https://github.com/JuliaLang/julia
Tip revision: 4608aba7aef2b3ca52c6d2cb82be38379543fd17 authored by Kristoffer on 03 May 2023, 13:58:41 UTC
add tracy support for inc/dec plots
add tracy support for inc/dec plots
Tip revision: 4608aba
subarray.jl
# This file is a part of Julia. License is MIT: https://julialang.org/license
using Test, Random, LinearAlgebra
######## Utilities ###########
# Generate an array similar to A[indx1, indx2, ...], but only call
# getindex with scalar-valued indices. This will be safe even if
# `getindex` someday calls `view`.
# The "nodrop" variant does not drop any dimensions (not even trailing ones)
function Agen_nodrop(A::AbstractArray, I...)
irep = replace_colon(A, I)
_Agen(A, ensure_iterable(irep)...)
end
# This drops scalar dimensions
function Agen_slice(A::AbstractArray, I...)
irep = replace_colon(A, I)
B = _Agen(A, ensure_iterable(irep)...)
sd = Int[]
for i = 1:length(I)
if isa(I[i], Real)
push!(sd, i)
end
end
dropdims(B, dims=sd)
end
_Agen(A, i1) = [A[j1] for j1 in i1]
_Agen(A, i1, i2) = [A[j1,j2] for j1 in i1, j2 in i2]
_Agen(A, i1, i2, i3) = [A[j1,j2,j3] for j1 in i1, j2 in i2, j3 in i3]
_Agen(A, i1, i2, i3, i4) = [A[j1,j2,j3,j4] for j1 in i1, j2 in i2, j3 in i3, j4 in i4]
_Agen(A, i1, i2, i3, i4, i5) = [A[j1,j2,j3,j4,j5] for j1 in i1, j2 in i2, j3 in i3, j4 in i4, j5 in i5]
_Agen(A, i1, i2, i3, i4, i5, i6) = [A[j1,j2,j3,j4,j5,j6] for j1 in i1, j2 in i2, j3 in i3, j4 in i4, j5 in i5, j6 in i6]
function replace_colon(A::AbstractArray, I)
Iout = Vector{Any}(undef, length(I))
I === (:,) && return (1:length(A),)
for d = 1:length(I)
Iout[d] = isa(I[d], Colon) ? (1:size(A,d)) : I[d]
end
(Iout...,)
end
ensure_iterable(::Tuple{}) = ()
ensure_iterable(t::Tuple{Union{Number, CartesianIndex}, Vararg{Any}}) = ((t[1],), ensure_iterable(Base.tail(t))...)
ensure_iterable(t::Tuple{Any, Vararg{Any}}) = (t[1], ensure_iterable(Base.tail(t))...)
index_ndims(t::Tuple) = tup2val(Base.index_ndims(t))
tup2val(::NTuple{N}) where {N} = Val(N)
# To avoid getting confused by manipulations that are implemented for SubArrays,
# it's good to copy the contents to an Array. This version protects against
# `similar` ever changing its meaning.
function copy_to_array(A::AbstractArray)
Ac = Array{eltype(A)}(undef, size(A))
copyto!(Ac, A)
end
# Discover the highest dimension along which the values in A are
# separated by a single increment. If A was extracted via getindex
# from reshape(1:N, ...), this is equivalent to finding the highest
# dimension of the SubArray consistent with a single stride in the
# parent array.
function single_stride_dim(A::Array)
ld = 0
while ld < ndims(A)
# Collapse all dimensions up to & including ld+1 into the first dimension
shp = [prod(size(A)[1:ld+1])]
for j = ld+2:ndims(A)
push!(shp, size(A,j))
end
Ar = reshape(A, shp...)
# Compute the diff along dimension 1
if size(Ar, 1) > 1
indices = map(d->1:size(Ar,d), [1:ndims(Ar);])
indicesp = copy(indices); indicesp[1] = 2:size(Ar,1)
indicesm = copy(indices); indicesm[1] = 1:size(Ar,1)-1
dA = Ar[indicesp...] - Ar[indicesm...]
ustride = unique(dA[:])
if length(ustride) == 1 # is it a single stride?
ld += 1
else
break
end
else
ld += 1
end
end
ld
end
single_stride_dim(@nospecialize(A)) = single_stride_dim(copy_to_array(A))
# Testing equality of AbstractArrays, using several different methods to access values
function test_cartesian(@nospecialize(A), @nospecialize(B))
isgood = true
for (IA, IB) in zip(CartesianIndices(A), CartesianIndices(B))
@test A[IA] == B[IB]
if A isa StridedArray
v1 = GC.@preserve A unsafe_load(pointer(A.parent, sum((0,(strides(A) .* (IA.I .- 1))...))+Base.first_index(A)))
@test v1 == B[IB]
end
end
end
function test_linear(@nospecialize(A), @nospecialize(B))
@test length(A) == length(B)
isgood = true
for (iA, iB) in zip(1:length(A), 1:length(B))
@test A[iA] == B[iB]
if A isa StridedArray
v1 = GC.@preserve A unsafe_load(pointer(A, iA))
v2 = Ref(A, iA)[]
@test v1 == v2 == B[iB]
end
end
end
# "mixed" means 2 indices even for N-dimensional arrays
test_mixed(::AbstractArray{T,1}, ::Array) where {T} = nothing
test_mixed(::AbstractArray{T,2}, ::Array) where {T} = nothing
test_mixed(A, B::Array) = _test_mixed(A, reshape(B, size(A)))
function _test_mixed(@nospecialize(A), @nospecialize(B))
m = size(A, 1)
n = size(A, 2)
isgood = true
for J in CartesianIndices(size(A)[2:end]), i in 1:m
@test A[i,J] == B[i,J]
end
nothing
end
function test_bounds(@nospecialize(A))
@test_throws BoundsError A[0]
@test_throws BoundsError A[end+1]
trailing2 = ntuple(Returns(1), max(ndims(A)-2, 0))
trailing3 = ntuple(Returns(1), max(ndims(A)-3, 0))
@test_throws BoundsError A[1, 0, trailing2...]
@test_throws BoundsError A[1, end+1, trailing2...]
@test_throws BoundsError A[1, 1, 0, trailing3...]
@test_throws BoundsError A[1, 1, end+1, trailing3...]
@test_throws BoundsError A[0, 1, trailing2...]
@test_throws BoundsError A[end+1, 1, trailing2...]
@test_throws BoundsError A[0, 1, 1, trailing3...]
@test_throws BoundsError A[end+1, 1, 1, trailing3...]
@test_throws BoundsError A[1, 0, 1, trailing3...]
@test_throws BoundsError A[1, end+1, 1, trailing3...]
@test_throws BoundsError A[1, 0]
@test_throws BoundsError A[1, end+1]
@test_throws BoundsError A[1, 1, 0]
@test_throws BoundsError A[1, 1, end+1]
@test_throws BoundsError A[0, 1]
@test_throws BoundsError A[end+1, 1]
@test_throws BoundsError A[0, 1, 1]
@test_throws BoundsError A[end+1, 1, 1]
@test_throws BoundsError A[1, 0, 1]
@test_throws BoundsError A[1, end+1, 1]
end
function dim_break_linindex(I)
i = 1
while i <= length(I) && !isa(I[i], Vector{Int})
i += 1
end
i - 1
end
function runsubarraytests(A::Array, I...)
# Direct test of linear indexing inference
C = Agen_nodrop(A, I...)
ld = min(single_stride_dim(C), dim_break_linindex(I))
S = view(A, I...)
if Base.iscontiguous(S)
@test S.stride1 == 1
end
test_linear(S, C)
test_cartesian(S, C)
test_mixed(S, C)
end
function runsubarraytests(@nospecialize(A), I...)
# When A was created with view, we have to check bounds, since some
# of the "residual" dimensions have size 1. It's possible that we
# need dedicated tests for view.
for d = 1:length(I)-1
if !isa(I[d], Colon) && any(I[d] .> size(A,d))
return nothing
end
end
if !isa(I[end], Colon) && any(I[end] .> prod(size(A)[length(I):end]))
return nothing
end
AA = copy_to_array(A)
# Direct test of linear indexing inference
C = Agen_nodrop(AA, I...)
Cld = ld = min(single_stride_dim(C), dim_break_linindex(I))
Cdim = AIindex = 0
while Cdim <= Cld && AIindex < length(A.indices)
AIindex += 1
if isa(A.indices[AIindex], Real)
ld += 1
else
Cdim += 1
end
end
S = view(A, I...)
test_linear(S, C)
test_cartesian(S, C)
test_mixed(S, C)
end
# indexN is a cartesian index, indexNN is a linear index for 2 dimensions, and indexNNN is a linear index for 3 dimensions
function runviews(SB::AbstractArray, indexN, indexNN, indexNNN)
@assert ndims(SB) > 2
for i3 in indexN, i2 in indexN, i1 in indexN
runsubarraytests(SB, i1, i2, i3, ntuple(Returns(1), max(ndims(SB)-3, 0))...)
end
for i2 in indexN, i1 in indexN
runsubarraytests(SB, i1, i2, ntuple(Returns(1), max(ndims(SB)-2, 0))...)
end
for i1 in indexNNN
runsubarraytests(SB, i1)
end
end
function runviews(SB::AbstractArray{T, 3} where T, indexN, indexNN, indexNNN)
@assert ndims(SB) > 2
for i3 in indexN, i2 in indexN, i1 in indexN
runsubarraytests(SB, i1, i2, i3)
end
for i2 in indexN, i1 in indexN
runsubarraytests(SB, i1, i2, 1)
end
for i1 in indexNNN
runsubarraytests(SB, i1)
end
end
function runviews(SB::AbstractArray{T,2}, indexN, indexNN, indexNNN) where T
for i2 in indexN, i1 in indexN
runsubarraytests(SB, i1, i2)
end
for i1 in indexNN
runsubarraytests(SB, i1)
end
end
function runviews(SB::AbstractArray{T,1}, indexN, indexNN, indexNNN) where T
for i1 in indexN
runsubarraytests(SB, i1)
end
end
runviews(SB::AbstractArray{T,0}, indexN, indexNN, indexNNN) where {T} = nothing
######### Tests #########
testfull = Base.get_bool_env("JULIA_TESTFULL", false)
### Views from Arrays ###
index5 = (1, :, 2:5, [4,1,5], reshape([2]), view(1:5,[2 3 4 1])) # all work with at least size 5
index25 = (3, :, 2:11, [19,9,7], reshape([10]), view(1:25,[19 15; 4 24]))
index125 = (113, :, 85:121, [99,14,103], reshape([72]), view(1:125,reshape([25,4,102,67], 1, 2, 2)))
if testfull
let A = copy(reshape(1:5*7*11, 11, 7, 5))
runviews(A, index5, index25, index125)
end
end
### Views from views ###
# "outer" indices create snips that have at least size 5 along each dimension,
# with the exception of Int-slicing
oindex = (:, 6, 3:7, reshape([12]), [8,4,6,12,5,7], [3:7 1:5 2:6 4:8 5:9], reshape(2:11, 2, 5))
_ndims(::AbstractArray{T,N}) where {T,N} = N
_ndims(x) = 1
if testfull
let B = copy(reshape(1:13^3, 13, 13, 13))
@testset "full tests: ($o1,$o2,$o3)" for o3 in oindex, o2 in oindex, o1 in oindex
viewB = view(B, o1, o2, o3)
runviews(viewB, index5, index25, index125)
end
end
end
let B = copy(reshape(1:13^3, 13, 13, 13))
@testset "spot checks: $oind" for oind in (
(:,:,:),
(:,:,6),
(:,6,:),
(6,:,:),
(:,3:7,:),
(3:7,:,:),
(3:7,6,:),
(3:7,6,0x6),
(13:-2:1,:,:),
([8,4,6,12,5,7],:,3:7),
(6,CartesianIndex.(6,[8,4,6,12,5,7])),
(CartesianIndex(13,6),[8,4,6,12,5,7]),
(1,:,view(1:13,[9,12,4,13,1])),
(2,:,reshape(2:11,2,5)),
(2,:,reshape(2:2:13,2,3)),
(3,reshape(2:11,5,2),4),
(3,reshape(2:2:13,3,2),4),
(view(1:13,[9,12,4,13,1]),2:6,4),
([1:5 2:6 3:7 4:8 5:9], :, 3),
)
runsubarraytests(B, oind...)
viewB = view(B, oind...)
runviews(viewB, index5, index25, index125)
end
end
let B = copy(reshape(1:13^3, 13, 13, 13))
@testset "spot checks (other BitIntegers): $oind" for oind in (
(:,:,0x6),
(:,0x00000006,:),
(0x0006,:,:),
(:,0x00000003:0x00000007,:),
(0x0000000000000003:0x0000000000000007,:,:),
(0x0003:0x0007,0x6,:),
(6,UInt(3):UInt(7),3:7),
(Int16(3):Int16(7),Int16(6),:),
(CartesianIndex(0xD,0x6),UInt8[8,4,6,12,5,7]),
(Int8(1),:,view(1:13,[9,12,4,13,1])),
(view(1:13,Int16[9,12,4,13,1]),UInt8(2):UInt16(6),Int8(4)),
(Int8[1:5 2:6 3:7 4:8 5:9],:,UInt64(3)),
)
runsubarraytests(B, oind...)
viewB = view(B, oind...)
runviews(viewB, index5, index25, index125)
end
end
####### "Classical" tests #######
@testset "non-trailing dimensions" begin
A = copy(reshape(1:120, 3, 5, 8))
sA = view(A, 2:2, 1:5, :)
@test @inferred(strides(sA)) == (1, 3, 15)
@test parent(sA) == A
@test parentindices(sA) == (2:2, 1:5, Base.Slice(1:8))
@test size(sA) == (1, 5, 8)
@test axes(sA) === (Base.OneTo(1), Base.OneTo(5), Base.OneTo(8))
@test sA[1, 2, 1:8][:] == [5:15:120;]
sA[2:5:end] .= -1
@test all(sA[2:5:end] .== -1)
@test all(A[5:15:120] .== -1)
@test @inferred(strides(sA)) == (1,3,15)
@test stride(sA,3) == 15
@test stride(sA,4) == 120
test_bounds(sA)
sA = view(A, 1:3, 1:5, 5)
sA[1:3,1:5] .= -2
@test all(A[:,:,5] .== -2)
fill!(sA, -3)
@test all(A[:,:,5] .== -3)
sA[:] .= 4
@test all(A[:,:,5] .== 4)
@test @inferred(strides(sA)) == (1,3)
test_bounds(sA)
sA = view(A, 1:3, 3:3, 2:5)
@test size(sA) == (3,1,4)
@test axes(sA) === (Base.OneTo(3), Base.OneTo(1), Base.OneTo(4))
@test sA == A[1:3,3:3,2:5]
@test sA[:] == A[1:3,3,2:5][:]
test_bounds(sA)
sA = view(A, 1:2:3, 1:3:5, 1:2:8)
@test @inferred(strides(sA)) == (2,9,30)
@test sA[:] == A[1:2:3, 1:3:5, 1:2:8][:]
# issue #8807
@test view(view([1:5;], 1:5), 1:5) == [1:5;]
# Test with mixed types
@test sA[:, Int16[1,2], big(2)] == [31 40; 33 42]
test_bounds(sA)
sA = view(A, 1:1, 1:5, [1 3; 4 2])
@test ndims(sA) == 4
@test axes(sA) === (Base.OneTo(1), Base.OneTo(5), Base.OneTo(2), Base.OneTo(2))
sA = view(A, 1:2, 3, [1 3; 4 2])
@test ndims(sA) == 3
@test axes(sA) === (Base.OneTo(2), Base.OneTo(2), Base.OneTo(2))
end
@testset "logical indexing #4763" begin
A = view([1:10;], 5:8)
@test A[A.<7] == view(A, A.<7) == [5, 6]
@test Base.unsafe_getindex(A, A.<7) == [5, 6]
B = reshape(1:16, 4, 4)
sB = view(B, 2:3, 2:3)
@test sB[sB.>8] == view(sB, sB.>8) == [10, 11]
@test Base.unsafe_getindex(sB, sB.>8) == [10, 11]
end
@testset "with dropped dimensions" begin
A = copy(reshape(1:120, 3, 5, 8))
sA = view(A, 2, :, 1:8)
@test parent(sA) == A
@test parentindices(sA) == (2, Base.Slice(1:5), 1:8)
@test size(sA) == (5, 8)
@test axes(sA) === (Base.OneTo(5), Base.OneTo(8))
@test @inferred(strides(sA)) == (3,15)
@test sA[2, 1:8][:] == [5:15:120;]
@test sA[:,1] == [2:3:14;]
@test sA[2:5:end] == [5:15:110;]
sA[2:5:end] .= -1
@test all(sA[2:5:end] .== -1)
@test all(A[5:15:120] .== -1)
test_bounds(sA)
sA = view(A, 1:3, 1:5, 5)
@test size(sA) == (3,5)
@test axes(sA) === (Base.OneTo(3),Base.OneTo(5))
@test @inferred(strides(sA)) == (1,3)
test_bounds(sA)
sA = view(A, 1:2:3, 3, 1:2:8)
@test size(sA) == (2,4)
@test axes(sA) === (Base.OneTo(2), Base.OneTo(4))
@test @inferred(strides(sA)) == (2,30)
@test sA[:] == A[sA.indices...][:]
test_bounds(sA)
end
@testset "parent" begin
a = [5:8;]
@test parent(a) == a
@test parentindices(a) == (1:4,)
end
@testset "issue #11289" begin
x11289 = randn(5,5)
@test isempty(view(x11289, Int[], :))
@test isempty(view(x11289, [2,5], Int[]))
@test isempty(view(x11289, Int[], 2))
end
@testset "issue #6218 - logical indexing" begin
A = rand(2, 2, 3)
msk = fill(true, 2, 2)
msk[2,1] = false
sA = view(A, :, :, 1)
sA[msk] .= 1.0
@test sA[msk] == fill(1, count(msk))
end
@testset "bounds checking upon construction; see #4044, #10296" begin
@test_throws BoundsError view(1:10, 8:11)
A = reshape(1:20, 5, 4)
sA = view(A, 1:2, 1:3)
@test_throws BoundsError view(sA, 1:3, 1:3)
@test_throws BoundsError view(sA, 1:2, 1:4)
view(sA, 1:2, 1:2)
@test_throws BoundsError view(A, 17:23)
view(A, 17:20)
end
@testset "Linear indexing by one multidimensional array" begin
A = reshape(1:120, 3, 5, 8)
sA = view(A, :, :, :)
@test sA[[72 17; 107 117]] == [72 17; 107 117]
@test sA[[99 38 119 14 76 81]] == [99 38 119 14 76 81]
@test sA[[fill(1, (2, 2, 2)); fill(2, (2, 2, 2))]] == [fill(1, (2, 2, 2)); fill(2, (2, 2, 2))]
sA = view(A, 1:2, 2:3, 3:4)
@test sA[(1:8)'] == [34 35 37 38 49 50 52 53]
@test sA[[1 2 4 4; 6 1 1 4]] == [34 35 38 38; 50 34 34 38]
end
@testset "issue #11871" begin
a = fill(1., (2,2))
b = view(a, 1:2, 1:2)
b[2] = 2
@test b[2] === 2.0
end
@testset "issue #15138" begin
a = [1,2,3]
b = view(a, UInt(1):UInt(2))
@test b == view(a, UInt(1):UInt(2)) == view(view(a, :), UInt(1):UInt(2)) == [1,2]
end
@testset "unsigned index" begin
A = reshape(1:4, 2, 2)
B = view(A, :, :)
@test parent(B) === A
@test parent(view(B, 0x1, :)) === parent(view(B, 0x1, :)) === A
end
@testset "issue #15168" begin
A = rand(10)
sA = view(copy(A), :)
@test sA[Int16(1)] === sA[Int32(1)] === sA[Int64(1)] === A[1]
permute!(sA, Vector{Int16}(1:10))
@test A == sA
end
# the following segfaults with LLVM 3.8 on Windows, ref #15417
@test Array(view(view(reshape(1:13^3, 13, 13, 13), 3:7, 6:6, :), 1:2:5, :, 1:2:5)) ==
cat([68,70,72],[406,408,410],[744,746,748]; dims=3)
@testset "@view (and replace_ref_begin_end!)" begin
@test_throws ArgumentError(
"Invalid use of @view macro: argument must be a reference expression A[...]."
) var"@view"(LineNumberNode(@__LINE__), @__MODULE__, 1)
X = reshape(1:24,2,3,4)
Y = 4:-1:1
@test isa(@view(X[1:3]), SubArray)
@test X[begin:end] == @.(@view X[begin:end]) # test compatibility of @. and @view
@test X[begin:end-3] == @view X[begin:end-3]
@test X[1:end,2,begin+1] == @view X[1:end,2,begin+1]
@test X[begin,1:end-2,1] == @view X[begin,1:end-2,1]
@test X[begin,begin+1,begin:end-2] == @view X[begin,begin+1,begin:end-2]
@test X[begin,2,Y[2:end]] == @view X[begin,2,Y[2:end]]
@test X[begin:end,2,Y[begin+1:end]] == @view X[begin:end,2,Y[begin+1:end]]
u = (1,2:3)
@test X[u...,begin+1:end] == @view X[u...,begin+1:end]
@test X[(1,)...,(2,)...,2:end] == @view X[(1,)...,(2,)...,2:end]
# test macro hygiene
let size=(x,y)-> error("should not happen"), Base=nothing
@test X[1:end,2,2] == @view X[1:end,2,2]
end
# test that side effects occur only once
let foo = [X]
@test X[2:end-1] == @view (push!(foo,X)[1])[2:end-1]
@test foo == [X, X]
end
# test @views macro
@views let f!(x) = x[begin:end-1] .+= x[begin+1:end].^2
x = [1,2,3,4]
f!(x)
@test x == [5,11,19,4]
@test x[1:3] isa SubArray
@test x[2] === 11
@test Dict((1:3) => 4)[1:3] === 4
x[1:2] .= 0
@test x == [0,0,19,4]
x[1:2] .= 5:6
@test x == [5,6,19,4]
f!(x[3:end])
@test x == [5,6,35,4]
x[Y[2:3]] .= 7:8
@test x == [5,8,7,4]
x[(3,)..., ()...] += 3
@test x == [5,8,10,4]
i = Int[]
# test that lhs expressions in update operations are evaluated only once:
x[push!(i,4)[1]] += 5
@test x == [5,8,10,9] && i == [4]
x[push!(i,3)[end]] += 2
@test x == [5,8,12,9] && i == [4,3]
@. x[3:end] = 0 # make sure @. works with end expressions in @views
@test x == [5,8,0,0]
end
@views @test isa(X[1:3], SubArray)
@test X[begin:end] == @views X[begin:end]
@test X[begin:end-3] == @views X[begin:end-3]
@test X[1:end,2,begin+1] == @views X[1:end,2,begin+1]
@test X[begin,2,1:end-2] == @views X[begin,2,1:end-2]
@test X[begin,2,Y[2:end]] == @views X[begin,2,Y[2:end]]
@test X[begin:end,2,Y[begin+1:end]] == @views X[begin:end,2,Y[begin+1:end]]
@test X[u...,begin+1:end] == @views X[u...,begin+1:end]
@test X[(1,)...,(2,)...,2:end] == @views X[(1,)...,(2,)...,2:end]
# @views for zero dimensional arrays
A = Array{Int, 0}(undef)
A[] = 2
@test (@views A[]) == 2
# test macro hygiene
let size=(x,y)-> error("should not happen"), Base=nothing
@test X[1:end,2,2] == @views X[1:end,2,2]
end
end
@testset "issue #18034: an isbits, IndexLinear view of an immutable Array" begin
struct ImmutableTestArray{T, N} <: Base.DenseArray{T, N}
end
Base.size(::Union{ImmutableTestArray, Type{ImmutableTestArray}}) = (0, 0)
Base.IndexStyle(::Union{ImmutableTestArray, Type{ImmutableTestArray}}) = Base.IndexLinear()
a = ImmutableTestArray{Float64, 2}()
@test Base.IndexStyle(view(a, :, :)) == Base.IndexLinear()
@test isbits(view(a, :, :))
end
@testset "inference; issue #17351, #25321" begin
@test @inferred(reverse(view([1 2; 3 4], :, 1), dims=1)) == [3, 1]
s = view(reshape(1:6, 2, 3), 1:2, 1:2)
@test @inferred(s[2,2,1]) === 4
A = rand(5,5,5,5)
V = view(A, 1:1 ,:, 1:3, :)
@test @inferred(strides(V)) == (1, 5, 25, 125)
end
@testset "issue #18581: slices with OneTo axes can be linear" begin
A18581 = rand(5, 5)
B18581 = view(A18581, :, axes(A18581,2))
@test IndexStyle(B18581) === IndexLinear()
end
primitive type UInt48 48 end
UInt48(x::UInt64) = Core.Intrinsics.trunc_int(UInt48, x)
UInt48(x::UInt32) = Core.Intrinsics.zext_int(UInt48, x)
@testset "sizeof" begin
@test sizeof(view(zeros(UInt8, 10), 1:4)) == 4
@test sizeof(view(zeros(UInt8, 10), 1:3)) == 3
@test sizeof(view(zeros(Float64, 10, 10), 1:3, 2:6)) == 120
# Test non-power of 2 types (Issue #35884)
a = UInt48(0x00000001);
b = UInt48(0x00000002);
c = UInt48(0x00000003);
arrayOfUInt48 = [a, b, c];
@test sizeof(view(arrayOfUInt48, 1:2)) == 16
@test sizeof(view(Diagonal(zeros(UInt8, 10)), 1:4)) == 4
@test sizeof(view(Diagonal(zeros(UInt8, 10)), 1:3)) == 3
@test sizeof(view(Diagonal(zeros(Float64, 10)), 1:3, 2:6)) == 120
end
@testset "write" begin
io = IOBuffer()
a = UInt48[ UInt48(UInt32(i+j)) for i = 1:5, j = 1:5 ]
@test write(io, view(a, :, 2)) == 40
seekstart(io)
v = Vector{UInt48}(undef, 5)
read!(io, v)
@test v == view(a, :, 2)
seekstart(io)
@test write(io, view(a, 2:5, 1:4)) == 4*4*8
seekstart(io)
v = Matrix{UInt48}(undef, 4, 4)
read!(io, v)
@test v == view(a, 2:5, 1:4)
seekstart(io)
@test write(io, view(a, 5:-1:1, 3)) == 5*8
seekstart(io)
v = Vector{UInt48}(undef, 5)
read!(io, v)
@test v == view(a, 5:-1:1, 3)
seekstart(io)
@test write(io, view(a, 1:2:5, :)) == 3*5*8
seekstart(io)
v = Matrix{UInt48}(undef, 3, 5)
read!(io, v)
@test v == view(a, 1:2:5, :)
end
@testset "unaliascopy trimming; Issue #26263" begin
A = rand(5,5,5,5)
V = view(A, 2:5, :, 2:5, 1:2:5)
@test @inferred(Base.unaliascopy(V)) == V == A[2:5, :, 2:5, 1:2:5]
@test @inferred(sum(Base.unaliascopy(V))) ≈ sum(V) ≈ sum(A[2:5, :, 2:5, 1:2:5])
end
@testset "issue #27632" begin
function _test_27632(A)
for J in CartesianIndices(size(A)[2:end])
A[1, J]
end
nothing
end
# check that this doesn't crash
@test _test_27632(view(ones(Int64, (1, 1, 1)), 1, 1, 1)) === nothing
end
@testset "issue #37199: 1-d views with offset range indices" begin
b = zeros(6, 3)
b[Base.IdentityUnitRange(4:6), 2] .= 3
@test b == [zeros(6, 1) [0,0,0,3,3,3] zeros(6,1)]
b[4, Base.IdentityUnitRange(2:3)] .= 4
@test b == [zeros(6,1) [0,0,0,4,3,3] [0,0,0,4,0,0]]
b[Base.IdentityUnitRange(2:3), :] .= 5
@test b == [zeros(1, 3); fill(5, 2, 3); [zeros(3) [4,3,3] [4,0,0]]]
b[:, Base.IdentityUnitRange(3:3)] .= 6
@test b == [[zeros(1, 2); fill(5, 2, 2); [zeros(3) [4,3,3]]] fill(6, 6)]
A = reshape(1:5*7*11, 11, 7, 5)
inds = (1:4, 2:5, 2, :, fill(3))
offset(x) = x
offset(r::UnitRange) = Base.IdentityUnitRange(r)
for i1 in inds
for i2 in inds
for i3 in inds
vo = @view A[offset(i1), offset(i2), offset(i3)]
v = @view A[i1, i2, i3]
@test first(vo) == first(v) == first(A[i1, i2, i3])
@test collect(A[i1, i2, i3]) == collect(vo) == collect(v)
end
end
end
end
@testset "issue #29608; contiguousness" begin
@test Base.iscontiguous(view(ones(1), 1))
@test Base.iscontiguous(view(ones(10), 1:10))
@test Base.iscontiguous(view(ones(10), :))
end
import InteractiveUtils
@testset "blas-enabled reshaped indices" begin
p = rand(30)
M = view(p, reshape(2:25, 6, 4))
v = rand(4)
@test M isa StridedArray
@test M*v == copy(M)*v
@test (InteractiveUtils.@which M*v) == (InteractiveUtils.@which copy(M)*v)
end
isdefined(Main, :InfiniteArrays) || @eval Main include("testhelpers/InfiniteArrays.jl")
using .Main.InfiniteArrays, Base64
@testset "PR #37741: non-Int sizes" begin
r = BigInt(1):BigInt(100_000_000)^100
v = SubArray(r, (r,))
@test size(v) == (last(r),)
v = SubArray(OneToInf(), (OneToInf(),))
@test size(v) == (Infinity(),)
@test stringmime("text/plain", v; context=(:limit => true)) == "$(Infinity())-element view(::$(OneToInf{Int}), 1:1:$(Infinity())) with eltype $Int with indices 1:1:$(Infinity()):\n 1\n 2\n 3\n 4\n 5\n 6\n 7\n 8\n 9\n 10\n ⋮"
end
@testset "PR #39809: copy on 0-dimensional SubArray" begin
v = [[1]]
s = @view v[1]
@test copy(s) == fill([1])
end
@testset "issue 40314: views of CartesianIndices" begin
c = CartesianIndices((1:2, 1:4))
@test (@view c[c]) === c
for inds in Any[(1:1, 1:2), (1:1:1, 1:2)]
c2 = @view c[inds...]
@test c2 isa CartesianIndices{2}
for i2 in inds[2], i1 in inds[1]
@test c2[i1, i2] == c[i1, i2]
end
end
for inds in Any[(Colon(), 1:2), (Colon(), 1:1:2)]
c2 = @view c[inds...]
@test c2 isa CartesianIndices{2}
for i2 in inds[2], i1 in axes(c, 1)
@test c2[i1, i2] == c[i1, i2]
end
end
end
@testset "issue #41221: view(::Vector, :, 1)" begin
v = randn(3)
@test view(v,:,1) == v
@test parent(view(v,:,1)) === v
@test parent(view(v,2:3,1,1)) === v
@test_throws BoundsError view(v,:,2)
@test_throws BoundsError view(v,:,1,2)
m = randn(4,5).+im
@test view(m, 1:2, 3, 1, 1) == m[1:2, 3]
@test parent(view(m, 1:2, 3, 1, 1)) === m
end