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abstractarray.jl
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abstractarray.jl
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# This file is a part of Julia. License is MIT: https://julialang.org/license
using Random, LinearAlgebra, SparseArrays
A = rand(5,4,3)
@testset "Bounds checking" begin
@test checkbounds(Bool, A, 1, 1, 1) == true
@test checkbounds(Bool, A, 5, 4, 3) == true
@test checkbounds(Bool, A, 0, 1, 1) == false
@test checkbounds(Bool, A, 1, 0, 1) == false
@test checkbounds(Bool, A, 1, 1, 0) == false
@test checkbounds(Bool, A, 6, 4, 3) == false
@test checkbounds(Bool, A, 5, 5, 3) == false
@test checkbounds(Bool, A, 5, 4, 4) == false
@test checkbounds(Bool, A, 1) == true # linear indexing
@test checkbounds(Bool, A, 60) == true
@test checkbounds(Bool, A, 61) == false
@test checkbounds(Bool, A, 2, 2, 2, 1) == true # extra indices
@test checkbounds(Bool, A, 2, 2, 2, 2) == false
@test checkbounds(Bool, A, 1, 1) == false
@test checkbounds(Bool, A, 1, 12) == false
@test checkbounds(Bool, A, 5, 12) == false
@test checkbounds(Bool, A, 1, 13) == false
@test checkbounds(Bool, A, 6, 12) == false
end
@testset "single CartesianIndex" begin
@test checkbounds(Bool, A, CartesianIndex((1, 1, 1))) == true
@test checkbounds(Bool, A, CartesianIndex((5, 4, 3))) == true
@test checkbounds(Bool, A, CartesianIndex((0, 1, 1))) == false
@test checkbounds(Bool, A, CartesianIndex((1, 0, 1))) == false
@test checkbounds(Bool, A, CartesianIndex((1, 1, 0))) == false
@test checkbounds(Bool, A, CartesianIndex((6, 4, 3))) == false
@test checkbounds(Bool, A, CartesianIndex((5, 5, 3))) == false
@test checkbounds(Bool, A, CartesianIndex((5, 4, 4))) == false
@test checkbounds(Bool, A, CartesianIndex((1,))) == false
@test checkbounds(Bool, A, CartesianIndex((60,))) == false
@test checkbounds(Bool, A, CartesianIndex((61,))) == false
@test checkbounds(Bool, A, CartesianIndex((2, 2, 2, 1,))) == true
@test checkbounds(Bool, A, CartesianIndex((2, 2, 2, 2,))) == false
@test checkbounds(Bool, A, CartesianIndex((1, 1,))) == false
@test checkbounds(Bool, A, CartesianIndex((1, 12,))) == false
@test checkbounds(Bool, A, CartesianIndex((5, 12,))) == false
@test checkbounds(Bool, A, CartesianIndex((1, 13,))) == false
@test checkbounds(Bool, A, CartesianIndex((6, 12,))) == false
end
@testset "mix of CartesianIndex and Int" begin
@test checkbounds(Bool, A, CartesianIndex((1,)), 1, CartesianIndex((1,))) == true
@test checkbounds(Bool, A, CartesianIndex((5, 4)), 3) == true
@test checkbounds(Bool, A, CartesianIndex((0, 1)), 1) == false
@test checkbounds(Bool, A, 1, CartesianIndex((0, 1))) == false
@test checkbounds(Bool, A, 1, 1, CartesianIndex((0,))) == false
@test checkbounds(Bool, A, 6, CartesianIndex((4, 3))) == false
@test checkbounds(Bool, A, 5, CartesianIndex((5,)), 3) == false
@test checkbounds(Bool, A, CartesianIndex((5,)), CartesianIndex((4,)), CartesianIndex((4,))) == false
end
@testset "vector indices" begin
@test checkbounds(Bool, A, 1:5, 1:4, 1:3) == true
@test checkbounds(Bool, A, 0:5, 1:4, 1:3) == false
@test checkbounds(Bool, A, 1:5, 0:4, 1:3) == false
@test checkbounds(Bool, A, 1:5, 1:4, 0:3) == false
@test checkbounds(Bool, A, 1:6, 1:4, 1:3) == false
@test checkbounds(Bool, A, 1:5, 1:5, 1:3) == false
@test checkbounds(Bool, A, 1:5, 1:4, 1:4) == false
@test checkbounds(Bool, A, 1:60) == true
@test checkbounds(Bool, A, 1:61) == false
@test checkbounds(Bool, A, 2, 2, 2, 1:1) == true # extra indices
@test checkbounds(Bool, A, 2, 2, 2, 1:2) == false
@test checkbounds(Bool, A, 1:5, 1:4) == false
@test checkbounds(Bool, A, 1:5, 1:12) == false
@test checkbounds(Bool, A, 1:5, 1:13) == false
@test checkbounds(Bool, A, 1:6, 1:12) == false
end
@testset "logical" begin
@test checkbounds(Bool, A, trues(5), trues(4), trues(3)) == true
@test checkbounds(Bool, A, trues(6), trues(4), trues(3)) == false
@test checkbounds(Bool, A, trues(5), trues(5), trues(3)) == false
@test checkbounds(Bool, A, trues(5), trues(4), trues(4)) == false
@test checkbounds(Bool, A, trues(60)) == true
@test checkbounds(Bool, A, trues(61)) == false
@test checkbounds(Bool, A, 2, 2, 2, trues(1)) == true # extra indices
@test checkbounds(Bool, A, 2, 2, 2, trues(2)) == false
@test checkbounds(Bool, A, trues(5), trues(12)) == false
@test checkbounds(Bool, A, trues(5), trues(13)) == false
@test checkbounds(Bool, A, trues(6), trues(12)) == false
@test checkbounds(Bool, A, trues(5, 4, 3)) == true
@test checkbounds(Bool, A, trues(5, 4, 2)) == false
@test checkbounds(Bool, A, trues(5, 12)) == false
@test checkbounds(Bool, A, trues(1, 5), trues(1, 4, 1), trues(1, 1, 3)) == false
@test checkbounds(Bool, A, trues(1, 5), trues(1, 4, 1), trues(1, 1, 2)) == false
@test checkbounds(Bool, A, trues(1, 5), trues(1, 5, 1), trues(1, 1, 3)) == false
@test checkbounds(Bool, A, trues(1, 5), :, 2) == false
end
@testset "array of CartesianIndex" begin
@test checkbounds(Bool, A, [CartesianIndex((1, 1, 1))]) == true
@test checkbounds(Bool, A, [CartesianIndex((5, 4, 3))]) == true
@test checkbounds(Bool, A, [CartesianIndex((0, 1, 1))]) == false
@test checkbounds(Bool, A, [CartesianIndex((1, 0, 1))]) == false
@test checkbounds(Bool, A, [CartesianIndex((1, 1, 0))]) == false
@test checkbounds(Bool, A, [CartesianIndex((6, 4, 3))]) == false
@test checkbounds(Bool, A, [CartesianIndex((5, 5, 3))]) == false
@test checkbounds(Bool, A, [CartesianIndex((5, 4, 4))]) == false
@test checkbounds(Bool, A, [CartesianIndex((1, 1))], 1) == true
@test checkbounds(Bool, A, [CartesianIndex((5, 4))], 3) == true
@test checkbounds(Bool, A, [CartesianIndex((0, 1))], 1) == false
@test checkbounds(Bool, A, [CartesianIndex((1, 0))], 1) == false
@test checkbounds(Bool, A, [CartesianIndex((1, 1))], 0) == false
@test checkbounds(Bool, A, [CartesianIndex((6, 4))], 3) == false
@test checkbounds(Bool, A, [CartesianIndex((5, 5))], 3) == false
@test checkbounds(Bool, A, [CartesianIndex((5, 4))], 4) == false
end
@testset "index conversion" begin
@testset "0-dimensional" begin
for i in ((), fill(0))
@test LinearIndices(i)[1] == 1
@test_throws BoundsError LinearIndices(i)[2]
@test_throws BoundsError LinearIndices(i)[1:2]
@test LinearIndices(i)[1,1] == 1
@test LinearIndices(i)[] == 1
@test size(LinearIndices(i)) == ()
@test CartesianIndices(i)[1] == CartesianIndex()
@test_throws BoundsError CartesianIndices(i)[2]
@test_throws BoundsError CartesianIndices(i)[1:2]
end
end
@testset "1-dimensional" begin
for i = 1:3
@test LinearIndices((3,))[i] == i
@test CartesianIndices((3,))[i] == CartesianIndex(i,)
end
@test LinearIndices((3,))[2,1] == 2
@test LinearIndices((3,))[[1]] == [1]
@test size(LinearIndices((3,))) == (3,)
@test LinearIndices((3,))[1:2] === 1:2
@test LinearIndices((3,))[1:2:3] === 1:2:3
@test_throws BoundsError LinearIndices((3,))[2:4]
@test_throws BoundsError CartesianIndices((3,))[2,2]
# ambiguity btw cartesian indexing and linear indexing in 1d when
# indices may be nontraditional
@test_throws ArgumentError Base._sub2ind((1:3,), 2)
@test_throws ArgumentError Base._ind2sub((1:3,), 2)
ci = CartesianIndices((2:4,))
@test first(ci) == ci[1] == CartesianIndex(2)
@test last(ci) == ci[end] == ci[3] == CartesianIndex(4)
li = LinearIndices(ci)
@test collect(li) == [1,2,3]
@test first(li) == li[1] == 1
@test last(li) == li[3] == 3
io = IOBuffer()
show(io, ci)
@test String(take!(io)) == "CartesianIndex{1}[CartesianIndex(2,), CartesianIndex(3,), CartesianIndex(4,)]"
end
@testset "2-dimensional" begin
k = 0
cartesian = CartesianIndices((4,3))
linear = LinearIndices(cartesian)
@test size(cartesian) == size(linear) == (4, 3)
for j = 1:3, i = 1:4
k += 1
@test linear[i,j] == linear[k] == k
@test cartesian[k] == CartesianIndex(i,j)
@test LinearIndices(map(Base.Slice, (0:3,3:5)))[i-1,j+2] == k
@test CartesianIndices(map(Base.Slice, (0:3,3:5)))[k] == CartesianIndex(i-1,j+2)
end
@test linear[linear] == linear
@test linear[vec(linear)] == vec(linear)
@test linear[cartesian] == linear
@test linear[vec(cartesian)] == vec(linear)
@test cartesian[linear] == cartesian
@test cartesian[vec(linear)] == vec(cartesian)
@test cartesian[cartesian] == cartesian
@test cartesian[vec(cartesian)] == vec(cartesian)
@test linear[2:3] === 2:3
@test linear[3:-1:1] === 3:-1:1
@test_throws BoundsError linear[4:13]
end
@testset "3-dimensional" begin
l = 0
for k = 1:2, j = 1:3, i = 1:4
l += 1
@test LinearIndices((4,3,2))[i,j,k] == l
@test LinearIndices((4,3,2))[l] == l
@test CartesianIndices((4,3,2))[i,j,k] == CartesianIndex(i,j,k)
@test CartesianIndices((4,3,2))[l] == CartesianIndex(i,j,k)
@test LinearIndices((1:4,1:3,1:2))[i,j,k] == l
@test LinearIndices((1:4,1:3,1:2))[l] == l
@test CartesianIndices((1:4,1:3,1:2))[i,j,k] == CartesianIndex(i,j,k)
@test CartesianIndices((1:4,1:3,1:2))[l] == CartesianIndex(i,j,k)
end
l = 0
for k = -101:-100, j = 3:5, i = 0:3
l += 1
@test LinearIndices(map(Base.Slice, (0:3,3:5,-101:-100)))[i,j,k] == l
@test LinearIndices(map(Base.Slice, (0:3,3:5,-101:-100)))[l] == l
@test CartesianIndices(map(Base.Slice, (0:3,3:5,-101:-100)))[i,j,k] == CartesianIndex(i,j,k)
@test CartesianIndices(map(Base.Slice, (0:3,3:5,-101:-100)))[l] == CartesianIndex(i,j,k)
end
local A = reshape(Vector(1:9), (3,3))
@test CartesianIndices(size(A))[6] == CartesianIndex(3,2)
@test LinearIndices(size(A))[3, 2] == 6
@test CartesianIndices(A)[6] == CartesianIndex(3,2)
@test LinearIndices(A)[3, 2] == 6
for i in 1:length(A)
@test LinearIndices(A)[CartesianIndices(A)[i]] == i
end
@testset "PR #9256" begin
function pr9256()
m = [1 2 3; 4 5 6; 7 8 9]
Base._ind2sub(m, 6)
end
@test pr9256() == (3,2)
end
end
end
# token type on which to dispatch testing methods in order to avoid potential
# name conflicts elsewhere in the base test suite
mutable struct TestAbstractArray end
## Tests for the abstract array interfaces with minimally defined array types
if !isdefined(@__MODULE__, :T24Linear)
include("testhelpers/arrayindexingtypes.jl")
end
const can_inline = Base.JLOptions().can_inline != 0
function test_scalar_indexing(::Type{T}, shape, ::Type{TestAbstractArray}) where T
N = prod(shape)
A = reshape(Vector(1:N), shape)
B = T(A)
@test A == B
# Test indexing up to 5 dimensions
trailing5 = CartesianIndex(ntuple(x->1, max(ndims(B)-5, 0)))
trailing4 = CartesianIndex(ntuple(x->1, max(ndims(B)-4, 0)))
trailing3 = CartesianIndex(ntuple(x->1, max(ndims(B)-3, 0)))
trailing2 = CartesianIndex(ntuple(x->1, max(ndims(B)-2, 0)))
i=0
for i5 = 1:size(B, 5)
for i4 = 1:size(B, 4)
for i3 = 1:size(B, 3)
for i2 = 1:size(B, 2)
for i1 = 1:size(B, 1)
i += 1
@test A[i1,i2,i3,i4,i5,trailing5] == B[i1,i2,i3,i4,i5,trailing5] == i
@test A[i1,i2,i3,i4,i5,trailing5] ==
Base.unsafe_getindex(B, i1, i2, i3, i4, i5, trailing5) == i
end
end
end
end
end
# Test linear indexing and partial linear indexing
i=0
for i1 = 1:length(B)
i += 1
@test A[i1] == B[i1] == i
end
i=0
for i2 = 1:size(B, 2)
for i1 = 1:size(B, 1)
i += 1
@test A[i1,i2,trailing2] == B[i1,i2,trailing2] == i
end
end
@test A == B
i=0
for i3 = 1:size(B, 3)
for i2 = 1:size(B, 2)
for i1 = 1:size(B, 1)
i += 1
@test A[i1,i2,i3,trailing3] == B[i1,i2,i3,trailing3] == i
end
end
end
# Test zero-dimensional accesses
@test A[1] == B[1] == 1
# Test multidimensional scalar indexed assignment
C = T(Int, shape)
D1 = T(Int, shape)
D2 = T(Int, shape)
D3 = T(Int, shape)
i=0
for i5 = 1:size(B, 5)
for i4 = 1:size(B, 4)
for i3 = 1:size(B, 3)
for i2 = 1:size(B, 2)
for i1 = 1:size(B, 1)
i += 1
C[i1,i2,i3,i4,i5,trailing5] = i
# test general unsafe_setindex!
Base.unsafe_setindex!(D1, i, i1,i2,i3,i4,i5,trailing5)
# test for dropping trailing dims
Base.unsafe_setindex!(D2, i, i1,i2,i3,i4,i5,trailing5, 1, 1, 1)
# test for expanding index argument to appropriate dims
Base.unsafe_setindex!(D3, i, i1,i2,i3,i4,trailing4)
end
end
end
end
end
@test D1 == D2 == C == B == A
@test D3[:, :, :, :, 1, trailing5] == D2[:, :, :, :, 1, trailing5]
# Test linear indexing and partial linear indexing
C = T(Int, shape)
fill!(C, 0)
@test C != B && C != A
i=0
for i1 = 1:length(C)
i += 1
C[i1] = i
end
@test C == B == A
C = T(Int, shape)
i=0
C2 = reshape(C, Val(2))
for i2 = 1:size(C2, 2)
for i1 = 1:size(C2, 1)
i += 1
C2[i1,i2,trailing2] = i
end
end
@test C == B == A
C = T(Int, shape)
i=0
C3 = reshape(C, Val(3))
for i3 = 1:size(C3, 3)
for i2 = 1:size(C3, 2)
for i1 = 1:size(C3, 1)
i += 1
C3[i1,i2,i3,trailing3] = i
end
end
end
@test C == B == A
# Test zero-dimensional setindex
if length(A) == 1
A[] = 0; B[] = 0
@test A[] == B[] == 0
@test A == B
else
@test_throws BoundsError A[] = 0
@test_throws BoundsError B[] = 0
@test_throws BoundsError A[]
@test_throws BoundsError B[]
end
end
function test_vector_indexing(::Type{T}, shape, ::Type{TestAbstractArray}) where T
@testset "test_vector_indexing{$(T)}" begin
N = prod(shape)
A = reshape(Vector(1:N), shape)
B = T(A)
trailing5 = CartesianIndex(ntuple(x->1, max(ndims(B)-5, 0)))
trailing4 = CartesianIndex(ntuple(x->1, max(ndims(B)-4, 0)))
trailing3 = CartesianIndex(ntuple(x->1, max(ndims(B)-3, 0)))
trailing2 = CartesianIndex(ntuple(x->1, max(ndims(B)-2, 0)))
idxs = rand(1:N, 3, 3, 3)
@test B[idxs] == A[idxs] == idxs
@test B[vec(idxs)] == A[vec(idxs)] == vec(idxs)
@test B[:] == A[:] == 1:N
@test B[1:end] == A[1:end] == 1:N
@test B[:,:,trailing2] == A[:,:,trailing2] == B[:,:,1,trailing3] == A[:,:,1,trailing3]
B[1:end,1:end,trailing2] == A[1:end,1:end,trailing2] == B[1:end,1:end,1,trailing3] == A[1:end,1:end,1,trailing3]
@testset "Test with containers that aren't Int[]" begin
@test B[[]] == A[[]] == []
@test B[convert(Array{Any}, idxs)] == A[convert(Array{Any}, idxs)] == idxs
end
idx1 = rand(1:size(A, 1), 3)
idx2 = rand(1:size(A, 2), 4, 5)
@testset "Test adding dimensions with matrices" begin
@test B[idx1, idx2, trailing2] == A[idx1, idx2, trailing2] == reshape(A[idx1, vec(idx2), trailing2], 3, 4, 5) == reshape(B[idx1, vec(idx2), trailing2], 3, 4, 5)
@test B[1, idx2, trailing2] == A[1, idx2, trailing2] == reshape(A[1, vec(idx2), trailing2], 4, 5) == reshape(B[1, vec(idx2), trailing2], 4, 5)
end
# test removing dimensions with 0-d arrays
@testset "test removing dimensions with 0-d arrays" begin
idx0 = reshape([rand(1:size(A, 1))])
@test B[idx0, idx2, trailing2] == A[idx0, idx2, trailing2] == reshape(A[idx0[], vec(idx2), trailing2], 4, 5) == reshape(B[idx0[], vec(idx2), trailing2], 4, 5)
@test B[reshape([end]), reshape([end]), trailing2] == A[reshape([end]), reshape([end]), trailing2] == reshape([A[end,end,trailing2]]) == reshape([B[end,end,trailing2]])
end
mask = bitrand(shape)
@testset "test logical indexing" begin
@test B[mask] == A[mask] == B[findall(mask)] == A[findall(mask)] == LinearIndices(mask)[findall(mask)]
@test B[vec(mask)] == A[vec(mask)] == LinearIndices(mask)[findall(mask)]
mask1 = bitrand(size(A, 1))
mask2 = bitrand(size(A, 2))
@test B[mask1, mask2, trailing2] == A[mask1, mask2, trailing2] ==
B[LinearIndices(mask1)[findall(mask1)], LinearIndices(mask2)[findall(mask2)], trailing2]
@test B[mask1, 1, trailing2] == A[mask1, 1, trailing2] == LinearIndices(mask)[findall(mask1)]
end
end
end
function test_primitives(::Type{T}, shape, ::Type{TestAbstractArray}) where T
N = prod(shape)
A = reshape(Vector(1:N), shape)
B = T(A)
# last(a)
@test last(B) == B[lastindex(B)] == B[end] == A[end]
@test lastindex(B) == lastindex(A) == last(LinearIndices(B))
@test lastindex(B, 1) == lastindex(A, 1) == last(axes(B, 1))
@test lastindex(B, 2) == lastindex(A, 2) == last(axes(B, 2))
# first(a)
@test first(B) == B[firstindex(B)] == B[begin] == B[1] == A[1] == A[begin]
@test firstindex(B) == firstindex(A) == first(LinearIndices(B))
@test firstindex(B, 1) == firstindex(A, 1) == first(axes(B, 1))
@test firstindex(B, 2) == firstindex(A, 2) == first(axes(B, 2))
# isassigned(a::AbstractArray, i::Int...)
j = rand(1:length(B))
@test isassigned(B, j) == true
if T == T24Linear
@test isassigned(B, length(B) + 1) == false
end
# reshape(a::AbstractArray, dims::Dims)
@test_throws DimensionMismatch reshape(B, (0, 1))
# copyto!(dest::AbstractArray, src::AbstractArray)
@test_throws BoundsError copyto!(Vector{Int}(undef, 10), [1:11...])
# convert{T, N}(::Type{Array}, A::AbstractArray{T, N})
X = [1:10...]
Y = [1 2; 3 4]
@test convert(Array, X) == X
@test convert(Array, Y) == Y
# convert{T}(::Type{Vector}, A::AbstractVector{T})
@test convert(Vector, X) == X
@test convert(Vector, view(X, 2:4)) == [2,3,4]
@test_throws MethodError convert(Vector, Y)
# convert{T}(::Type{Matrix}, A::AbstractMatrix{T})
@test convert(Matrix, Y) == Y
@test convert(Matrix, view(Y, 1:2, 1:2)) == Y
@test_throws MethodError convert(Matrix, X)
end
mutable struct TestThrowNoGetindex{T} <: AbstractVector{T} end
@testset "ErrorException if getindex is not defined" begin
Base.length(::TestThrowNoGetindex) = 2
Base.size(::TestThrowNoGetindex) = (2,)
@test_throws ErrorException isassigned(TestThrowNoGetindex{Float64}(), 1)
end
function test_in_bounds(::Type{TestAbstractArray})
n = rand(2:5)
sz = rand(2:5, n)
len = prod(sz)
A = zeros(sz...)
for i in 1:len
@test checkbounds(Bool, A, i) == true
end
@test checkbounds(Bool, A, len + 1) == false
end
mutable struct UnimplementedFastArray{T, N} <: AbstractArray{T, N} end
Base.IndexStyle(::UnimplementedFastArray) = Base.IndexLinear()
mutable struct UnimplementedSlowArray{T, N} <: AbstractArray{T, N} end
Base.IndexStyle(::UnimplementedSlowArray) = Base.IndexCartesian()
mutable struct UnimplementedArray{T, N} <: AbstractArray{T, N} end
function test_getindex_internals(::Type{T}, shape, ::Type{TestAbstractArray}) where T
N = prod(shape)
A = reshape(Vector(1:N), shape)
B = T(A)
@test getindex(A, 1) == 1
@test getindex(B, 1) == 1
@test Base.unsafe_getindex(A, 1) == 1
@test Base.unsafe_getindex(B, 1) == 1
end
function test_getindex_internals(::Type{TestAbstractArray})
U = UnimplementedFastArray{Int, 2}()
V = UnimplementedSlowArray{Int, 2}()
@test_throws ErrorException getindex(U, 1)
@test_throws ErrorException Base.unsafe_getindex(U, 1)
@test_throws ErrorException getindex(V, 1, 1)
@test_throws ErrorException Base.unsafe_getindex(V, 1, 1)
end
function test_setindex!_internals(::Type{T}, shape, ::Type{TestAbstractArray}) where T
N = prod(shape)
A = reshape(Vector(1:N), shape)
B = T(A)
Base.unsafe_setindex!(B, 2, 1)
@test B[1] == 2
end
function test_setindex!_internals(::Type{TestAbstractArray})
U = UnimplementedFastArray{Int, 2}()
V = UnimplementedSlowArray{Int, 2}()
@test_throws ErrorException setindex!(U, 0, 1)
@test_throws ErrorException Base.unsafe_setindex!(U, 0, 1)
@test_throws ErrorException setindex!(V, 0, 1, 1)
@test_throws ErrorException Base.unsafe_setindex!(V, 0, 1, 1)
end
function test_get(::Type{TestAbstractArray})
A = T24Linear(reshape([1:24...], 4, 3, 2))
B = TSlow(reshape([1:24...], 4, 3, 2))
@test get(A, (), 0) == 0
@test get(B, (), 0) == 0
@test get(A, (1,), 0) == get(A, 1, 0) == A[1] == 1
@test get(B, (1,), 0) == get(B, 1, 0) == B[1] == 1
@test get(A, (25,), 0) == get(A, 25, 0) == 0
@test get(B, (25,), 0) == get(B, 25, 0) == 0
@test get(A, (1,1,1), 0) == A[1,1,1] == 1
@test get(B, (1,1,1), 0) == B[1,1,1] == 1
@test get(A, (1,1,3), 0) == 0
@test get(B, (1,1,3), 0) == 0
@test get(TSlow([]), (), 0) == 0
@test get(TSlow([1]), (), 0) == 1
@test get(TSlow(fill(1)), (), 0) == 1
end
function test_cat(::Type{TestAbstractArray})
A = T24Linear([1:24...])
b_int = reshape([1:27...], 3, 3, 3)
b_float = reshape(Float64[1:27...], 3, 3, 3)
b2hcat = Array{Float64}(undef, 3, 6, 3)
b1 = reshape([1:9...], 3, 3)
b2 = reshape([10:18...], 3, 3)
b3 = reshape([19:27...], 3, 3)
b2hcat[:, :, 1] = hcat(b1, b1)
b2hcat[:, :, 2] = hcat(b2, b2)
b2hcat[:, :, 3] = hcat(b3, b3)
b3hcat = Array{Float64}(undef, 3, 9, 3)
b3hcat[:, :, 1] = hcat(b1, b1, b1)
b3hcat[:, :, 2] = hcat(b2, b2, b2)
b3hcat[:, :, 3] = hcat(b3, b3, b3)
B = TSlow(b_int)
B1 = TSlow([1:24...])
B2 = TSlow([1:25...])
C1 = TSlow([1 2; 3 4])
C2 = TSlow([1 2 3; 4 5 6])
C3 = TSlow([1 2; 3 4; 5 6])
D = [1:24...]
i = rand(1:10)
@test cat(;dims=i) == Any[]
@test vcat() == Any[]
@test hcat() == Any[]
@test hcat(1, 1.0, 3, 3.0) == [1.0 1.0 3.0 3.0]
@test_throws ArgumentError hcat(B1, B2)
@test_throws ArgumentError vcat(C1, C2)
@test vcat(B) == B
@test hcat(B) == B
@test Base.typed_hcat(Float64, B) == TSlow(b_float)
@test Base.typed_hcat(Float64, B, B) == TSlow(b2hcat)
@test Base.typed_hcat(Float64, B, B, B) == TSlow(b3hcat)
@test vcat(B1, B2) == TSlow(vcat([1:24...], [1:25...]))
@test hcat(C1, C2) == TSlow([1 2 1 2 3; 3 4 4 5 6])
@test hcat(C1, C2, C1) == TSlow([1 2 1 2 3 1 2; 3 4 4 5 6 3 4])
# hvcat
for nbc in (1, 2, 3, 4, 5, 6)
@test hvcat(nbc, 1:120...) == reshape([1:120...], nbc, round(Int, 120 / nbc))'
end
@test_throws ArgumentError hvcat(7, 1:20...)
@test_throws ArgumentError hvcat((2), C1, C3)
@test_throws ArgumentError hvcat((1), C1, C2)
@test_throws ArgumentError hvcat((1), C2, C3)
tup = tuple(rand(1:10, i)...)
@test hvcat(tup) == []
# check for shape mismatch
@test_throws ArgumentError hvcat((2, 2), 1, 2, 3, 4, 5)
@test_throws ArgumentError Base.typed_hvcat(Int, (2, 2), 1, 2, 3, 4, 5)
# check for # of columns mismatch b/w rows
@test_throws ArgumentError hvcat((3, 2), 1, 2, 3, 4, 5, 6)
@test_throws ArgumentError Base.typed_hvcat(Int, (3, 2), 1, 2, 3, 4, 5, 6)
# 18395
@test isa(Any["a" 5; 2//3 1.0][2,1], Rational{Int})
# 13665, 19038
@test @inferred(hcat([1.0 2.0], 3))::Array{Float64,2} == [1.0 2.0 3.0]
@test @inferred(vcat([1.0, 2.0], 3))::Array{Float64,1} == [1.0, 2.0, 3.0]
@test @inferred(vcat(["a"], "b"))::Vector{String} == ["a", "b"]
@test @inferred(vcat((1,), (2.0,)))::Vector{Tuple{Real}} == [(1,), (2.0,)]
# 29172
@test_throws ArgumentError cat([1], [2], dims=0)
@test_throws ArgumentError cat([1], [2], dims=[5, -3])
# 36041
@test_throws MethodError cat(["a"], ["b"], dims=[1, 2])
@test cat([1], [1], dims=[1, 2]) == I(2)
end
function test_ind2sub(::Type{TestAbstractArray})
n = rand(2:5)
dims = tuple(rand(1:5, n)...)
len = prod(dims)
A = reshape(Vector(1:len), dims...)
I = CartesianIndices(dims)
for i in 1:len
@test A[I[i]] == A[i]
end
end
# A custom linear slow array that insists upon Cartesian indexing
mutable struct TSlowNIndexes{T,N} <: AbstractArray{T,N}
data::Array{T,N}
end
Base.IndexStyle(::Type{A}) where {A<:TSlowNIndexes} = Base.IndexCartesian()
Base.size(A::TSlowNIndexes) = size(A.data)
Base.getindex(A::TSlowNIndexes, index::Int...) = error("Must use $(ndims(A)) indices")
Base.getindex(A::TSlowNIndexes{T,2}, i::Int, j::Int) where {T} = A.data[i,j]
@testset "issue #15689, mapping an abstract type" begin
@test isa(map(Set, Array[[1,2],[3,4]]), Vector{Set{Int}})
end
@testset "mapping over scalars and empty arguments:" begin
@test map(sin, 1) === sin(1)
@test map(()->1234) === 1234
end
function test_UInt_indexing(::Type{TestAbstractArray})
A = [1:100...]
_A = Expr(:quote, A)
for i in 1:100
_i8 = convert(UInt8, i)
_i16 = convert(UInt16, i)
_i32 = convert(UInt32, i)
for _i in (_i8, _i16, _i32)
@eval begin
@test $_A[$_i] == $i
end
end
end
end
# Issue 13315
function test_13315(::Type{TestAbstractArray})
U = UInt(1):UInt(2)
@test [U;[U;]] == [UInt(1), UInt(2), UInt(1), UInt(2)]
end
# checksquare
function test_checksquare()
@test LinearAlgebra.checksquare(zeros(2,2)) == 2
@test LinearAlgebra.checksquare(zeros(2,2),zeros(3,3)) == [2,3]
@test_throws DimensionMismatch LinearAlgebra.checksquare(zeros(2,3))
end
#----- run tests -------------------------------------------------------------#
@testset for T in (T24Linear, TSlow), shape in ((24,), (2, 12), (2,3,4), (1,2,3,4), (4,3,2,1))
test_scalar_indexing(T, shape, TestAbstractArray)
test_vector_indexing(T, shape, TestAbstractArray)
test_primitives(T, shape, TestAbstractArray)
test_getindex_internals(T, shape, TestAbstractArray)
test_setindex!_internals(T, shape, TestAbstractArray)
end
test_in_bounds(TestAbstractArray)
test_getindex_internals(TestAbstractArray)
test_setindex!_internals(TestAbstractArray)
test_get(TestAbstractArray)
test_cat(TestAbstractArray)
test_ind2sub(TestAbstractArray)
include("generic_map_tests.jl")
generic_map_tests(map, map!)
@test_throws ArgumentError map!(-, [1])
test_UInt_indexing(TestAbstractArray)
test_13315(TestAbstractArray)
test_checksquare()
A = TSlowNIndexes(rand(2,2))
@test_throws ErrorException A[1]
@test A[1,1] == A.data[1]
@test first(A) == A.data[1]
@testset "#16381" begin
@inferred size(rand(3,2,1))
@inferred size(rand(3,2,1), 2)
@test @inferred(axes(rand(3,2))) == (1:3,1:2)
@test @inferred(axes(rand(3,2,1))) == (1:3,1:2,1:1)
@test @inferred(axes(rand(3,2), 1)) == 1:3
@test @inferred(axes(rand(3,2), 2)) == 1:2
@test @inferred(axes(rand(3,2), 3)) == 1:1
end
@testset "#17088" begin
n = 10
M = rand(n, n)
@testset "vector of vectors" begin
v = [[M]; [M]] # using vcat
@test size(v) == (2,)
@test !issparse(v)
end
@testset "matrix of vectors" begin
m1 = [[M] [M]] # using hcat
m2 = [[M] [M];] # using hvcat
@test m1 == m2
@test size(m1) == (1,2)
@test !issparse(m1)
@test !issparse(m2)
end
end
@testset "isinteger and isreal" begin
@test all(isinteger, Diagonal(rand(1:5,5)))
@test isreal(Diagonal(rand(5)))
end
@testset "unary ops" begin
let A = Diagonal(rand(1:5,5))
@test +(A) == A
@test *(A) == A
end
end
@testset "reverse dim on empty" begin
@test reverse(Diagonal([]),dims=1) == Diagonal([])
end
@testset "ndims and friends" begin
@test ndims(Diagonal(rand(1:5,5))) == 2
@test ndims(Diagonal{Float64}) == 2
end
@testset "Issue #17811" begin
A17811 = Integer[]
I = [abs(x) for x in A17811]
@test isa(I, Array{Any,1})
push!(I, 1)
@test I == Any[1]
@test isa(map(abs, A17811), Array{Any,1})
end
@testset "copymutable for itrs" begin
@test Base.copymutable((1,2,3)) == [1,2,3]
end
@testset "_sub2ind for empty tuple" begin
@test Base._sub2ind(()) == 1
end
@testset "to_shape" begin
@test Base.to_shape(()) === ()
@test Base.to_shape(1) === 1
end
@testset "issue #19267" begin
@test ndims((1:3)[:]) == 1
@test ndims((1:3)[:,:]) == 2
@test ndims((1:3)[:,[1],:]) == 3
@test ndims((1:3)[:,[1],:,[1]]) == 4
@test ndims((1:3)[:,[1],1:1,:]) == 4
@test ndims((1:3)[:,:,1:1,:]) == 4
@test ndims((1:3)[:,:,1:1]) == 3
@test ndims((1:3)[:,:,1:1,:,:,[1]]) == 6
end
@testset "dispatch loop introduced in #19305" begin
Z22, O33 = fill(0, 2, 2), fill(1, 3, 3)
@test [(1:2) Z22; O33] == [[1,2] Z22; O33] == [[1 2]' Z22; O33]
end
@testset "checkbounds_indices method ambiguities #20989" begin
@test Base.checkbounds_indices(Bool, (1:1,), ([CartesianIndex(1)],))
end
# keys, values, pairs
for A in (rand(2), rand(2,3))
local A
for (i, v) in pairs(A)
@test A[i] == v
end
@test Array(values(A)) == A
@test keytype(A) == keytype(typeof(A)) == eltype(keys(A))
@test valtype(A) == valtype(typeof(A)) == eltype(values(A))
end
# nextind and prevind
@test nextind(zeros(4), 2) == 3
@test nextind(zeros(2,3), CartesianIndex(2,1)) == CartesianIndex(1, 2)
@test prevind(zeros(4), 2) == 1
@test prevind(zeros(2,3), CartesianIndex(2,1)) == CartesianIndex(1, 1)
@testset "ImageCore #40" begin
Base.convert(::Type{Array{T,n}}, a::Array{T,n}) where {T<:Number,n} = a
Base.convert(::Type{Array{T,n}}, a::Array) where {T<:Number,n} =
copyto!(Array{T,n}(undef, size(a)), a)
@test isa(empty(Dict(:a=>1, :b=>2.0), Union{}, Union{}), Dict{Union{}, Union{}})
end
@testset "zero-dimensional copy" begin
Z = Array{Int,0}(undef); Z[] = 17
@test Z == Array(Z) == copy(Z)
end
@testset "empty" begin
@test isempty([])
v = [1, 2, 3]
v2 = empty(v)
v3 = empty(v, Float64)
@test !isempty(v)
empty!(v)
@test isempty(v)
@test isempty(v2::Vector{Int})
@test isempty(v3::Vector{Float64})
end
@testset "CartesianIndices" begin
xrng = 2:4
yrng = 1:5
CR = CartesianIndices(map(Base.Slice, (xrng,yrng)))
for i in xrng, j in yrng
@test CR[i,j] == CartesianIndex(i,j)
end
for i_lin in LinearIndices(CR)
i = (i_lin-1) % length(xrng) + 1
j = (i_lin-i) ÷ length(xrng) + 1
@test CR[i_lin] == CartesianIndex(xrng[i],yrng[j])
end
@test CartesianIndices(fill(1., 2, 3)) == CartesianIndices((2,3))
@test LinearIndices((2,3)) == [1 3 5; 2 4 6]
for IType in (CartesianIndices, LinearIndices)
I1 = IType((Base.OneTo(3),))
I2 = IType((1:3,))
@test !(I1 === I2)
J1, J2 = @inferred(promote(I1, I2))
@test J1 === J2
end
i = CartesianIndex(17,-2)
@test CR .+ i === i .+ CR === CartesianIndices((19:21, -1:3))
@test CR .- i === CartesianIndices((-15:-13, 3:7))
@test collect(i .- CR) == Ref(i) .- collect(CR)
end
@testset "issue #25770" begin
@test vcat(1:3, fill(1, (2,1))) == vcat([1:3;], fill(1, (2,1))) == reshape([1,2,3,1,1], 5,1)
@test hcat(1:2, fill(1, (2,1))) == hcat([1:2;], fill(1, (2,1))) == reshape([1,2,1,1],2,2)
@test [(1:3) (4:6); fill(1, (3,2))] == reshape([1,2,3,1,1,1,4,5,6,1,1,1], 6,2)
end
@testset "copy!" begin
@testset "AbstractVector" begin
s = Vector([1, 2])
for a = ([1], UInt[1], [3, 4, 5], UInt[3, 4, 5])
@test s === copy!(s, Vector(a)) == Vector(a)
@test s === copy!(s, SparseVector(a)) == Vector(a)
end
# issue #35649
s = [1, 2, 3, 4]
s2 = reshape(s, 2, 2) # shared data
@test s === copy!(s, 11:14) == 11:14
end
@testset "AbstractArray" begin
@test_throws ArgumentError copy!(zeros(2, 3), zeros(3, 2))
s = zeros(2, 2)
@test s === copy!(s, fill(1, 2, 2)) == fill(1, 2, 2)
@test s === copy!(s, fill(1.0, 2, 2)) == fill(1.0, 2, 2)
end
end
@testset "map on Dicts/Sets is forbidden" begin
@test_throws ErrorException map(identity, Set([1,2,3]))
@test_throws ErrorException map(identity, Dict("a"=>"b"))
end
@testset "Issue 30145" begin
X = [1,2,3]
@test isempty(X[Union{}[]])
end
@testset "Issue 30259" begin
A = randn(1,2,3)
@test get(A, CartesianIndex(1,2,3), :some_default) === A[1,2,3]
@test get(A, CartesianIndex(2,2,3), :some_default) === :some_default
@test get(11:15, CartesianIndex(6), nothing) === nothing
@test get(11:15, CartesianIndex(5), nothing) === 15
end
@testset "IndexStyle for various types" begin
@test Base.IndexStyle(UpperTriangular) == IndexCartesian() # subtype of AbstractArray, not of Array
@test Base.IndexStyle(Vector) == IndexLinear()
@test Base.IndexStyle(UnitRange) == IndexLinear()
@test Base.IndexStyle(UpperTriangular(rand(3, 3)), [1; 2; 3]) == IndexCartesian()
@test Base.IndexStyle(UpperTriangular(rand(3, 3)), rand(3, 3), [1; 2; 3]) == IndexCartesian()
@test Base.IndexStyle(rand(3, 3), [1; 2; 3]) == IndexLinear()
end
@testset "promote_shape for Tuples and Dims" begin
@test promote_shape((2, 1), (2,)) == (2, 1)
@test_throws DimensionMismatch promote_shape((2, 3), (2,))
@test promote_shape(Dims((2, 1)), Dims((2,))) == (2, 1)
@test_throws DimensionMismatch promote_shape(Dims((2, 2)), Dims((2,)))
@test_throws DimensionMismatch promote_shape(Dims((2, 3, 1)), Dims((2,2)))
end
@testset "getindex and setindex! for Ref" begin
for x in [Ref(1), Ref([1,2,3], 1)]
@test getindex(x) == getindex(x, CartesianIndex()) == 1
x[CartesianIndex()] = 10
@test getindex(x) == getindex(x, CartesianIndex()) == 10
end
end
@testset "vcat with mixed elements" begin
@test vcat(Nothing[], [missing], [1.0], [Int8(1)]) isa Vector{Union{Missing, Nothing, Float64}}
end
@testset "sizeof" begin
let arrUInt8 = zeros(UInt8, 10)
@test sizeof(arrUInt8) == 10
@test Core.sizeof(arrUInt8) == 10
end
let arrUInt32 = zeros(UInt32, 10)
@test sizeof(arrUInt32) == 40
@test Core.sizeof(arrUInt32) == 40
end
let arrFloat64 = zeros(Float64, 10, 10)
@test sizeof(arrFloat64) == 800
@test Core.sizeof(arrFloat64) == 800
end
# Test union arrays (Issue #23321)
let arrUnion = Union{Int64, Cvoid}[rand(Bool) ? k : nothing for k = 1:10]
@test sizeof(arrUnion) == 80
@test Core.sizeof(arrUnion) == 80
end
# Test non-power of 2 types (Issue #35884)
primitive type UInt48 48 end
UInt48(x::UInt64) = Core.Intrinsics.trunc_int(UInt48, x)
UInt48(x::UInt32) = Core.Intrinsics.zext_int(UInt48, x)
a = UInt48(0x00000001);
b = UInt48(0x00000002);
c = UInt48(0x00000003);
let arrayOfUInt48 = [a, b, c]
f35884(x) = sizeof(x)
@test f35884(arrayOfUInt48) == 24
@test Core.sizeof(arrayOfUInt48) == 24
end
end
struct Strider{T,N} <: AbstractArray{T,N}
data::Vector{T}
offset::Int
strides::NTuple{N,Int}
size::NTuple{N,Int}
end
function Strider{T}(strides::NTuple{N}, size::NTuple{N}) where {T,N}
offset = 1-sum(strides .* (strides .< 0) .* (size .- 1))
data = Array{T}(undef, sum(abs.(strides) .* (size .- 1)) + 1)
return Strider{T, N, Vector{T}}(data, offset, strides, size)
end
function Strider(vec::AbstractArray{T}, strides::NTuple{N}, size::NTuple{N}) where {T,N}
offset = 1-sum(strides .* (strides .< 0) .* (size .- 1))
@assert length(vec) >= sum(abs.(strides) .* (size .- 1)) + 1
return Strider{T, N}(vec, offset, strides, size)
end
Base.size(S::Strider) = S.size
function Base.getindex(S::Strider{<:Any,N}, I::Vararg{Int,N}) where {N}
return S.data[sum(S.strides .* (I .- 1)) + S.offset]