Fix linear indexing of one-dimensional CartesianIndices (#28401)

The distinction between the values and the axes can be tricky

base/indices.jl

@@ -390,11 +390,11 @@ function getindex(iter::LinearIndices, i::AbstractRange{<:Integer})
 end
 # More efficient iteration — predominantly for non-vector LinearIndices
 # but one-dimensional LinearIndices must be special-cased to support OffsetArrays
-iterate(iter::LinearIndices{1}, s...) = iterate(iter.indices[1], s...)
+iterate(iter::LinearIndices{1}, s...) = iterate(axes1(iter.indices[1]), s...)
 iterate(iter::LinearIndices, i=1) = i > length(iter) ? nothing : (i, i+1)
 
 # Needed since firstindex and lastindex are defined in terms of LinearIndices
 first(iter::LinearIndices) = 1
-first(iter::LinearIndices{1}) = (@_inline_meta; first(iter.indices[1]))
+first(iter::LinearIndices{1}) = (@_inline_meta; first(axes1(iter.indices[1])))
 last(iter::LinearIndices) = (@_inline_meta; length(iter))
-last(iter::LinearIndices{1}) = (@_inline_meta; last(iter.indices[1]))
+last(iter::LinearIndices{1}) = (@_inline_meta; last(axes1(iter.indices[1])))

test/abstractarray.jl

@@ -145,6 +145,17 @@ end
  # indices may be nontraditional
  @test_throws ArgumentError Base._sub2ind((1:3,), 2)
  @test_throws ArgumentError Base._ind2sub((1:3,), 2)
+
+ ci = CartesianIndices((2:4,))
+ @test first(ci) == ci[1] == CartesianIndex(2)
+ @test last(ci) == ci[end] == ci[3] == CartesianIndex(4)
+ li = LinearIndices(ci)
+ @test collect(li) == [1,2,3]
+ @test first(li) == li[1] == 1
+ @test last(li) == li[3] == 3
+ io = IOBuffer()
+ show(io, ci)
+ @test String(take!(io)) == "CartesianIndex{1}[CartesianIndex(2,), CartesianIndex(3,), CartesianIndex(4,)]"
  end
 
  @testset "2-dimensional" begin