Adjust mapreduce to use first element in offset range as well.

Adjust tests

Author: andreasnoack

base/abstractarray.jl

@@ -1917,7 +1917,9 @@ function mapslices(f, A::AbstractArray; dims)
     Rsize = copy(dimsA)
     # TODO: maybe support removing dimensions
     if !isa(r1, AbstractArray) || ndims(r1) == 0
-        r1 = [r1]
+        tmp = similar(Aslice, typeof(r1), reduced_indices(Aslice, 1:ndims(Aslice)))
+        tmp[first(CartesianIndices(tmp))] = r1
+        r1 = tmp
     end
     nextra = max(0, length(dims)-ndims(r1))
     if eltype(Rsize) == Int

base/reducedim.jl

@@ -17,23 +17,27 @@ reduced_indices(a::AbstractArray, region) = reduced_indices(axes(a), region)
 # for reductions that keep 0 dims as 0
 reduced_indices0(a::AbstractArray, region) = reduced_indices0(axes(a), region)
 
-function reduced_indices(inds::Indices{N}, d::Int, rd::AbstractUnitRange) where N
+function reduced_indices(inds::Indices{N}, d::Int) where N
     d < 1 && throw(ArgumentError("dimension must be ≥ 1, got $d"))
     if d == 1
-        return (oftype(inds[1], rd), tail(inds)...)
+        return (reduced_index(inds[1]), tail(inds)...)
     elseif 1 < d <= N
-        return tuple(inds[1:d-1]..., oftype(inds[d], rd), inds[d+1:N]...)::typeof(inds)
+        return tuple(inds[1:d-1]..., oftype(inds[d], reduced_index(inds[d])), inds[d+1:N]...)::typeof(inds)
     else
         return inds
     end
 end
-reduced_indices(inds::Indices, d::Int) = reduced_indices(inds, d, reduced_index(inds[d]))
 
 function reduced_indices0(inds::Indices{N}, d::Int) where N
     d < 1 && throw(ArgumentError("dimension must be ≥ 1, got $d"))
     if d <= N
         ind = inds[d]
-        return reduced_indices(inds, d, (isempty(ind) ? ind : reduced_index(inds[d])))
+        rd = isempty(ind) ? ind : reduced_index(inds[d])
+        if d == 1
+            return (rd, tail(inds)...)
+        else
+            return tuple(inds[1:d-1]..., oftype(inds[d], rd), inds[d+1:N]...)::typeof(inds)
+        end
     else
         return inds
     end

test/offsetarray.jl

@@ -339,9 +339,9 @@ A = OffsetArray(rand(4,4), (-3,5))
 @test maximum(A) == maximum(parent(A))
 @test minimum(A) == minimum(parent(A))
 @test extrema(A) == extrema(parent(A))
-@test maximum(A, dims=1) == OffsetArray(maximum(parent(A), dims=1), (0,A.offsets[2]))
-@test maximum(A, dims=2) == OffsetArray(maximum(parent(A), dims=2), (A.offsets[1],0))
-@test maximum(A, dims=1:2) == maximum(parent(A), dims=1:2)
+@test maximum(A, dims=1) == OffsetArray(maximum(parent(A), dims=1), A.offsets)
+@test maximum(A, dims=2) == OffsetArray(maximum(parent(A), dims=2), A.offsets)
+@test maximum(A, dims=1:2) == OffsetArray(maximum(parent(A), dims=1:2), A.offsets)
 C = similar(A)
 cumsum!(C, A, dims=1)
 @test parent(C) == cumsum(parent(A), dims=1)
@@ -373,11 +373,11 @@ I = findall(!iszero, z)
 @test findall(x->x==0, h) == [2]
 @test mean(A_3_3) == median(A_3_3) == 5
 @test mean(x->2x, A_3_3) == 10
-@test mean(A_3_3, dims=1) == median(A_3_3, dims=1) == OffsetArray([2 5 8], (0,A_3_3.offsets[2]))
-@test mean(A_3_3, dims=2) == median(A_3_3, dims=2) == OffsetArray(reshape([4,5,6],(3,1)), (A_3_3.offsets[1],0))
+@test mean(A_3_3, dims=1) == median(A_3_3, dims=1) == OffsetArray([2 5 8], A_3_3.offsets)
+@test mean(A_3_3, dims=2) == median(A_3_3, dims=2) == OffsetArray(reshape([4,5,6],(3,1)), A_3_3.offsets)
 @test var(A_3_3) == 7.5
-@test std(A_3_3, dims=1) == OffsetArray([1 1 1], (0,A_3_3.offsets[2]))
-@test std(A_3_3, dims=2) == OffsetArray(reshape([3,3,3], (3,1)), (A_3_3.offsets[1],0))
+@test std(A_3_3, dims=1) == OffsetArray([1 1 1], A_3_3.offsets)
+@test std(A_3_3, dims=2) == OffsetArray(reshape([3,3,3], (3,1)), A_3_3.offsets)
 @test sum(OffsetArray(fill(1,3000), -1000)) == 3000
 
 @test norm(v) ≈ norm(parent(v))