add init kwarg to sum and prod as well (fix JuliaArrays#1119)

Author: thchr

src/mapreduce.jl

@@ -284,13 +284,13 @@ reduce(::typeof(hcat), A::StaticArray{<:Tuple,<:StaticVecOrMatLike}) =
 # TODO: change to use Base.reduce_empty/Base.reduce_first
 @inline iszero(a::StaticArray{<:Tuple,T}) where {T} = reduce((x,y) -> x && iszero(y), a, init=true)
 
-@inline sum(a::StaticArray{<:Tuple,T}; dims=:) where {T} = _reduce(+, a, dims)
-@inline sum(f, a::StaticArray{<:Tuple,T}; dims=:) where {T} = _mapreduce(f, +, dims, _InitialValue(), Size(a), a)
-@inline sum(f::Union{Function, Type}, a::StaticArray{<:Tuple,T}; dims=:) where {T} = _mapreduce(f, +, dims, _InitialValue(), Size(a), a) # avoid ambiguity
+@inline sum(a::StaticArray{<:Tuple,T}; dims=:, init=_IntialialValue()) where {T} = _reduce(+, a, dims, init)
+@inline sum(f, a::StaticArray{<:Tuple,T}; dims=:, init=_IntialialValue()) where {T} = _mapreduce(f, +, dims, init, Size(a), a)
+@inline sum(f::Union{Function, Type}, a::StaticArray{<:Tuple,T}; dims=:, init=_IntialialValue()) where {T} = _mapreduce(f, +, dims, init, Size(a), a) # avoid ambiguity
 
-@inline prod(a::StaticArray{<:Tuple,T}; dims=:) where {T} = _reduce(*, a, dims)
-@inline prod(f, a::StaticArray{<:Tuple,T}; dims=:) where {T} = _mapreduce(f, *, dims, _InitialValue(), Size(a), a)
-@inline prod(f::Union{Function, Type}, a::StaticArray{<:Tuple,T}; dims=:) where {T} = _mapreduce(f, *, dims, _InitialValue(), Size(a), a)
+@inline prod(a::StaticArray{<:Tuple,T}; dims=:, init=_IntialialValue()) where {T} = _reduce(*, a, dims, init)
+@inline prod(f, a::StaticArray{<:Tuple,T}; dims=:, init=_IntialialValue()) where {T} = _mapreduce(f, *, dims, init, Size(a), a)
+@inline prod(f::Union{Function, Type}, a::StaticArray{<:Tuple,T}; dims=:, init=_IntialialValue()) where {T} = _mapreduce(f, *, dims, init, Size(a), a)
 
 @inline count(a::StaticArray{<:Tuple,Bool}; dims=:, init=0) = _reduce(+, a, dims, init)
 @inline count(f, a::StaticArray; dims=:, init=0) = _mapreduce(x->f(x)::Bool, +, dims, init, Size(a), a)

test/mapreduce.jl

@@ -130,18 +130,22 @@ using Statistics: mean
         @test sum(sa, dims=Val(2)) === RSArray2(sum(a, dims=2))
         @test sum(abs2, sa; dims=2) === RSArray2(sum(abs2, a, dims=2))
         @test sum(abs2, sa; dims=Val(2)) === RSArray2(sum(abs2, a, dims=2))
+        @test sum(sa, init=2) == sum(a, init=2) == sum(sa) + 2
+        @test sum(sb, init=2) == sum(b, init=2) == sum(sb) + 2
 
         @test prod(sa) === prod(a)
         @test prod(abs2, sa) === prod(abs2, a)
         @test prod(sa, dims=Val(2)) === RSArray2(prod(a, dims=2))
         @test prod(abs2, sa, dims=Val(2)) === RSArray2(prod(abs2, a, dims=2))
+        @test prod(sa, init=2) == prod(a, init=2) == 2*prod(sa)
+        @test prod(sb, init=2) == prod(b, init=2) == 2*prod(sb)
 
         @test count(sb) === count(b)
-        @test count(sb, init=3) == count(b, init=3) == count(sb) + 3
         @test count(x->x>0, sa) === count(x->x>0, a)
-        @test count(x->x>0, sa, init=-2) == count(x->x>0, a, init=-2) == count(x->x>0, sa) - 2
         @test count(sb, dims=Val(2)) === RSArray2(reshape([count(b[i,:,k]) for i = 1:I, k = 1:K], (I,1,K)))
         @test count(x->x>0, sa, dims=Val(2)) === RSArray2(reshape([count(x->x>0, a[i,:,k]) for i = 1:I, k = 1:K], (I,1,K)))
+        @test count(sb, init=3) == count(b, init=3) == count(sb) + 3
+        @test count(x->x>0, sa, init=-2) == count(x->x>0, a, init=-2) == count(x->x>0, sa) - 2
 
         @test all(sb) === all(b)
         @test all(x->x>0, sa) === all(x->x>0, a)