            α[i,j]=(sign)(prod(c[i:j-1]))*θ[i-1]*φ[j+1]/θ[n]
        elseif i==j
            α[i,i]=                       θ[i-1]*φ[i+1]/θ[n]
        else #i>j
            α[i,j]=(sign)(prod(a[j:i-1]))*θ[j-1]*φ[i+1]/θ[n]
        end
    end
    α 
end

#Implements the determinant using principal minors
#Inputs and reference are as above for inv_usmani()
function det_usmani{T}(a::Vector{T}, b::Vector{T}, c::Vector{T})
    n = length(b)
    θa = one(T)
    n==0 && return θa
    θb = b[1]
    for i=2:n
        θb, θa = b[i]*θb-a[i-1]*c[i-1]*θa, θb
    end
    return θb
end

inv(A::SymTridiagonal) = inv_usmani(A.ev, A.dv, A.ev)
det(A::SymTridiagonal) = det_usmani(A.ev, A.dv, A.ev)

function getindex{T}(A::SymTridiagonal{T}, i::Integer, j::Integer)
    (1<=i<=size(A,2) && 1<=j<=size(A,2)) || throw(BoundsError())
    i==j ? A.dv[i] : i==j+1 ? A.ev[j] : i+1==j ? A.ev[i] : zero(T)
end

## Tridiagonal matrices ##
immutable Tridiagonal{T} <: AbstractMatrix{T}
    dl::Vector{T}    # sub-diagonal
    d::Vector{T}     # diagonal
    du::Vector{T}    # sup-diagonal
    du2::Vector{T}   # supsup-diagonal for pivoting
end
function Tridiagonal{T}(dl::Vector{T}, d::Vector{T}, du::Vector{T})
    n = length(d)
    if (length(dl) != n-1 || length(du) != n-1)
        error(string("Cannot make Tridiagonal from incompatible lengths of subdiagonal, diagonal and superdiagonal: (", length(dl), ", ", length(d), ", ", length(du),")"))
    end
    Tridiagonal(dl, d, du, zeros(T,n-2))
end
function Tridiagonal{Tl, Td, Tu}(dl::Vector{Tl}, d::Vector{Td}, du::Vector{Tu})
    Tridiagonal(map(v->convert(Vector{promote_type(Tl,Td,Tu)}, v), (dl, d, du))...)
end

size(M::Tridiagonal) = (length(M.d), length(M.d))
size(M::Tridiagonal, d::Integer) = d<1 ? error("dimension out of range") : (d<=2 ? length(M.d) : 1)

full{T}(M::Tridiagonal{T}) = convert(Matrix{T}, M)
function convert{T}(::Type{Matrix{T}}, M::Tridiagonal{T})
    A = zeros(T, size(M))
    for i = 1:length(M.d)
        A[i,i] = M.d[i]
    end
    for i = 1:length(M.d)-1
        A[i+1,i] = M.dl[i]
        A[i,i+1] = M.du[i]
    end
    A
end
function similar(M::Tridiagonal, T, dims::Dims)
    if length(dims) != 2 || dims[1] != dims[2]
        throw(DimensionMismatch("Tridiagonal matrices must be square"))
    end
    Tridiagonal{T}(similar(M.dl), similar(M.d), similar(M.du), similar(M.du2))
end

# Operations on Tridiagonal matrices
copy!(dest::Tridiagonal, src::Tridiagonal) = Tridiagonal(copy!(dest.dl, src.dl), copy!(dest.d, src.d), copy!(dest.du, src.du), copy!(dest.du2, src.du2))

#Elementary operations
for func in (:copy, :round, :iround, :conj) 
    @eval begin
        ($func)(M::Tridiagonal) = Tridiagonal(map(($func), (M.dl, M.d, M.du, M.du2))...)
    end
end

transpose(M::Tridiagonal) = Tridiagonal(M.du, M.d, M.dl)
ctranspose(M::Tridiagonal) = conj(transpose(M))

diag{T}(M::Tridiagonal{T}, n::Integer=0) = n==0 ? M.d : n==-1 ? M.dl : n==1 ? M.du : abs(n)<size(M,1) ? zeros(T,size(M,1)-abs(n)) : throw(BoundsError()) 
function getindex{T}(A::Tridiagonal{T}, i::Integer, j::Integer)
    (1<=i<=size(A,2) && 1<=j<=size(A,2)) || throw(BoundsError())
    i==j ? A.d[i] : i==j+1 ? A.dl[j] : i+1==j ? A.du[i] : zero(T)
end

###################
# Generic methods #
###################

+(A::Tridiagonal, B::Tridiagonal) = Tridiagonal(A.dl+B.dl, A.d+B.d, A.du+B.du)
-(A::Tridiagonal, B::Tridiagonal) = Tridiagonal(A.dl-B.dl, A.d-B.d, A.du+B.du)
*(A::Tridiagonal, B::Number) = Tridiagonal(A.dl*B, A.d*B, A.du*B)
*(B::Number, A::Tridiagonal) = A*B
/(A::Tridiagonal, B::Number) = Tridiagonal(A.dl/B, A.d/B, A.du/B)

==(A::Tridiagonal, B::Tridiagonal) = (A.dl==B.dl) && (A.d==B.d) && (A.du==B.du)
==(A::Tridiagonal, B::SymTridiagonal) = (A.dl==A.du==B.ev) && (A.d==B.dv)
==(A::SymTridiagonal, B::Tridiagonal) = (B.dl==B.du==A.ev) && (B.d==A.dv)

inv(A::Tridiagonal) = inv_usmani(A.dl, A.d, A.du)
det(A::Tridiagonal) = det_usmani(A.dl, A.d, A.du)

# Elementary operations that mix Tridiagonal and SymTridiagonal matrices
convert(::Type{Tridiagonal}, A::SymTridiagonal) = Tridiagonal(A.ev, A.dv, A.ev)
+(A::Tridiagonal, B::SymTridiagonal) = Tridiagonal(A.dl+B.ev, A.d+B.dv, A.du+B.ev)
+(A::SymTridiagonal, B::Tridiagonal) = Tridiagonal(A.ev+B.dl, A.dv+B.d, A.ev+B.du)
-(A::Tridiagonal, B::SymTridiagonal) = Tridiagonal(A.dl-B.ev, A.d-B.dv, A.du-B.ev)
-(A::SymTridiagonal, B::Tridiagonal) = Tridiagonal(A.ev-B.dl, A.dv-B.d, A.ev-B.du)

convert{T}(::Type{Tridiagonal{T}},M::Tridiagonal) = Tridiagonal(convert(Vector{T}, M.dl), convert(Vector{T}, M.d), convert(Vector{T}, M.du), convert(Vector{T}, M.du2))
convert{T}(::Type{AbstractMatrix{T}},M::Tridiagonal) = convert(Tridiagonal{T}, M)
convert{T}(::Type{Tridiagonal{T}}, M::SymTridiagonal{T}) = Tridiagonal(M)
convert{T}(::Type{SymTridiagonal{T}}, M::Tridiagonal) = M.dl==M.du ? (SymTridiagonal(M.dl, M.d)) :
    error("Tridiagonal is not symmetric, cannot convert to SymTridiagonal")
convert{T}(::Type{SymTridiagonal{T}},M::SymTridiagonal) = SymTridiagonal(convert(Vector{T}, M.dv), convert(Vector{T}, M.ev))

function A_mul_B!(C::AbstractVecOrMat, A::Tridiagonal, B::AbstractVecOrMat)
    size(C,1) == size(B,1) == (nA = size(A,1)) || throw(DimensionMismatch(""))
    size(C,2) == (nB = size(B,2)) || throw(DimensionMismatch(""))
    l = A.dl
    d = A.d
    u = A.du
    @inbounds begin
        for j = 1:nB
            C[1,j] = d[1]*B[1,j] + u[1]*B[2,j]
            for i = 2:nA-1
                C[i,j] = l[i-1]*B[i-1,j] + d[i]*B[i,j] + u[i]*B[i+1,j]
            end
            C[nA,j] = l[nA-1]*B[nA-1,j] + d[nA]*B[nA,j]
        end
    end
    C
end
*(A::Tridiagonal, B::AbstractVecOrMat) = A_mul_B!(similar(B), A, B)

A_ldiv_B!(A::Tridiagonal,B::AbstractVecOrMat) = A_ldiv_B!(lufact!(A), B)
At_ldiv_B!(A::Tridiagonal,B::AbstractVecOrMat) = At_ldiv_B!(lufact!(A), B)
Ac_ldiv_B!(A::Tridiagonal,B::AbstractVecOrMat) = Ac_ldiv_B!(lufact!(A), B)
