no sortby for special matrix types

JuliaLang · stevengj · Feb 5, 2019 · Jan 10, 2019 · Jan 10, 2019 · Jan 10, 2019
commit c49310060996510df0e4a347c5ff48013eca0652
diff --git a/stdlib/LinearAlgebra/src/bidiag.jl b/stdlib/LinearAlgebra/src/bidiag.jl
@@ -690,8 +690,8 @@ end
 factorize(A::Bidiagonal) = A
 
 # Eigensystems
-eigvals(M::Bidiagonal; sortby::Union{Function,Nothing}=eigsortby) = sortby===nothing ? M.dv : sort(M.dv, by=sortby)
-function eigvecs_(M::Bidiagonal{T}) where T # non-sorted
+eigvals(M::Bidiagonal) = M.dv
+function eigvecs(M::Bidiagonal{T}) where T
     n = length(M.dv)
     Q = Matrix{T}(undef, n,n)
     blks = [0; findall(x -> x == 0, M.ev); n]
@@ -723,6 +723,4 @@ function eigvecs_(M::Bidiagonal{T}) where T # non-sorted
     end
     Q #Actually Triangular
 end
-eigvecs(M::Bidiagonal{T}; sortby::Union{Function,Nothing}=eigsortby) =
-    sorteigvecs!(M.dv, eigvecs_(M), sortby)
-eigen(M::Bidiagonal) = Eigen(sorteig!(copy(M.dv), eigvecs_(M), sortby)...)
+eigen(M::Bidiagonal) = Eigen(eigvals(M), eigvecs(M))
diff --git a/stdlib/LinearAlgebra/src/diagonal.jl b/stdlib/LinearAlgebra/src/diagonal.jl
@@ -524,16 +524,15 @@ function pinv(D::Diagonal{T}, tol::Real) where T
 end
 
 #Eigensystem
-eigvals(D::Diagonal{<:Number}; permute::Bool=true, scale::Bool=true, sortby::Union{Function,Nothing}=eigsortby) = sortby === nothing ? D.diag : sort(D.diag, by=sortby)
-eigvals_(D::Diagonal) = [eigvals(x) for x in D.diag] # non-sorted copy, for block matrices etc.
-eigvals(D::Diagonal; permute::Bool=true, scale::Bool=true, sortby::Union{Function,Nothing}=eigsortby) =
-    sorteigvals!(eigvals_(D), sortby)
-eigvecs(D::Diagonal; sortby::Union{Function,Nothing}=eigsortby) = sorteigvecs!(D.diag, Matrix{eltype(D)}(I, size(D)), sortby)
-function eigen(D::Diagonal; permute::Bool=true, scale::Bool=true, sortby::Union{Function,Nothing}=eigsortby)
+eigvals(D::Diagonal{<:Number}; permute::Bool=true, scale::Bool=true) = D.diag
+eigvals(D::Diagonal; permute::Bool=true, scale::Bool=true) =
+    [eigvals(x) for x in D.diag] #For block matrices, etc.
+eigvecs(D::Diagonal) = Matrix{eltype(D)}(I, size(D))
+function eigen(D::Diagonal; permute::Bool=true, scale::Bool=true)
     if any(!isfinite, D.diag)
         throw(ArgumentError("matrix contains Infs or NaNs"))
     end
-    Eigen(sorteig!(eigvals_(D), Matrix{eltype(D)}(I, size(D)))...)
+    Eigen(eigvals(D), eigvecs(D))
 end
 
 #Singular system

diff --git a/stdlib/LinearAlgebra/src/eigen.jl b/stdlib/LinearAlgebra/src/eigen.jl
@@ -103,7 +103,9 @@ make rows and columns more equal in norm. The default is `true` for both options
 
 By default, the eigenvalues and vectors are sorted lexicographically by `(real(λ),imag(λ))`.
 A different comparison function `by(λ)` can be passed to `sortby`, or you can pass
-`sortby=nothing` to leave the eigenvalues in an arbitrary order.
+`sortby=nothing` to leave the eigenvalues in an arbitrary order.   Some special matrix types
+(e.g. `Diagonal` or `SymTridiagonal`) may implement their own sorting convention and not
+accept a `sortby` keyword.
 
 # Examples
 ```jldoctest
@@ -372,7 +374,8 @@ Iterating the decomposition produces the components `F.values` and `F.vectors`.
 
 By default, the eigenvalues and vectors are sorted lexicographically by `(real(λ),imag(λ))`.
 A different comparison function `by(λ)` can be passed to `sortby`, or you can pass
-`sortby=nothing` to leave the eigenvalues in an arbitrary order.
+`sortby=nothing` to leave the eigenvalues in an arbitrary order.   Some special matrix types
+may implement their own sorting convention and not accept a `sortby` keyword.
 
 # Examples
 ```jldoctest