Deprecate (cum)sum_kbn

This removes `sum_kbn` and `cumsum_kbn` in favor of `sum` and `cumsum`,
respectively, with the `*_kbn` functions moving to a package.

Fixes #24804

base/abstractarraymath.jl

@@ -238,73 +238,6 @@ function circshift(a::AbstractArray, shiftamt)
     circshift!(similar(a), a, map(Integer, (shiftamt...,)))
 end
 
-# Uses K-B-N summation
-function cumsum_kbn(v::AbstractVector{T}) where T<:AbstractFloat
-    r = similar(v)
-    if isempty(v); return r; end
-
-    inds = indices(v, 1)
-    i1 = first(inds)
-    s = r[i1] = v[i1]
-    c = zero(T)
-    for i=i1+1:last(inds)
-        vi = v[i]
-        t = s + vi
-        if abs(s) >= abs(vi)
-            c += ((s-t) + vi)
-        else
-            c += ((vi-t) + s)
-        end
-        s = t
-        r[i] = s+c
-    end
-    return r
-end
-
-# Uses K-B-N summation
-# TODO: Needs a separate IndexCartesian method, this is only fast for IndexLinear
-
-"""
-    cumsum_kbn(A, dim::Integer)
-
-Cumulative sum along a dimension, using the Kahan-Babuska-Neumaier compensated summation
-algorithm for additional accuracy.
-"""
-function cumsum_kbn(A::AbstractArray{T}, axis::Integer) where T<:AbstractFloat
-    dimsA = size(A)
-    ndimsA = ndims(A)
-    axis_size = dimsA[axis]
-    axis_stride = 1
-    for i = 1:(axis-1)
-        axis_stride *= size(A,i)
-    end
-
-    if axis_size <= 1
-        return A
-    end
-
-    B = similar(A)
-    C = similar(A)
-
-    for i = 1:length(A)
-        if div(i-1, axis_stride) % axis_size == 0
-            B[i] = A[i]
-            C[i] = zero(T)
-        else
-            s = B[i-axis_stride]
-            Ai = A[i]
-            B[i] = t = s + Ai
-            if abs(s) >= abs(Ai)
-                C[i] = C[i-axis_stride] + ((s-t) + Ai)
-            else
-                C[i] = C[i-axis_stride] + ((Ai-t) + s)
-            end
-        end
-    end
-
-    return B + C
-end
-
 ## Other array functions ##
 
 """

base/deprecated.jl

@@ -2136,7 +2136,6 @@ end
 @deprecate RowVector{T}(n::Tuple{Int,Int}) where {T}    RowVector{T}(uninitialized, n)
 
 @deprecate cumsum(A::AbstractArray)     cumsum(A, 1)
-@deprecate cumsum_kbn(A::AbstractArray) cumsum_kbn(A, 1)
 @deprecate cumprod(A::AbstractArray)    cumprod(A, 1)
 
 # issue #16307
@@ -2183,6 +2182,10 @@ end
     @deprecate SSHCredentials SSHCredential false
 end
 
+# issue #24804
+@deprecate_moved sum_kbn "KahanSummation"
+@deprecate_moved cumsum_kbn "KahanSummation"
+
 # END 0.7 deprecations
 
 # BEGIN 1.0 deprecations

base/exports.jl

@@ -433,7 +433,6 @@ export
     cumsum!,
     accumulate,
     accumulate!,
-    cumsum_kbn,
     eachindex,
     extrema,
     fill!,
@@ -527,7 +526,6 @@ export
     sub2ind,
     sum!,
     sum,
-    sum_kbn,
     to_indices,
     vcat,
     vec,

base/reduce.jl

@@ -391,38 +391,6 @@ julia> sum(1:20)
 sum(a) = mapreduce(promote_sys_size_add, +, a)
 sum(a::AbstractArray{Bool}) = count(a)
 
-
-# Kahan (compensated) summation: O(1) error growth, at the expense
-# of a considerable increase in computational expense.
-
-"""
-    sum_kbn(A)
-
-Returns the sum of all elements of `A`, using the Kahan-Babuska-Neumaier compensated
-summation algorithm for additional accuracy.
-"""
-function sum_kbn(A)
-    T = @default_eltype(typeof(A))
-    c = promote_sys_size_add(zero(T)::T)
-    i = start(A)
-    if done(A, i)
-        return c
-    end
-    Ai, i = next(A, i)
-    s = Ai - c
-    while !(done(A, i))
-        Ai, i = next(A, i)
-        t = s + Ai
-        if abs(s) >= abs(Ai)
-            c -= ((s-t) + Ai)
-        else
-            c -= ((Ai-t) + s)
-        end
-        s = t
-    end
-    s - c
-end
-
 ## prod
 """
     prod(f, itr)

doc/src/manual/style-guide.md

@@ -159,7 +159,7 @@ uses (e.g. `a[i]::Int`) than to try to pack many alternatives into one type.
   * functions are lowercase ([`maximum`](@ref), [`convert`](@ref)) and, when readable, with multiple
     words squashed together ([`isequal`](@ref), [`haskey`](@ref)). When necessary, use underscores
     as word separators. Underscores are also used to indicate a combination of concepts ([`remotecall_fetch`](@ref)
-    as a more efficient implementation of `fetch(remotecall(...))`) or as modifiers ([`sum_kbn`](@ref)).
+    as a more efficient implementation of `fetch(remotecall(...))`) or as modifiers.
   * conciseness is valued, but avoid abbreviation ([`indexin`](@ref) rather than `indxin`) as
     it becomes difficult to remember whether and how particular words are abbreviated.
 

doc/src/stdlib/arrays.md

@@ -147,7 +147,6 @@ Base.cumprod
 Base.cumprod!
 Base.cumsum
 Base.cumsum!
-Base.cumsum_kbn
 Base.LinAlg.diff
 Base.repeat(::AbstractArray)
 Base.rot180
@@ -156,7 +155,6 @@ Base.rotr90
 Base.reducedim
 Base.mapreducedim
 Base.mapslices
-Base.sum_kbn
 ```
 
 ## Combinatorics

test/arrayops.jl

@@ -870,29 +870,6 @@ end
         @test c[2,2] == A[3,1]+A[3,3]
     end
 
-    v   = [1,1e100,1,-1e100]*1000
-    v2  = [1,-1e100,1,1e100]*1000
-
-    cv  = [1,1e100,1e100,2]*1000
-    cv2 = [1,-1e100,-1e100,2]*1000
-
-    @test isequal(cumsum_kbn(v), cv)
-    @test isequal(cumsum_kbn(v2), cv2)
-
-    A = [v reverse(v) v2 reverse(v2)]
-
-    c = cumsum_kbn(A, 1)
-
-    @test isequal(c[:,1], cv)
-    @test isequal(c[:,3], cv2)
-    @test isequal(c[4,:], [2.0, 2.0, 2.0, 2.0]*1000)
-
-    c = cumsum_kbn(A, 2)
-
-    @test isequal(c[1,:], cv2)
-    @test isequal(c[3,:], cv)
-    @test isequal(c[:,4], [2.0,2.0,2.0,2.0]*1000)
-
     @test repeat(BitMatrix(Matrix(I, 2, 2)), inner = (2,1), outer = (1,2)) ==
             repeat(Matrix(I, 2, 2), inner = (2,1), outer = (1,2))
 end

test/offsetarray.jl

@@ -383,14 +383,20 @@ I,J,N = findnz(z)
 @test vecnorm(A) ≈ vecnorm(parent(A))
 @test vecdot(v, v) ≈ vecdot(v0, v0)
 
-v  = OffsetArray([1,1e100,1,-1e100], (-3,))*1000
-v2 = OffsetArray([1,-1e100,1,1e100], (5,))*1000
-@test isa(v, OffsetArray)
-cv  = OffsetArray([1,1e100,1e100,2], (-3,))*1000
-cv2 = OffsetArray([1,-1e100,-1e100,2], (5,))*1000
-@test isequal(cumsum_kbn(v), cv)
-@test isequal(cumsum_kbn(v2), cv2)
-@test isequal(sum_kbn(v), sum_kbn(parent(v)))
+# Prior to its removal from Base, cumsum_kbn was used here. To achieve the same level of
+# accuracy in the tests, we need to use BigFloats with enlarged precision.
+@testset "high-precision array reduction" begin
+    setprecision(BigFloat, 500) do
+        v  = OffsetArray(BigFloat[1,1e100,1,-1e100], (-3,)) .* 1000
+        v2 = OffsetArray(BigFloat[1,-1e100,1,1e100], ( 5,)) .* 1000
+        @test isa(v, OffsetArray)
+        cv  = OffsetArray(BigFloat[1, 1e100, 1e100,2], (-3,)) .* 1000
+        cv2 = OffsetArray(BigFloat[1,-1e100,-1e100,2], ( 5,)) .* 1000
+        @test cumsum(v) ≈ cv
+        @test cumsum(v2) ≈ cv2
+        @test sum(v) ≈ sum(parent(v))
+    end
+end
 
 io = IOBuffer()
 writedlm(io, A)

test/reduce.jl

@@ -135,18 +135,6 @@ for f in (sum3, sum4, sum7, sum8)
 end
 @test typeof(sum(Int8[])) == typeof(sum(Int8[1])) == typeof(sum(Int8[1 7]))
 
-@test sum_kbn([1,1e100,1,-1e100]) === 2.0
-@test sum_kbn(Float64[]) === 0.0
-@test sum_kbn(i for i=1.0:1.0:10.0) === 55.0
-@test sum_kbn(i for i=1:1:10) === 55
-@test sum_kbn([1 2 3]) === 6
-@test sum_kbn([2+im 3-im]) === 5+0im
-@test sum_kbn([1+im 2+3im]) === 3+4im
-@test sum_kbn([7 8 9]) === sum_kbn([8 9 7])
-@test sum_kbn(i for i=1:1:10) === sum_kbn(i for i=10:-1:1)
-@test sum_kbn([-0.0]) === -0.0
-@test sum_kbn([-0.0,-0.0]) === -0.0
-
 # check sum(abs, ...) for support of empty collections
 @testset "sum(abs, [])" begin
     @test @inferred(sum(abs, Float64[])) === 0.0
@@ -362,14 +350,13 @@ end
 ## cumsum, cummin, cummax
 
 z = rand(10^6)
-let es = sum_kbn(z), es2 = sum_kbn(z[1:10^5])
+let es = sum(BigFloat.(z)), es2 = sum(BigFloat.(z[1:10^5]))
     @test (es - sum(z)) < es * 1e-13
     cs = cumsum(z)
     @test (es - cs[end]) < es * 1e-13
     @test (es2 - cs[10^5]) < es2 * 1e-13
 end
 
-
 @test sum(collect(map(UInt8,0:255))) == 32640
 @test sum(collect(map(UInt8,254:255))) == 509