Delete uses of FillArrays

Author: mtfishman

src/KroneckerArrays.jl

@@ -158,6 +158,8 @@ end
 
 arguments(a::KroneckerArray) = (a.a, a.b)
 arguments(a::KroneckerArray, n::Int) = arguments(a)[n]
+argument_types(a::KroneckerArray) = argument_types(typeof(a))
+argument_types(::Type{<:KroneckerArray{<:Any,<:Any,A,B}}) where {A,B} = (A, B)
 
 function Base.print_array(io::IO, a::KroneckerArray)
   Base.print_array(io, a.a)
@@ -609,12 +611,26 @@ end
 for f in (:eig, :eigh, :lq, :qr, :polar, :svd)
   ff = Symbol("default_", f, "_algorithm")
   @eval begin
-    function MatrixAlgebraKit.$ff(a::KroneckerMatrix; kwargs...)
-      return KroneckerAlgorithm($ff(a.a; kwargs...), $ff(a.b; kwargs...))
+    function MatrixAlgebraKit.$ff(A::Type{<:KroneckerMatrix}; kwargs...)
+      A1, A2 = argument_types(A)
+      return KroneckerAlgorithm($ff(A1; kwargs...), $ff(A2; kwargs...))
     end
   end
 end
 
+# TODO: Delete this once https://github.com/QuantumKitHub/MatrixAlgebraKit.jl/pull/32 is merged.
+function MatrixAlgebraKit.default_algorithm(
+  ::typeof(qr_compact!), A::Type{<:KroneckerMatrix}; kwargs...
+)
+  return default_qr_algorithm(A; kwargs...)
+end
+# TODO: Delete this once https://github.com/QuantumKitHub/MatrixAlgebraKit.jl/pull/32 is merged.
+function MatrixAlgebraKit.default_algorithm(
+  ::typeof(qr_full!), A::Type{<:KroneckerMatrix}; kwargs...
+)
+  return default_qr_algorithm(A; kwargs...)
+end
+
 for f in (
   :eig_full!,
   :eigh_full!,
@@ -689,75 +705,4 @@ for f in (:left_null!, :right_null!)
   end
 end
 
-# Special case for `FillArrays.Eye` matrices.
-struct EyeAlgorithm <: AbstractAlgorithm end
-
-for f in [
-  :eig_full,
-  :eigh_full,
-  :qr_compact,
-  :qr_full,
-  :left_polar,
-  :lq_compact,
-  :lq_full,
-  :right_polar,
-  :svd_compact,
-  :svd_full,
-]
-  @eval begin
-    MatrixAlgebraKit.copy_input(::typeof($f), a::Eye) = a
-  end
-end
-
-for f in (:eig, :eigh, :lq, :qr, :polar, :svd)
-  ff = Symbol("default_", f, "_algorithm")
-  @eval begin
-    function MatrixAlgebraKit.$ff(a::Eye; kwargs...)
-      return EyeAlgorithm()
-    end
-  end
-end
-
-for f in (
-  :eig_full!,
-  :eigh_full!,
-  :qr_compact!,
-  :qr_full!,
-  :left_polar!,
-  :lq_compact!,
-  :lq_full!,
-  :right_polar!,
-)
-  @eval begin
-    nfactors(::typeof($f)) = 2
-  end
-end
-for f in (:svd_compact!, :svd_full!)
-  @eval begin
-    nfactors(::typeof($f)) = 3
-  end
-end
-
-for f in (
-  :eig_full!,
-  :eigh_full!,
-  :qr_compact!,
-  :qr_full!,
-  :left_polar!,
-  :lq_compact!,
-  :lq_full!,
-  :right_polar!,
-  :svd_compact!,
-  :svd_full!,
-)
-  @eval begin
-    function MatrixAlgebraKit.initialize_output(::typeof($f), a::Eye, alg::EyeAlgorithm)
-      return ntuple(_ -> a, nfactors($f))
-    end
-    function MatrixAlgebraKit.$f(a::Eye, F, alg::EyeAlgorithm; kwargs...)
-      return ntuple(_ -> a, nfactors($f))
-    end
-  end
-end
-
 end

test/Project.toml

@@ -1,6 +1,5 @@
 [deps]
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
-FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
 KroneckerArrays = "05d0b138-81bc-4ff7-84be-08becefb1ccc"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MatrixAlgebraKit = "6c742aac-3347-4629-af66-fc926824e5e4"
@@ -10,7 +9,6 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]
 Aqua = "0.8"
-FillArrays = "1"
 KroneckerArrays = "0.1"
 LinearAlgebra = "1.10"
 MatrixAlgebraKit = "0.2"

test/test_matrixalgebrakit.jl

@@ -1,4 +1,3 @@
-using FillArrays: Eye
 using KroneckerArrays: ⊗
 using LinearAlgebra: Hermitian, I, diag, hermitianpart, norm
 using MatrixAlgebraKit:
@@ -33,11 +32,6 @@ herm(a) = hermitianpart(a).data
   d, v = eig_full(a)
   @test a * v ≈ v * d
 
-  a = randn(elt, 2, 2) ⊗ Eye(3)
-  d, v = eig_full(a)
-  @test d.b == v.b == Eye(3)
-  @test a * v ≈ v * d
-
   a = randn(elt, 2, 2) ⊗ randn(elt, 3, 3)
   @test_throws MethodError eig_trunc(a)
 
@@ -110,11 +104,6 @@ herm(a) = hermitianpart(a).data
   @test collect(u'u) ≈ I
   @test collect(v * v') ≈ I
 
-  a = randn(elt, 2, 2) ⊗ Eye(3)
-  u, s, v = svd_compact(a)
-  @test u * s * v ≈ a
-  @test u.b == s.b == v.b == Eye(3)
-
   a = randn(elt, 2, 2) ⊗ randn(elt, 3, 3)
   u, s, v = svd_full(a)
   @test u * s * v ≈ a