diff --git a/base/multidimensional.jl b/base/multidimensional.jl index a37211f367f5eb..3328fa0e4cffb6 100644 --- a/base/multidimensional.jl +++ b/base/multidimensional.jl @@ -719,6 +719,27 @@ function cumsum(A::AbstractArray{T}, axis::Integer) where T cumsum!(out, A, axis) end +""" + cumsum(x::AbstractVector) + +Cumulative sum a vector. See also [`cumsum!`](@ref) +to use a preallocated output array, both for performance and to control the precision of the +output (e.g. to avoid overflow). + +```jldoctest +julia> cumsum([1, 1, 1]) +3-element Array{Int64,1}: + 1 + 2 + 3 + +julia> cumsum([fill(1, 2) for i in 1:3]) +3-element Array{Array{Int64,1},1}: + [1, 1] + [2, 2] + [3, 3] +``` +""" cumsum(x::AbstractVector) = cumsum(x, 1) """ @@ -728,6 +749,11 @@ Cumulative sum of `A` along a dimension, storing the result in `B`. See also [`c """ cumsum!(B, A, axis::Integer) = accumulate!(+, B, A, axis) +""" + cumsum!(y::AbstractVector, x::AbstractVector) + +Cumulative sum of a vector `x`, storing the result in `y`. See also [`cumsum`](@ref). +""" cumsum!(y::AbstractVector, x::AbstractVector) = cumsum!(y, x, 1) """ @@ -756,6 +782,27 @@ julia> cumprod(a,2) """ cumprod(A::AbstractArray, axis::Integer) = accumulate(*, A, axis) +""" + cumprod(x::AbstractVector) + +Cumulative product of a vector. See also +[`cumprod!`](@ref) to use a preallocated output array, both for performance and +to control the precision of the output (e.g. to avoid overflow). + +```jldoctest +julia> cumprod(fill(1//2, 3)) +3-element Array{Rational{Int64},1}: + 1//2 + 1//4 + 1//8 + +julia> cumprod([fill(1//3, 2, 2) for i in 1:3]) +3-element Array{Array{Rational{Int64},2},1}: + Rational{Int64}[1//3 1//3; 1//3 1//3] + Rational{Int64}[2//9 2//9; 2//9 2//9] + Rational{Int64}[4//27 4//27; 4//27 4//27] +``` +""" cumprod(x::AbstractVector) = cumprod(x, 1) """ @@ -766,6 +813,12 @@ See also [`cumprod`](@ref). """ cumprod!(B, A, axis::Integer) = accumulate!(*, B, A, axis) +""" + cumprod!(y::AbstractVector, x::AbstractVector) + +Cumulative product of a vector `x`, storing the result in `y`. +See also [`cumprod`](@ref). +""" cumprod!(y::AbstractVector, x::AbstractVector) = cumprod!(y, x, 1) """ @@ -778,17 +831,17 @@ there are specialized variants of `accumulate`, see: [`cumsum`](@ref), [`cumprod`](@ref) ```jldoctest -julia> accumulate(+, [1,2,3]) -3-element Array{Int64,1}: - 1 - 3 - 6 - -julia> accumulate(*, [1,2,3]) -3-element Array{Int64,1}: - 1 - 2 - 6 +julia> accumulate(+, fill(1, 3, 3), 1) +3×3 Array{Int64,2}: + 1 1 1 + 2 2 2 + 3 3 3 + +julia> accumulate(+, fill(1, 3, 3), 2) +3×3 Array{Int64,2}: + 1 2 3 + 1 2 3 + 1 2 3 ``` """ function accumulate(op, A, axis::Integer) @@ -796,65 +849,30 @@ function accumulate(op, A, axis::Integer) accumulate!(op, out, A, axis) end -accumulate(op, x::AbstractVector) = accumulate(op, x, 1) - """ - accumulate(op, v0, A) + accumulate(op, x::AbstractVector) -Like `accumulate`, but using a starting element `v0`. The first entry of the result will be -`op(v0, first(A))`. +Cumulative operation `op` on a vector. See also +[`accumulate!`](@ref) to use a preallocated output array, both for performance and +to control the precision of the output (e.g. to avoid overflow). For common operations +there are specialized variants of `accumulate`, see: +[`cumsum`](@ref), [`cumprod`](@ref) -# Examples ```jldoctest -julia> accumulate(+, 100, [1,2,3]) +julia> accumulate(+, [1,2,3]) 3-element Array{Int64,1}: - 101 - 103 - 106 + 1 + 3 + 6 -julia> accumulate(min, 0, [1,2,-1]) +julia> accumulate(*, [1,2,3]) 3-element Array{Int64,1}: - 0 - 0 - -1 + 1 + 2 + 6 ``` """ -function accumulate(op, v0, A, axis::Integer) - T = rcum_promote_type(op, typeof(v0), eltype(A)) - out = similar(A, T) - accumulate!(op, out, v0, A, 1) -end - -accumulate(op, v0, x::AbstractVector) = accumulate(op, v0, x, 1) - -function accumulate!(op::Op, B, A::AbstractVector, axis::Integer) where Op - isempty(A) && return B - v1 = first(A) - _accumulate1!(op, B, v1, A, axis) -end - -function accumulate!(op, B, v0, A::AbstractVector, axis::Integer) - isempty(A) && return B - v1 = op(v0, first(A)) - _accumulate1!(op, B, v1, A, axis) -end - -accumulate!(op, y::AbstractVector, v0, x::AbstractVector) = accumulate!(op, y, v0, x, 1) - -function _accumulate1!(op, B, v1, A::AbstractVector, axis::Integer) - axis > 0 || throw(ArgumentError("axis must be a positive integer")) - inds = linearindices(A) - inds == linearindices(B) || throw(DimensionMismatch("linearindices of A and B don't match")) - axis > 1 && return copy!(B, A) - i1 = inds[1] - cur_val = v1 - B[i1] = cur_val - @inbounds for i in inds[2:end] - cur_val = op(cur_val, A[i]) - B[i] = cur_val - end - return B -end +accumulate(op, x::AbstractVector) = accumulate(op, x, 1) """ accumulate!(op, B, A, dim) @@ -888,7 +906,17 @@ function accumulate!(op, B, A, axis::Integer) return B end -accumulate!(op, y::AbstractVector, x::AbstractVector) = accumulate!(op, y, x, 1) +""" + accumulate!(op, y, x::AbstractVector) + +Cumulative operation `op` on a vector `x`, storing the result in `y`. +See also [`accumulate`](@ref). +""" +function accumulate!(op::Op, y, x::AbstractVector) where Op + isempty(x) && return y + v1 = first(x) + _accumulate1!(op, y, v1, x, 1) +end @noinline function _accumulate!(op, B, A, R1, ind, R2) # Copy the initial element in each 1d vector along dimension `axis` @@ -903,6 +931,54 @@ accumulate!(op, y::AbstractVector, x::AbstractVector) = accumulate!(op, y, x, 1) B end +""" + accumulate(op, v0, x::AbstractVector) + +Like `accumulate`, but using a starting element `v0`. The first entry of the result will be +`op(v0, first(A))`. + +# Examples +```jldoctest +julia> accumulate(+, 100, [1,2,3]) +3-element Array{Int64,1}: + 101 + 103 + 106 + +julia> accumulate(min, 0, [1,2,-1]) +3-element Array{Int64,1}: + 0 + 0 + -1 +``` +""" +function accumulate(op, v0, x::AbstractVector) + T = rcum_promote_type(op, typeof(v0), eltype(x)) + out = similar(x, T) + accumulate!(op, out, v0, x) +end + +function accumulate!(op, y, v0, x::AbstractVector) + isempty(x) && return y + v1 = op(v0, first(x)) + _accumulate1!(op, y, v1, x, 1) +end + +function _accumulate1!(op, B, v1, A::AbstractVector, axis::Integer) + axis > 0 || throw(ArgumentError("axis must be a positive integer")) + inds = linearindices(A) + inds == linearindices(B) || throw(DimensionMismatch("linearindices of A and B don't match")) + axis > 1 && return copy!(B, A) + i1 = inds[1] + cur_val = v1 + B[i1] = cur_val + @inbounds for i in inds[2:end] + cur_val = op(cur_val, A[i]) + B[i] = cur_val + end + return B +end + ### from abstractarray.jl """