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Merged
merged 4 commits into from
May 30, 2021
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Preserve axes in permutedims for AbstractVectors #243

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1002455
preserve axes in permutedims for AbstractVectors
jishnub May 29, 2021
c312eac
fix stackoverflow in reshape
jishnub May 30, 2021
8409f01
conditionally pop parent array in reshape
jishnub May 30, 2021
986fc0a
add test for 2D permutedims
jishnub May 30, 2021
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7 changes: 6 additions & 1 deletion src/OffsetArrays.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -349,7 +349,8 @@ _similar_axes_or_length(AT, ax::I, ::I) where {I} = similar(AT, map(_indexlength
Base.reshape(A::AbstractArray, inds::OffsetAxis...) = reshape(A, inds)
function Base.reshape(A::AbstractArray, inds::Tuple{OffsetAxis,Vararg{OffsetAxis}})
AR = reshape(A, map(_indexlength, inds))
return OffsetArray(AR, map(_offset, axes(AR), inds))
O = OffsetArray(AR, map(_offset, axes(AR), inds))
return _popreshape(O, axes(AR), _filterreshapeinds(inds))
end

# Reshaping OffsetArrays can "pop" the original OffsetArray wrapper and return
Expand All @@ -364,6 +365,10 @@ Base.reshape(A::OffsetVector, ::Colon) = A
Base.reshape(A::OffsetArray, inds::Union{Int,Colon}...) = reshape(parent(A), inds)
Base.reshape(A::OffsetArray, inds::Tuple{Vararg{Union{Int,Colon}}}) = reshape(parent(A), inds)

# permutedims in Base does not preserve axes, and can not be fixed in a non-breaking way
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Would you explain it a bit why this can't be fixed in a non-breaking way? The following version looks good to me.

julia> using OffsetArrays

julia> function Base.permutedims(v::AbstractVector)
           out = similar(v, (1, axes(v, 1)))
           copyto!(out, v)
       end

julia> permutedims(rand(4))
1×4 Matrix{Float64}:
 0.062106  0.864693  0.0235159  0.929236

julia> x = OffsetArray(rand(4,), -1);

julia> permutedims(x)
1×4 OffsetArray(::Matrix{Float64}, 1:1, 0:3) with eltype Float64 with indices 1:1×0:3:
 0.449456  0.0518755  0.689773  0.00949295

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@jishnub jishnub May 29, 2021 •
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The docstring for permutedims states that it must be a reshape for AbstractVectors (that is the underlying data is shared), however reshape does not currently accept custom axis types as arguments.

Although I might be misinterpreting what the docstring tries to say. Perhaps it uses reshape loosely.

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JuliaLang/julia#41003 is a good but controversial call; I don't think there will be a generic fix until #87 (comment) is solved; there will be many similar issues as identified by @mcabbott.

This specialization itself makes sense without being involved in type piracy so there's no objection in adding this to OffsetArrays.

# This is a stopgap solution
Base.permutedims(v::OffsetVector) = reshape(v, (1, axes(v, 1)))

Base.fill(v, inds::NTuple{N, Union{Integer, AbstractUnitRange}}) where {N} =
fill!(similar(Array{typeof(v)}, inds), v)
Base.zeros(::Type{T}, inds::NTuple{N, Union{Integer, AbstractUnitRange}}) where {T, N} =
Expand Down
10 changes: 9 additions & 1 deletion src/utils.jl
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Expand Up @@ -4,7 +4,7 @@ _indexoffset(r::AbstractRange) = first(r) - 1
_indexoffset(i::Integer) = 0
_indexoffset(i::Colon) = 0
_indexlength(r::AbstractRange) = length(r)
_indexlength(i::Integer) = i
_indexlength(i::Integer) = Int(i)
_indexlength(i::Colon) = Colon()

_strip_IdOffsetRange(r::IdOffsetRange) = parent(r)
Expand Down Expand Up @@ -102,3 +102,11 @@ end

_of_eltype(::Type{T}, M::AbstractArray{T}) where {T} = M
_of_eltype(T, M::AbstractArray) = map(T, M)

# filter the arguments to reshape to check if there are any ranges
# If not, we may pop the parent array
_filterreshapeinds(t::Tuple{AbstractUnitRange, Vararg{Any}}) = t
_filterreshapeinds(t::Tuple) = _filterreshapeinds(tail(t))
_filterreshapeinds(t::Tuple{}) = t
_popreshape(A::AbstractArray, ax::Tuple{Vararg{Base.OneTo}}, inds::Tuple{}) = no_offset_view(A)
_popreshape(A::AbstractArray, ax, inds) = A
33 changes: 33 additions & 0 deletions test/runtests.jl
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Expand Up @@ -1767,6 +1767,39 @@ end
Arsc = reshape(A, :, 1)
Arsc[1,1] = 5
@test first(A) == 5

@testset "issue #235" begin
Vec64 = zeros(6)
ind_a_64 = 3
ind_a_32 =Int32.(ind_a_64)
@test reshape(Vec64, ind_a_32, :) == reshape(Vec64, ind_a_64, :)
end

R = reshape(zeros(6), 2, :)
@test R isa Matrix
@test axes(R) == (1:2, 1:3)
R = reshape(zeros(6,1), 2, :)
@test R isa Matrix
@test axes(R) == (1:2, 1:3)

R = reshape(zeros(6), 1:2, :)
@test axes(R) == (1:2, 1:3)
R = reshape(zeros(6,1), 1:2, :)
@test axes(R) == (1:2, 1:3)
end

@testset "permutedims" begin
a = OffsetArray(1:2, 2:3)
@test permutedims(a) == reshape(1:2, 1, 2:3)
a = OffsetArray([10,11], Base.OneTo(2))
@test permutedims(a) == reshape(10:11, 1, 1:2)
a = OffsetArray(SVector{2}(1,2), 3:4)
@test permutedims(a) == reshape(1:2, 1, 3:4)

# check that the 2D case is unaffected
a = OffsetArray(reshape(1:2, 1, 2), 2:2, 4:5)
b = permutedims(a)
@test a[2,:] == b[:,2]
end

@testset "Indexing with OffsetArray axes" begin
Expand Down