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array.jl
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# This file is a part of Julia. License is MIT: https://julialang.org/license
## array.jl: Dense arrays
"""
DimensionMismatch([msg])
The objects called do not have matching dimensionality. Optional argument `msg` is a
descriptive error string.
"""
struct DimensionMismatch <: Exception
msg::AbstractString
end
DimensionMismatch() = DimensionMismatch("")
## Type aliases for convenience ##
"""
AbstractVector{T}
Supertype for one-dimensional arrays (or array-like types) with
elements of type `T`. Alias for [`AbstractArray{T,1}`](@ref).
"""
const AbstractVector{T} = AbstractArray{T,1}
"""
AbstractMatrix{T}
Supertype for two-dimensional arrays (or array-like types) with
elements of type `T`. Alias for [`AbstractArray{T,2}`](@ref).
"""
const AbstractMatrix{T} = AbstractArray{T,2}
"""
AbstractVecOrMat{T}
Union type of [`AbstractVector{T}`](@ref) and [`AbstractMatrix{T}`](@ref).
"""
const AbstractVecOrMat{T} = Union{AbstractVector{T}, AbstractMatrix{T}}
const RangeIndex = Union{Int, AbstractRange{Int}, AbstractUnitRange{Int}}
const DimOrInd = Union{Integer, AbstractUnitRange}
const IntOrInd = Union{Int, AbstractUnitRange}
const DimsOrInds{N} = NTuple{N,DimOrInd}
const NeedsShaping = Union{Tuple{Integer,Vararg{Integer}}, Tuple{OneTo,Vararg{OneTo}}}
"""
Array{T,N} <: AbstractArray{T,N}
`N`-dimensional dense array with elements of type `T`.
"""
Array
"""
Vector{T} <: AbstractVector{T}
One-dimensional dense array with elements of type `T`, often used to represent
a mathematical vector. Alias for [`Array{T,1}`](@ref).
"""
const Vector{T} = Array{T,1}
"""
Matrix{T} <: AbstractMatrix{T}
Two-dimensional dense array with elements of type `T`, often used to represent
a mathematical matrix. Alias for [`Array{T,2}`](@ref).
"""
const Matrix{T} = Array{T,2}
"""
VecOrMat{T}
Union type of [`Vector{T}`](@ref) and [`Matrix{T}`](@ref).
"""
const VecOrMat{T} = Union{Vector{T}, Matrix{T}}
"""
DenseArray{T, N} <: AbstractArray{T,N}
`N`-dimensional dense array with elements of type `T`.
The elements of a dense array are stored contiguously in memory.
"""
DenseArray
"""
DenseVector{T}
One-dimensional [`DenseArray`](@ref) with elements of type `T`. Alias for `DenseArray{T,1}`.
"""
const DenseVector{T} = DenseArray{T,1}
"""
DenseMatrix{T}
Two-dimensional [`DenseArray`](@ref) with elements of type `T`. Alias for `DenseArray{T,2}`.
"""
const DenseMatrix{T} = DenseArray{T,2}
"""
DenseVecOrMat{T}
Union type of [`DenseVector{T}`](@ref) and [`DenseMatrix{T}`](@ref).
"""
const DenseVecOrMat{T} = Union{DenseVector{T}, DenseMatrix{T}}
## Basic functions ##
"""
eltype(type)
Determine the type of the elements generated by iterating a collection of the given `type`.
For dictionary types, this will be a `Pair{KeyType,ValType}`. The definition
`eltype(x) = eltype(typeof(x))` is provided for convenience so that instances can be passed
instead of types. However the form that accepts a type argument should be defined for new
types.
# Examples
```jldoctest
julia> eltype(fill(1f0, (2,2)))
Float32
julia> eltype(fill(0x1, (2,2)))
UInt8
```
"""
eltype(::Type) = Any
eltype(::Type{Bottom}) = throw(ArgumentError("Union{} does not have elements"))
eltype(x) = eltype(typeof(x))
import Core: arraysize, arrayset, arrayref, const_arrayref
vect() = Vector{Any}()
vect(X::T...) where {T} = T[ X[i] for i = 1:length(X) ]
"""
vect(X...)
Create a [`Vector`](@ref) with element type computed from the `promote_typeof` of the argument,
containing the argument list.
# Examples
```jldoctest
julia> a = Base.vect(UInt8(1), 2.5, 1//2)
3-element Vector{Float64}:
1.0
2.5
0.5
```
"""
function vect(X...)
T = promote_typeof(X...)
#T[ X[i] for i=1:length(X) ]
# TODO: this is currently much faster. should figure out why. not clear.
return copyto!(Vector{T}(undef, length(X)), X)
end
size(a::Array, d::Integer) = arraysize(a, convert(Int, d))
size(a::Vector) = (arraysize(a,1),)
size(a::Matrix) = (arraysize(a,1), arraysize(a,2))
size(a::Array{<:Any,N}) where {N} = (@_inline_meta; ntuple(M -> size(a, M), Val(N))::Dims)
asize_from(a::Array, n) = n > ndims(a) ? () : (arraysize(a,n), asize_from(a, n+1)...)
allocatedinline(T::Type) = (@_pure_meta; ccall(:jl_stored_inline, Cint, (Any,), T) != Cint(0))
"""
Base.isbitsunion(::Type{T})
Return whether a type is an "is-bits" Union type, meaning each type included in a Union is [`isbitstype`](@ref).
# Examples
```jldoctest
julia> Base.isbitsunion(Union{Float64, UInt8})
true
julia> Base.isbitsunion(Union{Float64, String})
false
```
"""
isbitsunion(u::Union) = allocatedinline(u)
isbitsunion(x) = false
function _unsetindex!(A::Array{T}, i::Int) where {T}
@_inline_meta
@boundscheck checkbounds(A, i)
t = @_gc_preserve_begin A
p = Ptr{Ptr{Cvoid}}(pointer(A, i))
if !allocatedinline(T)
unsafe_store!(p, C_NULL)
elseif T isa DataType
if !datatype_pointerfree(T)
for j = 1:(Core.sizeof(T) ÷ Core.sizeof(Ptr{Cvoid}))
unsafe_store!(p, C_NULL, j)
end
end
end
@_gc_preserve_end t
return A
end
"""
Base.bitsunionsize(U::Union)
For a `Union` of [`isbitstype`](@ref) types, return the size of the largest type; assumes `Base.isbitsunion(U) == true`.
# Examples
```jldoctest
julia> Base.bitsunionsize(Union{Float64, UInt8})
0x0000000000000008
julia> Base.bitsunionsize(Union{Float64, UInt8, Int128})
0x0000000000000010
```
"""
function bitsunionsize(u::Union)
isinline, sz, _ = uniontype_layout(u)
@assert isinline
return sz
end
length(a::Array) = arraylen(a)
elsize(::Type{<:Array{T}}) where {T} = aligned_sizeof(T)
sizeof(a::Array) = Core.sizeof(a)
function isassigned(a::Array, i::Int...)
@_inline_meta
ii = (_sub2ind(size(a), i...) % UInt) - 1
@boundscheck ii < length(a) % UInt || return false
ccall(:jl_array_isassigned, Cint, (Any, UInt), a, ii) == 1
end
## copy ##
"""
unsafe_copyto!(dest::Ptr{T}, src::Ptr{T}, N)
Copy `N` elements from a source pointer to a destination, with no checking. The size of an
element is determined by the type of the pointers.
The `unsafe` prefix on this function indicates that no validation is performed on the
pointers `dest` and `src` to ensure that they are valid. Incorrect usage may corrupt or
segfault your program, in the same manner as C.
"""
function unsafe_copyto!(dest::Ptr{T}, src::Ptr{T}, n) where T
# Do not use this to copy data between pointer arrays.
# It can't be made safe no matter how carefully you checked.
ccall(:memmove, Ptr{Cvoid}, (Ptr{Cvoid}, Ptr{Cvoid}, Csize_t),
dest, src, n * aligned_sizeof(T))
return dest
end
function _unsafe_copyto!(dest, doffs, src, soffs, n)
destp = pointer(dest, doffs)
srcp = pointer(src, soffs)
@inbounds if destp < srcp || destp > srcp + n
for i = 1:n
if isassigned(src, soffs + i - 1)
dest[doffs + i - 1] = src[soffs + i - 1]
else
_unsetindex!(dest, doffs + i - 1)
end
end
else
for i = n:-1:1
if isassigned(src, soffs + i - 1)
dest[doffs + i - 1] = src[soffs + i - 1]
else
_unsetindex!(dest, doffs + i - 1)
end
end
end
return dest
end
"""
unsafe_copyto!(dest::Array, do, src::Array, so, N)
Copy `N` elements from a source array to a destination, starting at offset `so` in the
source and `do` in the destination (1-indexed).
The `unsafe` prefix on this function indicates that no validation is performed to ensure
that N is inbounds on either array. Incorrect usage may corrupt or segfault your program, in
the same manner as C.
"""
function unsafe_copyto!(dest::Array{T}, doffs, src::Array{T}, soffs, n) where T
t1 = @_gc_preserve_begin dest
t2 = @_gc_preserve_begin src
destp = pointer(dest, doffs)
srcp = pointer(src, soffs)
if !allocatedinline(T)
ccall(:jl_array_ptr_copy, Cvoid, (Any, Ptr{Cvoid}, Any, Ptr{Cvoid}, Int),
dest, destp, src, srcp, n)
elseif isbitstype(T)
ccall(:memmove, Ptr{Cvoid}, (Ptr{Cvoid}, Ptr{Cvoid}, Csize_t),
destp, srcp, n * aligned_sizeof(T))
elseif isbitsunion(T)
ccall(:memmove, Ptr{Cvoid}, (Ptr{Cvoid}, Ptr{Cvoid}, Csize_t),
destp, srcp, n * aligned_sizeof(T))
# copy selector bytes
ccall(:memmove, Ptr{Cvoid}, (Ptr{Cvoid}, Ptr{Cvoid}, Csize_t),
ccall(:jl_array_typetagdata, Ptr{UInt8}, (Any,), dest) + doffs - 1,
ccall(:jl_array_typetagdata, Ptr{UInt8}, (Any,), src) + soffs - 1,
n)
else
_unsafe_copyto!(dest, doffs, src, soffs, n)
end
@_gc_preserve_end t2
@_gc_preserve_end t1
return dest
end
unsafe_copyto!(dest::Array, doffs, src::Array, soffs, n) =
_unsafe_copyto!(dest, doffs, src, soffs, n)
"""
copyto!(dest, do, src, so, N)
Copy `N` elements from collection `src` starting at offset `so`, to array `dest` starting at
offset `do`. Return `dest`.
"""
function copyto!(dest::Array, doffs::Integer, src::Array, soffs::Integer, n::Integer)
return _copyto_impl!(dest, doffs, src, soffs, n)
end
# this is only needed to avoid possible ambiguities with methods added in some packages
function copyto!(dest::Array{T}, doffs::Integer, src::Array{T}, soffs::Integer, n::Integer) where T
return _copyto_impl!(dest, doffs, src, soffs, n)
end
function _copyto_impl!(dest::Array, doffs::Integer, src::Array, soffs::Integer, n::Integer)
n == 0 && return dest
n > 0 || _throw_argerror()
if soffs < 1 || doffs < 1 || soffs+n-1 > length(src) || doffs+n-1 > length(dest)
throw(BoundsError())
end
unsafe_copyto!(dest, doffs, src, soffs, n)
return dest
end
# Outlining this because otherwise a catastrophic inference slowdown
# occurs, see discussion in #27874.
# It is also mitigated by using a constant string.
function _throw_argerror()
@_noinline_meta
throw(ArgumentError("Number of elements to copy must be nonnegative."))
end
copyto!(dest::Array, src::Array) = copyto!(dest, 1, src, 1, length(src))
# also to avoid ambiguities in packages
copyto!(dest::Array{T}, src::Array{T}) where {T} = copyto!(dest, 1, src, 1, length(src))
# N.B: The generic definition in multidimensional.jl covers, this, this is just here
# for bootstrapping purposes.
function fill!(dest::Array{T}, x) where T
xT = convert(T, x)
for i in eachindex(dest)
@inbounds dest[i] = xT
end
return dest
end
"""
copy(x)
Create a shallow copy of `x`: the outer structure is copied, but not all internal values.
For example, copying an array produces a new array with identically-same elements as the
original.
"""
copy
copy(a::T) where {T<:Array} = ccall(:jl_array_copy, Ref{T}, (Any,), a)
## Constructors ##
similar(a::Array{T,1}) where {T} = Vector{T}(undef, size(a,1))
similar(a::Array{T,2}) where {T} = Matrix{T}(undef, size(a,1), size(a,2))
similar(a::Array{T,1}, S::Type) where {T} = Vector{S}(undef, size(a,1))
similar(a::Array{T,2}, S::Type) where {T} = Matrix{S}(undef, size(a,1), size(a,2))
similar(a::Array{T}, m::Int) where {T} = Vector{T}(undef, m)
similar(a::Array, T::Type, dims::Dims{N}) where {N} = Array{T,N}(undef, dims)
similar(a::Array{T}, dims::Dims{N}) where {T,N} = Array{T,N}(undef, dims)
# T[x...] constructs Array{T,1}
"""
getindex(type[, elements...])
Construct a 1-d array of the specified type. This is usually called with the syntax
`Type[]`. Element values can be specified using `Type[a,b,c,...]`.
# Examples
```jldoctest
julia> Int8[1, 2, 3]
3-element Vector{Int8}:
1
2
3
julia> getindex(Int8, 1, 2, 3)
3-element Vector{Int8}:
1
2
3
```
"""
function getindex(::Type{T}, vals...) where T
a = Vector{T}(undef, length(vals))
@inbounds for i = 1:length(vals)
a[i] = vals[i]
end
return a
end
getindex(::Type{T}) where {T} = (@_inline_meta; Vector{T}())
getindex(::Type{T}, x) where {T} = (@_inline_meta; a = Vector{T}(undef, 1); @inbounds a[1] = x; a)
getindex(::Type{T}, x, y) where {T} = (@_inline_meta; a = Vector{T}(undef, 2); @inbounds (a[1] = x; a[2] = y); a)
getindex(::Type{T}, x, y, z) where {T} = (@_inline_meta; a = Vector{T}(undef, 3); @inbounds (a[1] = x; a[2] = y; a[3] = z); a)
function getindex(::Type{Any}, @nospecialize vals...)
a = Vector{Any}(undef, length(vals))
@inbounds for i = 1:length(vals)
a[i] = vals[i]
end
return a
end
getindex(::Type{Any}) = Vector{Any}()
function fill!(a::Union{Array{UInt8}, Array{Int8}}, x::Integer)
ccall(:memset, Ptr{Cvoid}, (Ptr{Cvoid}, Cint, Csize_t), a, convert(eltype(a), x), length(a))
return a
end
to_dim(d::Integer) = d
to_dim(d::OneTo) = last(d)
"""
fill(x, dims::Tuple)
fill(x, dims...)
Create an array filled with the value `x`. For example, `fill(1.0, (5,5))` returns a 5×5
array of floats, with each element initialized to `1.0`.
`dims` may be specified as either a tuple or a sequence of arguments. For example,
the common idiom `fill(x)` creates a zero-dimensional array containing the single value `x`.
# Examples
```jldoctest
julia> fill(1.0, (2,3))
2×3 Matrix{Float64}:
1.0 1.0 1.0
1.0 1.0 1.0
julia> fill(42)
0-dimensional Array{Int64, 0}:
42
```
If `x` is an object reference, all elements will refer to the same object:
```jldoctest
julia> A = fill(zeros(2), 2);
julia> A[1][1] = 42; # modifies both A[1][1] and A[2][1]
julia> A
2-element Vector{Vector{Float64}}:
[42.0, 0.0]
[42.0, 0.0]
```
"""
function fill end
fill(v, dims::DimOrInd...) = fill(v, dims)
fill(v, dims::NTuple{N, Union{Integer, OneTo}}) where {N} = fill(v, map(to_dim, dims))
fill(v, dims::NTuple{N, Integer}) where {N} = (a=Array{typeof(v),N}(undef, dims); fill!(a, v); a)
fill(v, dims::Tuple{}) = (a=Array{typeof(v),0}(undef, dims); fill!(a, v); a)
"""
zeros([T=Float64,] dims::Tuple)
zeros([T=Float64,] dims...)
Create an `Array`, with element type `T`, of all zeros with size specified by `dims`.
See also [`fill`](@ref), [`ones`](@ref).
# Examples
```jldoctest
julia> zeros(1)
1-element Vector{Float64}:
0.0
julia> zeros(Int8, 2, 3)
2×3 Matrix{Int8}:
0 0 0
0 0 0
```
"""
function zeros end
"""
ones([T=Float64,] dims::Tuple)
ones([T=Float64,] dims...)
Create an `Array`, with element type `T`, of all ones with size specified by `dims`.
See also: [`fill`](@ref), [`zeros`](@ref).
# Examples
```jldoctest
julia> ones(1,2)
1×2 Matrix{Float64}:
1.0 1.0
julia> ones(ComplexF64, 2, 3)
2×3 Matrix{ComplexF64}:
1.0+0.0im 1.0+0.0im 1.0+0.0im
1.0+0.0im 1.0+0.0im 1.0+0.0im
```
"""
function ones end
for (fname, felt) in ((:zeros, :zero), (:ones, :one))
@eval begin
$fname(dims::DimOrInd...) = $fname(dims)
$fname(::Type{T}, dims::DimOrInd...) where {T} = $fname(T, dims)
$fname(dims::Tuple{Vararg{DimOrInd}}) = $fname(Float64, dims)
$fname(::Type{T}, dims::NTuple{N, Union{Integer, OneTo}}) where {T,N} = $fname(T, map(to_dim, dims))
function $fname(::Type{T}, dims::NTuple{N, Integer}) where {T,N}
a = Array{T,N}(undef, dims)
fill!(a, $felt(T))
return a
end
function $fname(::Type{T}, dims::Tuple{}) where {T}
a = Array{T}(undef)
fill!(a, $felt(T))
return a
end
end
end
function _one(unit::T, x::AbstractMatrix) where T
require_one_based_indexing(x)
m,n = size(x)
m==n || throw(DimensionMismatch("multiplicative identity defined only for square matrices"))
# Matrix{T}(I, m, m)
I = zeros(T, m, m)
for i in 1:m
I[i,i] = unit
end
I
end
one(x::AbstractMatrix{T}) where {T} = _one(one(T), x)
oneunit(x::AbstractMatrix{T}) where {T} = _one(oneunit(T), x)
## Conversions ##
convert(::Type{T}, a::AbstractArray) where {T<:Array} = a isa T ? a : T(a)
promote_rule(a::Type{Array{T,n}}, b::Type{Array{S,n}}) where {T,n,S} = el_same(promote_type(T,S), a, b)
## Constructors ##
if nameof(@__MODULE__) === :Base # avoid method overwrite
# constructors should make copies
Array{T,N}(x::AbstractArray{S,N}) where {T,N,S} = copyto_axcheck!(Array{T,N}(undef, size(x)), x)
AbstractArray{T,N}(A::AbstractArray{S,N}) where {T,N,S} = copyto_axcheck!(similar(A,T), A)
end
## copying iterators to containers
"""
collect(element_type, collection)
Return an `Array` with the given element type of all items in a collection or iterable.
The result has the same shape and number of dimensions as `collection`.
# Examples
```jldoctest
julia> collect(Float64, 1:2:5)
3-element Vector{Float64}:
1.0
3.0
5.0
```
"""
collect(::Type{T}, itr) where {T} = _collect(T, itr, IteratorSize(itr))
_collect(::Type{T}, itr, isz::HasLength) where {T} = copyto!(Vector{T}(undef, Int(length(itr)::Integer)), itr)
_collect(::Type{T}, itr, isz::HasShape) where {T} = copyto!(similar(Array{T}, axes(itr)), itr)
function _collect(::Type{T}, itr, isz::SizeUnknown) where T
a = Vector{T}()
for x in itr
push!(a,x)
end
return a
end
# make a collection similar to `c` and appropriate for collecting `itr`
_similar_for(c::AbstractArray, ::Type{T}, itr, ::SizeUnknown) where {T} = similar(c, T, 0)
_similar_for(c::AbstractArray, ::Type{T}, itr, ::HasLength) where {T} =
similar(c, T, Int(length(itr)::Integer))
_similar_for(c::AbstractArray, ::Type{T}, itr, ::HasShape) where {T} =
similar(c, T, axes(itr))
_similar_for(c, ::Type{T}, itr, isz) where {T} = similar(c, T)
"""
collect(collection)
Return an `Array` of all items in a collection or iterator. For dictionaries, returns
`Pair{KeyType, ValType}`. If the argument is array-like or is an iterator with the
[`HasShape`](@ref IteratorSize) trait, the result will have the same shape
and number of dimensions as the argument.
# Examples
```jldoctest
julia> collect(1:2:13)
7-element Vector{Int64}:
1
3
5
7
9
11
13
```
"""
collect(itr) = _collect(1:1 #= Array =#, itr, IteratorEltype(itr), IteratorSize(itr))
collect(A::AbstractArray) = _collect_indices(axes(A), A)
collect_similar(cont, itr) = _collect(cont, itr, IteratorEltype(itr), IteratorSize(itr))
_collect(cont, itr, ::HasEltype, isz::Union{HasLength,HasShape}) =
copyto!(_similar_for(cont, eltype(itr), itr, isz), itr)
function _collect(cont, itr, ::HasEltype, isz::SizeUnknown)
a = _similar_for(cont, eltype(itr), itr, isz)
for x in itr
push!(a,x)
end
return a
end
_collect_indices(::Tuple{}, A) = copyto!(Array{eltype(A),0}(undef), A)
_collect_indices(indsA::Tuple{Vararg{OneTo}}, A) =
copyto!(Array{eltype(A)}(undef, length.(indsA)), A)
function _collect_indices(indsA, A)
B = Array{eltype(A)}(undef, length.(indsA))
copyto!(B, CartesianIndices(axes(B)), A, CartesianIndices(indsA))
end
# define this as a macro so that the call to Core.Compiler
# gets inlined into the caller before recursion detection
# gets a chance to see it, so that recursive calls to the caller
# don't trigger the inference limiter
if isdefined(Core, :Compiler)
macro default_eltype(itr)
I = esc(itr)
return quote
if $I isa Generator && ($I).f isa Type
($I).f
else
Core.Compiler.return_type(first, Tuple{typeof($I)})
end
end
end
else
macro default_eltype(itr)
I = esc(itr)
return quote
if $I isa Generator && ($I).f isa Type
($I).f
else
Any
end
end
end
end
_array_for(::Type{T}, itr, ::HasLength) where {T} = Vector{T}(undef, Int(length(itr)::Integer))
_array_for(::Type{T}, itr, ::HasShape{N}) where {T,N} = similar(Array{T,N}, axes(itr))
function collect(itr::Generator)
isz = IteratorSize(itr.iter)
et = @default_eltype(itr)
if isa(isz, SizeUnknown)
return grow_to!(Vector{et}(), itr)
else
y = iterate(itr)
if y === nothing
return _array_for(et, itr.iter, isz)
end
v1, st = y
collect_to_with_first!(_array_for(typeof(v1), itr.iter, isz), v1, itr, st)
end
end
_collect(c, itr, ::EltypeUnknown, isz::SizeUnknown) =
grow_to!(_similar_for(c, @default_eltype(itr), itr, isz), itr)
function _collect(c, itr, ::EltypeUnknown, isz::Union{HasLength,HasShape})
y = iterate(itr)
if y === nothing
return _similar_for(c, @default_eltype(itr), itr, isz)
end
v1, st = y
collect_to_with_first!(_similar_for(c, typeof(v1), itr, isz), v1, itr, st)
end
function collect_to_with_first!(dest::AbstractArray, v1, itr, st)
i1 = first(LinearIndices(dest))
dest[i1] = v1
return collect_to!(dest, itr, i1+1, st)
end
function collect_to_with_first!(dest, v1, itr, st)
push!(dest, v1)
return grow_to!(dest, itr, st)
end
function setindex_widen_up_to(dest::AbstractArray{T}, el, i) where T
@_inline_meta
new = similar(dest, promote_typejoin(T, typeof(el)))
f = first(LinearIndices(dest))
copyto!(new, first(LinearIndices(new)), dest, f, i-f)
@inbounds new[i] = el
return new
end
function collect_to!(dest::AbstractArray{T}, itr, offs, st) where T
# collect to dest array, checking the type of each result. if a result does not
# match, widen the result type and re-dispatch.
i = offs
while true
y = iterate(itr, st)
y === nothing && break
el, st = y
if el isa T || typeof(el) === T
@inbounds dest[i] = el::T
i += 1
else
new = setindex_widen_up_to(dest, el, i)
return collect_to!(new, itr, i+1, st)
end
end
return dest
end
function grow_to!(dest, itr)
y = iterate(itr)
y === nothing && return dest
dest2 = empty(dest, typeof(y[1]))
push!(dest2, y[1])
grow_to!(dest2, itr, y[2])
end
function push_widen(dest, el)
@_inline_meta
new = sizehint!(empty(dest, promote_typejoin(eltype(dest), typeof(el))), length(dest))
if new isa AbstractSet
# TODO: merge back these two branches when copy! is re-enabled for sets/vectors
union!(new, dest)
else
append!(new, dest)
end
push!(new, el)
return new
end
function grow_to!(dest, itr, st)
T = eltype(dest)
y = iterate(itr, st)
while y !== nothing
el, st = y
if el isa T || typeof(el) === T
push!(dest, el::T)
else
new = push_widen(dest, el)
return grow_to!(new, itr, st)
end
y = iterate(itr, st)
end
return dest
end
## Iteration ##
iterate(A::Array, i=1) = (@_inline_meta; (i % UInt) - 1 < length(A) ? (@inbounds A[i], i + 1) : nothing)
## Indexing: getindex ##
"""
getindex(collection, key...)
Retrieve the value(s) stored at the given key or index within a collection. The syntax
`a[i,j,...]` is converted by the compiler to `getindex(a, i, j, ...)`.
# Examples
```jldoctest
julia> A = Dict("a" => 1, "b" => 2)
Dict{String, Int64} with 2 entries:
"b" => 2
"a" => 1
julia> getindex(A, "a")
1
```
"""
function getindex end
# This is more complicated than it needs to be in order to get Win64 through bootstrap
@eval getindex(A::Array, i1::Int) = arrayref($(Expr(:boundscheck)), A, i1)
@eval getindex(A::Array, i1::Int, i2::Int, I::Int...) = (@_inline_meta; arrayref($(Expr(:boundscheck)), A, i1, i2, I...))
# Faster contiguous indexing using copyto! for UnitRange and Colon
function getindex(A::Array, I::UnitRange{Int})
@_inline_meta
@boundscheck checkbounds(A, I)
lI = length(I)
X = similar(A, lI)
if lI > 0
unsafe_copyto!(X, 1, A, first(I), lI)
end
return X
end
function getindex(A::Array, c::Colon)
lI = length(A)
X = similar(A, lI)
if lI > 0
unsafe_copyto!(X, 1, A, 1, lI)
end
return X
end
# This is redundant with the abstract fallbacks, but needed for bootstrap
function getindex(A::Array{S}, I::AbstractRange{Int}) where S
return S[ A[i] for i in I ]
end
## Indexing: setindex! ##
"""
setindex!(collection, value, key...)
Store the given value at the given key or index within a collection. The syntax `a[i,j,...] =
x` is converted by the compiler to `(setindex!(a, x, i, j, ...); x)`.
"""
function setindex! end
@eval setindex!(A::Array{T}, x, i1::Int) where {T} = arrayset($(Expr(:boundscheck)), A, convert(T,x)::T, i1)
@eval setindex!(A::Array{T}, x, i1::Int, i2::Int, I::Int...) where {T} =
(@_inline_meta; arrayset($(Expr(:boundscheck)), A, convert(T,x)::T, i1, i2, I...))
# This is redundant with the abstract fallbacks but needed and helpful for bootstrap
function setindex!(A::Array, X::AbstractArray, I::AbstractVector{Int})
@_propagate_inbounds_meta
@boundscheck setindex_shape_check(X, length(I))
require_one_based_indexing(X)
X′ = unalias(A, X)
I′ = unalias(A, I)
count = 1
for i in I′
@inbounds x = X′[count]
A[i] = x
count += 1
end
return A
end
# Faster contiguous setindex! with copyto!
function setindex!(A::Array{T}, X::Array{T}, I::UnitRange{Int}) where T
@_inline_meta
@boundscheck checkbounds(A, I)
lI = length(I)
@boundscheck setindex_shape_check(X, lI)
if lI > 0
unsafe_copyto!(A, first(I), X, 1, lI)
end
return A
end
function setindex!(A::Array{T}, X::Array{T}, c::Colon) where T
@_inline_meta
lI = length(A)
@boundscheck setindex_shape_check(X, lI)
if lI > 0
unsafe_copyto!(A, 1, X, 1, lI)
end
return A
end
# efficiently grow an array
_growbeg!(a::Vector, delta::Integer) =
ccall(:jl_array_grow_beg, Cvoid, (Any, UInt), a, delta)
_growend!(a::Vector, delta::Integer) =
ccall(:jl_array_grow_end, Cvoid, (Any, UInt), a, delta)
_growat!(a::Vector, i::Integer, delta::Integer) =
ccall(:jl_array_grow_at, Cvoid, (Any, Int, UInt), a, i - 1, delta)
# efficiently delete part of an array
_deletebeg!(a::Vector, delta::Integer) =
ccall(:jl_array_del_beg, Cvoid, (Any, UInt), a, delta)
_deleteend!(a::Vector, delta::Integer) =
ccall(:jl_array_del_end, Cvoid, (Any, UInt), a, delta)
_deleteat!(a::Vector, i::Integer, delta::Integer) =
ccall(:jl_array_del_at, Cvoid, (Any, Int, UInt), a, i - 1, delta)
## Dequeue functionality ##
"""
push!(collection, items...) -> collection
Insert one or more `items` in `collection`. If `collection` is an ordered container,
the items are inserted at the end (in the given order).
# Examples
```jldoctest
julia> push!([1, 2, 3], 4, 5, 6)
6-element Vector{Int64}:
1
2
3
4
5
6
```
If `collection` is ordered, use [`append!`](@ref) to add all the elements of another
collection to it. The result of the preceding example is equivalent to `append!([1, 2, 3], [4,
5, 6])`. For `AbstractSet` objects, [`union!`](@ref) can be used instead.
"""
function push! end
function push!(a::Array{T,1}, item) where T
# convert first so we don't grow the array if the assignment won't work
itemT = convert(T, item)
_growend!(a, 1)
a[end] = itemT
return a
end
function push!(a::Array{Any,1}, @nospecialize item)
_growend!(a, 1)
arrayset(true, a, item, length(a))
return a
end
"""
append!(collection, collections...) -> collection.
For an ordered container `collection`, add the elements of each `collections`
to the end of it.
!!! compat "Julia 1.6"
Specifying multiple collections to be appended requires at least Julia 1.6.
# Examples
```jldoctest
julia> append!([1], [2, 3])
3-element Vector{Int64}:
1
2
3
julia> append!([1, 2, 3], [4, 5], [6])
6-element Vector{Int64}:
1
2
3
4
5
6
```
Use [`push!`](@ref) to add individual items to `collection` which are not already
themselves in another collection. The result of the preceding example is equivalent to
`push!([1, 2, 3], 4, 5, 6)`.
"""
function append!(a::Vector, items::AbstractVector)
itemindices = eachindex(items)
n = length(itemindices)
_growend!(a, n)
copyto!(a, length(a)-n+1, items, first(itemindices), n)
return a
end
append!(a::AbstractVector, iter) = _append!(a, IteratorSize(iter), iter)
push!(a::AbstractVector, iter...) = append!(a, iter)
append!(a::AbstractVector, iter...) = foldl(append!, iter, init=a)
function _append!(a, ::Union{HasLength,HasShape}, iter)
n = length(a)
i = lastindex(a)
resize!(a, n+Int(length(iter))::Int)
@inbounds for (i, item) in zip(i+1:lastindex(a), iter)
a[i] = item
end
a
end
function _append!(a, ::IteratorSize, iter)