Sort diagonal eig values and standardize output types

docs/src/changelog.md

@@ -30,6 +30,8 @@ When releasing a new version, move the "Unreleased" changes to a new version sec
 
 ### Fixed
 
+- Eigenvalue decompositions of diagonal inputs are sorted and have the same type as non-diagonal inputs ([#151](https://github.com/QuantumKitHub/MatrixAlgebraKit.jl/pull/151)
+
 ## [0.6.2](https://github.com/QuantumKitHub/MatrixAlgebraKit.jl/compare/v0.6.1...v0.6.2) - 2026-01-08
 
 ### Added

src/implementations/eig.jl

@@ -30,23 +30,21 @@ end
 
 function check_input(::typeof(eig_full!), A::AbstractMatrix, DV, ::DiagonalAlgorithm)
     m, n = size(A)
-    @assert m == n && isdiag(A)
+    ((m == n) && isdiag(A)) || throw(DimensionMismatch("diagonal input matrix expected"))
     D, V = DV
-    @assert D isa Diagonal && V isa Diagonal
+    @assert D isa Diagonal && V isa AbstractMatrix
     @check_size(D, (m, m))
+    @check_scalar(D, A, complex)
     @check_size(V, (m, m))
-    # Diagonal doesn't need to promote to complex scalartype since we know it is diagonalizable
-    @check_scalar(D, A)
-    @check_scalar(V, A)
+    @check_scalar(V, A, complex)
     return nothing
 end
 function check_input(::typeof(eig_vals!), A::AbstractMatrix, D, ::DiagonalAlgorithm)
     m, n = size(A)
-    @assert m == n && isdiag(A)
+    ((m == n) && isdiag(A)) || throw(DimensionMismatch("diagonal input matrix expected"))
     @assert D isa AbstractVector
     @check_size(D, (n,))
-    # Diagonal doesn't need to promote to complex scalartype since we know it is diagonalizable
-    @check_scalar(D, A)
+    @check_scalar(D, A, complex)
     return nothing
 end
 
@@ -70,10 +68,14 @@ function initialize_output(::Union{typeof(eig_trunc!), typeof(eig_trunc_no_error
 end
 
 function initialize_output(::typeof(eig_full!), A::Diagonal, ::DiagonalAlgorithm)
-    return A, similar(A)
+    T = eltype(A)
+    Tc = complex(T)
+    D = T <: Complex ? A : Diagonal(similar(A, Tc, size(A, 1)))
+    return D, similar(A, Tc, size(A))
 end
 function initialize_output(::typeof(eig_vals!), A::Diagonal, ::DiagonalAlgorithm)
-    return diagview(A)
+    T = eltype(A)
+    return T <: Complex ? diagview(A) : similar(A, complex(T), size(A, 1))
 end
 
 # Implementation
@@ -129,17 +131,29 @@ end
 
 # Diagonal logic
 # --------------
-function eig_full!(A::Diagonal, (D, V)::Tuple{Diagonal, Diagonal}, alg::DiagonalAlgorithm)
-    check_input(eig_full!, A, (D, V), alg)
-    D === A || copy!(D, A)
-    one!(V)
+eig_sortby(x::T) where {T <: Number} = T <: Complex ? (real(x), imag(x)) : x
+function eig_full!(A::Diagonal, DV, alg::DiagonalAlgorithm)
+    check_input(eig_full!, A, DV, alg)
+    D, V = DV
+    diagA = diagview(A)
+    I = sortperm(diagA; by = eig_sortby)
+    if D === A
+        permute!(diagA, I)
+    else
+        diagview(D) .= view(diagA, I)
+    end
+    zero!(V)
+    n = size(A, 1)
+    I .+= (0:(n - 1)) .* n
+    V[I] .= Ref(one(eltype(V)))
     return D, V
 end
 
 function eig_vals!(A::Diagonal, D::AbstractVector, alg::DiagonalAlgorithm)
     check_input(eig_vals!, A, D, alg)
     Ad = diagview(A)
     D === Ad || copy!(D, Ad)
+    sort!(D; by = eig_sortby)
     return D
 end
 

test/testsuite/eig.jl

@@ -28,7 +28,7 @@ function test_eig_full(
     return @testset "eig_full! $summary_str" begin
         A = instantiate_matrix(T, sz)
         Ac = deepcopy(A)
-        Tc = isa(A, Diagonal) ? eltype(T) : complex(eltype(T))
+        Tc = complex(eltype(T))
         D, V = @testinferred eig_full(A)
         @test eltype(D) == eltype(V) == Tc
         @test A * V ≈ V * D
@@ -51,7 +51,7 @@ function test_eig_full_algs(
     return @testset "eig_full! algorithm $alg $summary_str" for alg in algs
         A = instantiate_matrix(T, sz)
         Ac = deepcopy(A)
-        Tc = isa(A, Diagonal) ? eltype(T) : complex(eltype(T))
+        Tc = complex(eltype(T))
         D, V = @testinferred eig_full(A; alg)
         @test eltype(D) == eltype(V) == Tc
         @test A * V ≈ V * D