Support inv on diagonal matrices from unitranges (#177)

* Support inv on diagonal matrices from unitranges

* Don't use == on entire matrix

* Check for singular exception

Project.toml

@@ -1,6 +1,6 @@
 name = "InfiniteArrays"
 uuid = "4858937d-0d70-526a-a4dd-2d5cb5dd786c"
-version = "0.14"
+version = "0.14.1"
 
 [deps]
 ArrayLayouts = "4c555306-a7a7-4459-81d9-ec55ddd5c99a"

src/InfiniteArrays.jl

@@ -8,7 +8,7 @@ import Base: *, +, -, /, <, ==, >, \, ≤, ≥, (:), @propagate_inbounds,
              angle, axes, broadcast, cat_indices,
              cat_similar, cat_size, checkindex, collect, convert, copy,
              cumsum, dataids, diff, div, eltype, fill, findfirst, first, floatrange, getindex, hcat,
-             in, ind2sub_rs, intersect, isempty, isinf, issorted, last, length, lt, max,
+             in, ind2sub_rs, intersect, inv, isempty, isinf, issorted, last, length, lt, max,
              maximum, minimum, mod, one, ones, parent, parentindices, permutedims, print_matrix, print_matrix_row,
              print_matrix_vdots, promote_rule, reinterpret, reshape, reverse, searchsorted,
              searchsortedfirst, searchsortedlast, setindex!, show, show_circular, show_delim_array, sign,

src/infrange.jl

@@ -617,3 +617,10 @@ function LinearAlgebra.diag(D::Diagonal{<:Any,<:InfRanges}, k::Integer = 0)
         return Zeros{eltype(D)}(size(D,1)) # infinite vector of zeros
     end
 end
+
+function inv(D::Diagonal{T, <:InfRanges}) where {T} 
+    d = D.diag 
+    idx = findfirst(==(zero(T)), d) 
+    isnothing(idx) || throw(SingularException(idx))
+    return Diagonal(inv.(d))
+end

test/runtests.jl

@@ -1206,6 +1206,8 @@ end
     @test @inferred((D -> diag(D,1))(D)) === Zeros{Int}(ℵ₀)
     # test for compile-time evaluation of off-diagonals
     @inferred Val((D -> diag(D,1))(D))
+    # Issue #176 
+    @test inv(D)[1:100,1:100] == Diagonal(inv.(1:∞))[1:100,1:100]
 end
 
 @testset "inf padded" begin