specialize sum for FillArrays

[jishnub]

The specialized sum was removed in #181, relying on the specialized mapreduce instead. While this is fine for finite-sized arrays, it doesn't seem to work for infinite arrays. This PR reverts that change. With sum specialized, the following works in O(1) time again:

julia> using FillArrays, InfiniteArrays

julia> A = Ones((InfiniteArrays.OneToInf(),))
ℵ₀-element Ones{Float64, 1, Tuple{InfiniteArrays.OneToInf{Int64}}} with indices OneToInf()

julia> @time sum(A)
  0.000006 seconds
+∞

Ideally, we would be able to get mapreduce to work for infinite arrays, but this should avoid breaking code meanwhile.

[codecov]

Codecov Report

Merging #182 (4516ab6) into master (6ed6ec5) will increase coverage by 0.00%.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master     #182   +/-   ##
=======================================
  Coverage   96.95%   96.96%           
=======================================
  Files           4        4           
  Lines         657      659    +2     
=======================================
+ Hits          637      639    +2     
  Misses         20       20           

Impacted Files	Coverage Δ
src/FillArrays.jl	95.60% <100.00%> (+0.02%)	⬆️

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[jishnub]

Gentle bump @dlfivefifty. This is a bugfix and restores previous behaviour, so would be good to have this merged soon. The CI for ApproxFun has been broken by this change.

[dlfivefifty]

I'm a bit worried about depending on packages which depend on this package....couldn't we just implement a simple version of OneToInf in the tests?

You could use the version in Base:

https://github.com/JuliaLang/julia/blob/master/test/testhelpers/InfiniteArrays.jl

[jishnub]

I've updated this now as suggested. I don't think the dependency resolution should be an issue, as the test environment will dev this package, which will ensure the same version downstream. However, I do agree that adding a test dependency is unnecessary in this case.