#37666

Committed 04 Nov 2023 02:27AM UTC coverage: 87.924% (+0.09%) from 87.831%

Build # #37666

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Simplify, 16bit PDP-11 isn't going to be supported (#45763)

PDP_ENDIAN isn't used.

Co-authored-by: Viral B. Shah <ViralBShah@users.noreply.github.com>

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91.9

/base/reshapedarray.jl

# This file is a part of Julia. License is MIT: https://julialang.org/license

using  Base.MultiplicativeInverses: SignedMultiplicativeInverse

struct ReshapedArray{T,N,P<:AbstractArray,MI<:Tuple{Vararg{SignedMultiplicativeInverse{Int}}}} <: AbstractArray{T,N}
    parent::P
    dims::NTuple{N,Int}
    mi::MI
end
ReshapedArray(parent::AbstractArray{T}, dims::NTuple{N,Int}, mi) where {T,N} = ReshapedArray{T,N,typeof(parent),typeof(mi)}(parent, dims, mi)

# IndexLinear ReshapedArray
const ReshapedArrayLF{T,N,P<:AbstractArray} = ReshapedArray{T,N,P,Tuple{}}

# Fast iteration on ReshapedArrays: use the parent iterator
struct ReshapedArrayIterator{I,M}
    iter::I
    mi::NTuple{M,SignedMultiplicativeInverse{Int}}
end
ReshapedArrayIterator(A::ReshapedArray) = _rs_iterator(parent(A), A.mi)
function _rs_iterator(P, mi::NTuple{M}) where M
    iter = eachindex(P)
    ReshapedArrayIterator{typeof(iter),M}(iter, mi)
end

struct ReshapedIndex{T}
    parentindex::T
end

# eachindex(A::ReshapedArray) = ReshapedArrayIterator(A)  # TODO: uncomment this line
@inline function iterate(R::ReshapedArrayIterator, i...)
    item, inext = iterate(R.iter, i...)
    ReshapedIndex(item), inext
end
length(R::ReshapedArrayIterator) = length(R.iter)
eltype(::Type{<:ReshapedArrayIterator{I}}) where {I} = @isdefined(I) ? ReshapedIndex{eltype(I)} : Any

## reshape(::Array, ::Dims) returns an Array, except for isbitsunion eltypes (issue #28611)
# reshaping to same # of dimensions
@eval function reshape(a::Array{T,M}, dims::NTuple{N,Int}) where {T,N,M}
    throw_dmrsa(dims, len) =
        throw(DimensionMismatch("new dimensions $(dims) must be consistent with array size $len"))
    len = Core.checked_dims(dims...) # make sure prod(dims) doesn't overflow (and because of the comparison to length(a))
    if len != length(a)
        throw_dmrsa(dims, length(a))
    end
    isbitsunion(T) && return ReshapedArray(a, dims, ())
    if N == M && dims == size(a)
        return a
    end
    ref = a.ref
    if M == 1 && N !== 1
        mem = ref.mem::Memory{T}
        if !(ref === GenericMemoryRef(mem) && len === mem.length)
            mem = ccall(:jl_genericmemory_slice, Memory{T}, (Any, Ptr{Cvoid}, Int), mem, ref.ptr_or_offset, len)
            ref = GenericMemoryRef(mem)::typeof(ref)
        end
    end
    # or we could use `a = Array{T,N}(undef, ntuple(0, Val(N))); a.ref = ref; a.size = dims; return a` here
    return $(Expr(:new, :(Array{T,N}), :ref, :dims))
end


"""
    reshape(A, dims...) -> AbstractArray
    reshape(A, dims) -> AbstractArray

Return an array with the same data as `A`, but with different
dimension sizes or number of dimensions. The two arrays share the same
underlying data, so that the result is mutable if and only if `A` is
mutable, and setting elements of one alters the values of the other.

The new dimensions may be specified either as a list of arguments or
as a shape tuple. At most one dimension may be specified with a `:`,
in which case its length is computed such that its product with all
the specified dimensions is equal to the length of the original array
`A`. The total number of elements must not change.

# Examples
```jldoctest
julia> A = Vector(1:16)
16-element Vector{Int64}:
  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16

julia> reshape(A, (4, 4))
4×4 Matrix{Int64}:
 1  5   9  13
 2  6  10  14
 3  7  11  15
 4  8  12  16

julia> reshape(A, 2, :)
2×8 Matrix{Int64}:
 1  3  5  7   9  11  13  15
 2  4  6  8  10  12  14  16

julia> reshape(1:6, 2, 3)
2×3 reshape(::UnitRange{Int64}, 2, 3) with eltype Int64:
 1  3  5
 2  4  6
```
"""
reshape

reshape(parent::AbstractArray, dims::IntOrInd...) = reshape(parent, dims)
reshape(parent::AbstractArray, shp::Tuple{Union{Integer,OneTo}, Vararg{Union{Integer,OneTo}}}) = reshape(parent, to_shape(shp))
reshape(parent::AbstractArray, dims::Dims)        = _reshape(parent, dims)

# Allow missing dimensions with Colon():
reshape(parent::AbstractVector, ::Colon) = parent
reshape(parent::AbstractVector, ::Tuple{Colon}) = parent
reshape(parent::AbstractArray, dims::Int...) = reshape(parent, dims)
reshape(parent::AbstractArray, dims::Union{Int,Colon}...) = reshape(parent, dims)
reshape(parent::AbstractArray, dims::Tuple{Vararg{Union{Int,Colon}}}) = reshape(parent, _reshape_uncolon(parent, dims))
@inline function _reshape_uncolon(A, dims)
    @noinline throw1(dims) = throw(DimensionMismatch(string("new dimensions $(dims) ",
        "may have at most one omitted dimension specified by `Colon()`")))
    @noinline throw2(A, dims) = throw(DimensionMismatch(string("array size $(length(A)) ",
        "must be divisible by the product of the new dimensions $dims")))
    pre = _before_colon(dims...)
    post = _after_colon(dims...)
    _any_colon(post...) && throw1(dims)
    sz, remainder = divrem(length(A), prod(pre)*prod(post))
    remainder == 0 || throw2(A, dims)
    (pre..., Int(sz), post...)
end
@inline _any_colon() = false
@inline _any_colon(dim::Colon, tail...) = true
@inline _any_colon(dim::Any, tail...) = _any_colon(tail...)
@inline _before_colon(dim::Any, tail...) = (dim, _before_colon(tail...)...)
@inline _before_colon(dim::Colon, tail...) = ()
@inline _after_colon(dim::Any, tail...) =  _after_colon(tail...)
@inline _after_colon(dim::Colon, tail...) = tail

reshape(parent::AbstractArray{T,N}, ndims::Val{N}) where {T,N} = parent
function reshape(parent::AbstractArray, ndims::Val{N}) where N
    reshape(parent, rdims(Val(N), axes(parent)))
end

# Move elements from inds to out until out reaches the desired
# dimensionality N, either filling with OneTo(1) or collapsing the
# product of trailing dims into the last element
rdims_trailing(l, inds...) = length(l) * rdims_trailing(inds...)
rdims_trailing(l) = length(l)
rdims(out::Val{N}, inds::Tuple) where {N} = rdims(ntuple(Returns(OneTo(1)), Val(N)), inds)
rdims(out::Tuple{}, inds::Tuple{}) = () # N == 0, M == 0
rdims(out::Tuple{}, inds::Tuple{Any}) = ()
rdims(out::Tuple{}, inds::NTuple{M,Any}) where {M} = ()
rdims(out::Tuple{Any}, inds::Tuple{}) = out # N == 1, M == 0
rdims(out::NTuple{N,Any}, inds::Tuple{}) where {N} = out # N > 1, M == 0
rdims(out::Tuple{Any}, inds::Tuple{Any}) = inds # N == 1, M == 1
rdims(out::Tuple{Any}, inds::NTuple{M,Any}) where {M} = (oneto(rdims_trailing(inds...)),) # N == 1, M > 1
rdims(out::NTuple{N,Any}, inds::NTuple{N,Any}) where {N} = inds # N > 1, M == N
rdims(out::NTuple{N,Any}, inds::NTuple{M,Any}) where {N,M} = (first(inds), rdims(tail(out), tail(inds))...) # N > 1, M > 1, M != N


# _reshape on Array returns an Array
_reshape(parent::Vector, dims::Dims{1}) = parent
_reshape(parent::Array, dims::Dims{1}) = reshape(parent, dims)
_reshape(parent::Array, dims::Dims) = reshape(parent, dims)

# When reshaping Vector->Vector, don't wrap with a ReshapedArray
function _reshape(v::AbstractVector, dims::Dims{1})
    require_one_based_indexing(v)
    len = dims[1]
    len == length(v) || _throw_dmrs(length(v), "length", len)
    v
end
# General reshape
function _reshape(parent::AbstractArray, dims::Dims)
    n = length(parent)
    prod(dims) == n || _throw_dmrs(n, "size", dims)
    __reshape((parent, IndexStyle(parent)), dims)
end

@noinline function _throw_dmrs(n, str, dims)
    throw(DimensionMismatch("parent has $n elements, which is incompatible with $str $dims"))
end

# Reshaping a ReshapedArray
_reshape(v::ReshapedArray{<:Any,1}, dims::Dims{1}) = _reshape(v.parent, dims)
_reshape(R::ReshapedArray, dims::Dims) = _reshape(R.parent, dims)

function __reshape(p::Tuple{AbstractArray,IndexStyle}, dims::Dims)
    parent = p[1]
    strds = front(size_to_strides(map(length, axes(parent))..., 1))
    strds1 = map(s->max(1,Int(s)), strds)  # for resizing empty arrays
    mi = map(SignedMultiplicativeInverse, strds1)
    ReshapedArray(parent, dims, reverse(mi))
end

function __reshape(p::Tuple{AbstractArray{<:Any,0},IndexCartesian}, dims::Dims)
    parent = p[1]
    ReshapedArray(parent, dims, ())
end

function __reshape(p::Tuple{AbstractArray,IndexLinear}, dims::Dims)
    parent = p[1]
    ReshapedArray(parent, dims, ())
end

size(A::ReshapedArray) = A.dims
length(A::ReshapedArray) = length(parent(A))
similar(A::ReshapedArray, eltype::Type, dims::Dims) = similar(parent(A), eltype, dims)
IndexStyle(::Type{<:ReshapedArrayLF}) = IndexLinear()
parent(A::ReshapedArray) = A.parent
parentindices(A::ReshapedArray) = map(oneto, size(parent(A)))
reinterpret(::Type{T}, A::ReshapedArray, dims::Dims) where {T} = reinterpret(T, parent(A), dims)
elsize(::Type{<:ReshapedArray{<:Any,<:Any,P}}) where {P} = elsize(P)

unaliascopy(A::ReshapedArray) = typeof(A)(unaliascopy(A.parent), A.dims, A.mi)
dataids(A::ReshapedArray) = dataids(A.parent)

@inline ind2sub_rs(ax, ::Tuple{}, i::Int) = (i,)
@inline ind2sub_rs(ax, strds, i) = _ind2sub_rs(ax, strds, i - 1)
@inline _ind2sub_rs(ax, ::Tuple{}, ind) = (ind + first(ax[end]),)
@inline function _ind2sub_rs(ax, strds, ind)
    d, r = divrem(ind, strds[1])
    (_ind2sub_rs(front(ax), tail(strds), r)..., d + first(ax[end]))
end
offset_if_vec(i::Integer, axs::Tuple{<:AbstractUnitRange}) = i + first(axs[1]) - 1
offset_if_vec(i::Integer, axs::Tuple) = i

@inline function isassigned(A::ReshapedArrayLF, index::Int)
    @boundscheck checkbounds(Bool, A, index) || return false
    @inbounds ret = isassigned(parent(A), index)
    ret
end
@inline function isassigned(A::ReshapedArray{T,N}, indices::Vararg{Int, N}) where {T,N}
    @boundscheck checkbounds(Bool, A, indices...) || return false
    axp = axes(A.parent)
    i = offset_if_vec(_sub2ind(size(A), indices...), axp)
    I = ind2sub_rs(axp, A.mi, i)
    @inbounds isassigned(A.parent, I...)
end

@inline function getindex(A::ReshapedArrayLF, index::Int)
    @boundscheck checkbounds(A, index)
    @inbounds ret = parent(A)[index]
    ret
end
@inline function getindex(A::ReshapedArray{T,N}, indices::Vararg{Int,N}) where {T,N}
    @boundscheck checkbounds(A, indices...)
    _unsafe_getindex(A, indices...)
end
@inline function getindex(A::ReshapedArray, index::ReshapedIndex)
    @boundscheck checkbounds(parent(A), index.parentindex)
    @inbounds ret = parent(A)[index.parentindex]
    ret
end

@inline function _unsafe_getindex(A::ReshapedArray{T,N}, indices::Vararg{Int,N}) where {T,N}
    axp = axes(A.parent)
    i = offset_if_vec(_sub2ind(size(A), indices...), axp)
    I = ind2sub_rs(axp, A.mi, i)
    _unsafe_getindex_rs(parent(A), I)
end
@inline _unsafe_getindex_rs(A, i::Integer) = (@inbounds ret = A[i]; ret)
@inline _unsafe_getindex_rs(A, I) = (@inbounds ret = A[I...]; ret)

@inline function setindex!(A::ReshapedArrayLF, val, index::Int)
    @boundscheck checkbounds(A, index)
    @inbounds parent(A)[index] = val
    val
end
@inline function setindex!(A::ReshapedArray{T,N}, val, indices::Vararg{Int,N}) where {T,N}
    @boundscheck checkbounds(A, indices...)
    _unsafe_setindex!(A, val, indices...)
end
@inline function setindex!(A::ReshapedArray, val, index::ReshapedIndex)
    @boundscheck checkbounds(parent(A), index.parentindex)
    @inbounds parent(A)[index.parentindex] = val
    val
end

@inline function _unsafe_setindex!(A::ReshapedArray{T,N}, val, indices::Vararg{Int,N}) where {T,N}
    axp = axes(A.parent)
    i = offset_if_vec(_sub2ind(size(A), indices...), axp)
    @inbounds parent(A)[ind2sub_rs(axes(A.parent), A.mi, i)...] = val
    val
end

# helpful error message for a common failure case
const ReshapedRange{T,N,A<:AbstractRange} = ReshapedArray{T,N,A,Tuple{}}
setindex!(A::ReshapedRange, val, index::Int) = _rs_setindex!_err()
setindex!(A::ReshapedRange{T,N}, val, indices::Vararg{Int,N}) where {T,N} = _rs_setindex!_err()
setindex!(A::ReshapedRange, val, index::ReshapedIndex) = _rs_setindex!_err()

@noinline _rs_setindex!_err() = error("indexed assignment fails for a reshaped range; consider calling collect")

cconvert(::Type{Ptr{T}}, a::ReshapedArray{T}) where {T} = cconvert(Ptr{T}, parent(a))

# Add a few handy specializations to further speed up views of reshaped ranges
const ReshapedUnitRange{T,N,A<:AbstractUnitRange} = ReshapedArray{T,N,A,Tuple{}}
viewindexing(I::Tuple{Slice, ReshapedUnitRange, Vararg{ScalarIndex}}) = IndexLinear()
viewindexing(I::Tuple{ReshapedRange, Vararg{ScalarIndex}}) = IndexLinear()
compute_stride1(s, inds, I::Tuple{ReshapedRange, Vararg{Any}}) = s*step(I[1].parent)
compute_offset1(parent::AbstractVector, stride1::Integer, I::Tuple{ReshapedRange}) =
    (@inline; first(I[1]) - first(axes1(I[1]))*stride1)
substrides(strds::NTuple{N,Int}, I::Tuple{ReshapedUnitRange, Vararg{Any}}) where N =
    (size_to_strides(strds[1], size(I[1])...)..., substrides(tail(strds), tail(I))...)

# cconvert(::Type{<:Ptr}, V::SubArray{T,N,P,<:Tuple{Vararg{Union{RangeIndex,ReshapedUnitRange}}}}) where {T,N,P} = V
function unsafe_convert(::Type{Ptr{S}}, V::SubArray{T,N,P,<:Tuple{Vararg{Union{RangeIndex,ReshapedUnitRange}}}}) where {S,T,N,P}
    parent = V.parent
    p = cconvert(Ptr{T}, parent) # XXX: this should occur in cconvert, the result is not GC-rooted
    Δmem = if _checkcontiguous(Bool, parent)
        (first_index(V) - firstindex(parent)) * elsize(parent)
    else
        _memory_offset(parent, map(first, V.indices)...)
    end
    return Ptr{S}(unsafe_convert(Ptr{T}, p) + Δmem)
end

_checkcontiguous(::Type{Bool}, A::AbstractArray) = false
# `strides(A::DenseArray)` calls `size_to_strides` by default.
# Thus it's OK to assume all `DenseArray`s are contiguously stored.
_checkcontiguous(::Type{Bool}, A::DenseArray) = true
_checkcontiguous(::Type{Bool}, A::ReshapedArray) = _checkcontiguous(Bool, parent(A))
_checkcontiguous(::Type{Bool}, A::FastContiguousSubArray) = _checkcontiguous(Bool, parent(A))

function strides(a::ReshapedArray)
    _checkcontiguous(Bool, a) && return size_to_strides(1, size(a)...)
    apsz::Dims = size(a.parent)
    apst::Dims = strides(a.parent)
    msz, mst, n = merge_adjacent_dim(apsz, apst) # Try to perform "lazy" reshape
    n == ndims(a.parent) && return size_to_strides(mst, size(a)...) # Parent is stridevector like
    return _reshaped_strides(size(a), 1, msz, mst, n, apsz, apst)
end

function _reshaped_strides(::Dims{0}, reshaped::Int, msz::Int, ::Int, ::Int, ::Dims, ::Dims)
    reshaped == msz && return ()
    throw(ArgumentError("Input is not strided."))
end
function _reshaped_strides(sz::Dims, reshaped::Int, msz::Int, mst::Int, n::Int, apsz::Dims, apst::Dims)
    st = reshaped * mst
    reshaped = reshaped * sz[1]
    if length(sz) > 1 && reshaped == msz && sz[2] != 1
        msz, mst, n = merge_adjacent_dim(apsz, apst, n + 1)
        reshaped = 1
    end
    sts = _reshaped_strides(tail(sz), reshaped, msz, mst, n, apsz, apst)
    return (st, sts...)
end

merge_adjacent_dim(::Dims{0}, ::Dims{0}) = 1, 1, 0
merge_adjacent_dim(apsz::Dims{1}, apst::Dims{1}) = apsz[1], apst[1], 1
function merge_adjacent_dim(apsz::Dims{N}, apst::Dims{N}, n::Int = 1) where {N}
    sz, st = apsz[n], apst[n]
    while n < N
        szₙ, stₙ = apsz[n+1], apst[n+1]
        if sz == 1
            sz, st = szₙ, stₙ
        elseif stₙ == st * sz || szₙ == 1
            sz *= szₙ
        else
            break
        end
        n += 1
    end
    return sz, st, n
end

1	# This file is a part of Julia. License is MIT: https://julialang.org/license
2
3	using Base.MultiplicativeInverses: SignedMultiplicativeInverse
4
5	struct ReshapedArray{T,N,P<:AbstractArray,MI<:Tuple{Vararg{SignedMultiplicativeInverse{Int}}}} <: AbstractArray{T,N}
6	parent::P	129,643✔
7	dims::NTuple{N,Int}
8	mi::MI
9	end
10	ReshapedArray(parent::AbstractArray{T}, dims::NTuple{N,Int}, mi) where {T,N} = ReshapedArray{T,N,typeof(parent),typeof(mi)}(parent, dims, mi)	129,637✔
11
12	# IndexLinear ReshapedArray
13	const ReshapedArrayLF{T,N,P<:AbstractArray} = ReshapedArray{T,N,P,Tuple{}}
14
15	# Fast iteration on ReshapedArrays: use the parent iterator
16	struct ReshapedArrayIterator{I,M}
17	iter::I
18	mi::NTuple{M,SignedMultiplicativeInverse{Int}}
19	end
20	ReshapedArrayIterator(A::ReshapedArray) = _rs_iterator(parent(A), A.mi)	×
21	function _rs_iterator(P, mi::NTuple{M}) where M	×
22	iter = eachindex(P)	×
23	ReshapedArrayIterator{typeof(iter),M}(iter, mi)	×
24	end
25
26	struct ReshapedIndex{T}
27	parentindex::T	4✔
28	end
29
30	# eachindex(A::ReshapedArray) = ReshapedArrayIterator(A) # TODO: uncomment this line
31	@inline function iterate(R::ReshapedArrayIterator, i...)	×
32	item, inext = iterate(R.iter, i...)	×
33	ReshapedIndex(item), inext	×
34	end
35	length(R::ReshapedArrayIterator) = length(R.iter)	×
36	eltype(::Type{<:ReshapedArrayIterator{I}}) where {I} = @isdefined(I) ? ReshapedIndex{eltype(I)} : Any	×
37
38	## reshape(::Array, ::Dims) returns an Array, except for isbitsunion eltypes (issue #28611)
39	# reshaping to same # of dimensions
40	@eval function reshape(a::Array{T,M}, dims::NTuple{N,Int}) where {T,N,M}	19,299✔
41	throw_dmrsa(dims, len) =	19,299✔
42	throw(DimensionMismatch("new dimensions $(dims) must be consistent with array size $len"))
43	len = Core.checked_dims(dims...) # make sure prod(dims) doesn't overflow (and because of the comparison to length(a))	19,299✔
44	if len != length(a)	19,299✔
45	throw_dmrsa(dims, length(a))	4✔
46	end
47	isbitsunion(T) && return ReshapedArray(a, dims, ())	19,292✔
48	if N == M && dims == size(a)	23,607✔
49	return a	4,413✔
50	end
51	ref = a.ref	14,839✔
52	if M == 1 && N !== 1	14,836✔
53	mem = ref.mem::Memory{T}	8,670✔
54	if !(ref === GenericMemoryRef(mem) && len === mem.length)	8,670✔
55	mem = ccall(:jl_genericmemory_slice, Memory{T}, (Any, Ptr{Cvoid}, Int), mem, ref.ptr_or_offset, len)	12✔
56	ref = GenericMemoryRef(mem)::typeof(ref)	12✔
57	end
58	end
59	# or we could use `a = Array{T,N}(undef, ntuple(0, Val(N))); a.ref = ref; a.size = dims; return a` here
60	return $(Expr(:new, :(Array{T,N}), :ref, :dims))	14,839✔
61	end
62
63
64	"""
65	reshape(A, dims...) -> AbstractArray
66	reshape(A, dims) -> AbstractArray
67
68	Return an array with the same data as `A`, but with different
69	dimension sizes or number of dimensions. The two arrays share the same
70	underlying data, so that the result is mutable if and only if `A` is
71	mutable, and setting elements of one alters the values of the other.
72
73	The new dimensions may be specified either as a list of arguments or
74	as a shape tuple. At most one dimension may be specified with a `:`,
75	in which case its length is computed such that its product with all
76	the specified dimensions is equal to the length of the original array
77	`A`. The total number of elements must not change.
78
79	# Examples
80	```jldoctest
81	julia> A = Vector(1:16)
82	16-element Vector{Int64}:
83	1
84	2
85	3
86	4
87	5
88	6
89	7
90	8
91	9
92	10
93	11
94	12
95	13
96	14
97	15
98	16
99
100	julia> reshape(A, (4, 4))
101	4×4 Matrix{Int64}:
102	1 5 9 13
103	2 6 10 14
104	3 7 11 15
105	4 8 12 16
106
107	julia> reshape(A, 2, :)
108	2×8 Matrix{Int64}:
109	1 3 5 7 9 11 13 15
110	2 4 6 8 10 12 14 16
111
112	julia> reshape(1:6, 2, 3)
113	2×3 reshape(::UnitRange{Int64}, 2, 3) with eltype Int64:
114	1 3 5
115	2 4 6
116	```
117	"""
118	reshape
119
120	reshape(parent::AbstractArray, dims::IntOrInd...) = reshape(parent, dims)	1✔
121	reshape(parent::AbstractArray, shp::Tuple{Union{Integer,OneTo}, Vararg{Union{Integer,OneTo}}}) = reshape(parent, to_shape(shp))	6,456✔
122	reshape(parent::AbstractArray, dims::Dims) = _reshape(parent, dims)	11,496✔
123
124	# Allow missing dimensions with Colon():
125	reshape(parent::AbstractVector, ::Colon) = parent	3✔
126	reshape(parent::AbstractVector, ::Tuple{Colon}) = parent	2✔
127	reshape(parent::AbstractArray, dims::Int...) = reshape(parent, dims)	14,724✔
128	reshape(parent::AbstractArray, dims::Union{Int,Colon}...) = reshape(parent, dims)	72✔
129	reshape(parent::AbstractArray, dims::Tuple{Vararg{Union{Int,Colon}}}) = reshape(parent, _reshape_uncolon(parent, dims))	80✔
130	@inline function _reshape_uncolon(A, dims)	78✔
131	@noinline throw1(dims) = throw(DimensionMismatch(string("new dimensions $(dims) ",	80✔
132	"may have at most one omitted dimension specified by `Colon()`")))
133	@noinline throw2(A, dims) = throw(DimensionMismatch(string("array size $(length(A)) ",	81✔
134	"must be divisible by the product of the new dimensions $dims")))
135	pre = _before_colon(dims...)	78✔
136	post = _after_colon(dims...)	78✔
137	_any_colon(post...) && throw1(dims)	78✔
138	sz, remainder = divrem(length(A), prod(pre)*prod(post))	76✔
139	remainder == 0 \|\| throw2(A, dims)	79✔
140	(pre..., Int(sz), post...)	73✔
141	end
142	@inline _any_colon() = false	76✔
143	@inline _any_colon(dim::Colon, tail...) = true	2✔
144	@inline _any_colon(dim::Any, tail...) = _any_colon(tail...)	35✔
145	@inline _before_colon(dim::Any, tail...) = (dim, _before_colon(tail...)...)	24✔
146	@inline _before_colon(dim::Colon, tail...) = ()	78✔
147	@inline _after_colon(dim::Any, tail...) = _after_colon(tail...)	24✔
148	@inline _after_colon(dim::Colon, tail...) = tail	78✔
149
150	reshape(parent::AbstractArray{T,N}, ndims::Val{N}) where {T,N} = parent	480,417✔
151	function reshape(parent::AbstractArray, ndims::Val{N}) where N	6,387✔
152	reshape(parent, rdims(Val(N), axes(parent)))	6,387✔
153	end
154
155	# Move elements from inds to out until out reaches the desired
156	# dimensionality N, either filling with OneTo(1) or collapsing the
157	# product of trailing dims into the last element
158	rdims_trailing(l, inds...) = length(l) * rdims_trailing(inds...)	6,288✔
159	rdims_trailing(l) = length(l)	5,879✔
160	rdims(out::Val{N}, inds::Tuple) where {N} = rdims(ntuple(Returns(OneTo(1)), Val(N)), inds)	6,387✔
161	rdims(out::Tuple{}, inds::Tuple{}) = () # N == 0, M == 0	×
162	rdims(out::Tuple{}, inds::Tuple{Any}) = ()	6✔
163	rdims(out::Tuple{}, inds::NTuple{M,Any}) where {M} = ()	×
164	rdims(out::Tuple{Any}, inds::Tuple{}) = out # N == 1, M == 0	494✔
165	rdims(out::NTuple{N,Any}, inds::Tuple{}) where {N} = out # N > 1, M == 0	8✔
166	rdims(out::Tuple{Any}, inds::Tuple{Any}) = inds # N == 1, M == 1	×
167	rdims(out::Tuple{Any}, inds::NTuple{M,Any}) where {M} = (oneto(rdims_trailing(inds...)),) # N == 1, M > 1	5,879✔
168	rdims(out::NTuple{N,Any}, inds::NTuple{N,Any}) where {N} = inds # N > 1, M == N	×
169	rdims(out::NTuple{N,Any}, inds::NTuple{M,Any}) where {N,M} = (first(inds), rdims(tail(out), tail(inds))...) # N > 1, M > 1, M != N	546✔
170
171
172	# _reshape on Array returns an Array
173	_reshape(parent::Vector, dims::Dims{1}) = parent	2✔
174	_reshape(parent::Array, dims::Dims{1}) = reshape(parent, dims)	×
175	_reshape(parent::Array, dims::Dims) = reshape(parent, dims)	×
176
177	# When reshaping Vector->Vector, don't wrap with a ReshapedArray
178	function _reshape(v::AbstractVector, dims::Dims{1})	37✔
179	require_one_based_indexing(v)	37✔
180	len = dims[1]	37✔
181	len == length(v) \|\| _throw_dmrs(length(v), "length", len)	38✔
182	v	36✔
183	end
184	# General reshape
185	function _reshape(parent::AbstractArray, dims::Dims)	11,449✔
186	n = length(parent)	11,449✔
187	prod(dims) == n \|\| _throw_dmrs(n, "size", dims)	11,462✔
188	__reshape((parent, IndexStyle(parent)), dims)	11,436✔
189	end
190
191	@noinline function _throw_dmrs(n, str, dims)	14✔
192	throw(DimensionMismatch("parent has $n elements, which is incompatible with $str $dims"))	14✔
193	end
194
195	# Reshaping a ReshapedArray
196	_reshape(v::ReshapedArray{<:Any,1}, dims::Dims{1}) = _reshape(v.parent, dims)	2✔
197	_reshape(R::ReshapedArray, dims::Dims) = _reshape(R.parent, dims)	28✔
198
199	function __reshape(p::Tuple{AbstractArray,IndexStyle}, dims::Dims)	6,865✔
200	parent = p[1]	6,865✔
201	strds = front(size_to_strides(map(length, axes(parent))..., 1))	6,865✔
202	strds1 = map(s->max(1,Int(s)), strds) # for resizing empty arrays	13,734✔
203	mi = map(SignedMultiplicativeInverse, strds1)	6,865✔
204	ReshapedArray(parent, dims, reverse(mi))	6,865✔
205	end
206
207	function __reshape(p::Tuple{AbstractArray{<:Any,0},IndexCartesian}, dims::Dims)	4✔
208	parent = p[1]	4✔
209	ReshapedArray(parent, dims, ())	4✔
210	end
211
212	function __reshape(p::Tuple{AbstractArray,IndexLinear}, dims::Dims)	4,567✔
213	parent = p[1]	4,567✔
214	ReshapedArray(parent, dims, ())	4,567✔
215	end
216
217	size(A::ReshapedArray) = A.dims	4,154,347✔
218	length(A::ReshapedArray) = length(parent(A))	8,057,303✔
219	similar(A::ReshapedArray, eltype::Type, dims::Dims) = similar(parent(A), eltype, dims)	5,276✔
220	IndexStyle(::Type{<:ReshapedArrayLF}) = IndexLinear()	21,024✔
221	parent(A::ReshapedArray) = A.parent	17,244,770✔
222	parentindices(A::ReshapedArray) = map(oneto, size(parent(A)))	2✔
223	reinterpret(::Type{T}, A::ReshapedArray, dims::Dims) where {T} = reinterpret(T, parent(A), dims)	×
224	elsize(::Type{<:ReshapedArray{<:Any,<:Any,P}}) where {P} = elsize(P)	6,834✔
225
226	unaliascopy(A::ReshapedArray) = typeof(A)(unaliascopy(A.parent), A.dims, A.mi)	6✔
227	dataids(A::ReshapedArray) = dataids(A.parent)	5,143✔
228
229	@inline ind2sub_rs(ax, ::Tuple{}, i::Int) = (i,)	90,269✔
230	@inline ind2sub_rs(ax, strds, i) = _ind2sub_rs(ax, strds, i - 1)	1,773,781✔
231	@inline _ind2sub_rs(ax, ::Tuple{}, ind) = (ind + first(ax[end]),)	1,773,781✔
232	@inline function _ind2sub_rs(ax, strds, ind)	3,364,299✔
233	d, r = divrem(ind, strds[1])	3,364,299✔
234	(_ind2sub_rs(front(ax), tail(strds), r)..., d + first(ax[end]))	3,364,299✔
235	end
236	offset_if_vec(i::Integer, axs::Tuple{<:AbstractUnitRange}) = i + first(axs[1]) - 1	73,175✔
237	offset_if_vec(i::Integer, axs::Tuple) = i	1,660,369✔
238
239	@inline function isassigned(A::ReshapedArrayLF, index::Int)	4,008,803✔
240	@boundscheck checkbounds(Bool, A, index) \|\| return false	4,008,803✔
241	@inbounds ret = isassigned(parent(A), index)	4,008,803✔
242	ret	4,008,803✔
243	end
244	@inline function isassigned(A::ReshapedArray{T,N}, indices::Vararg{Int, N}) where {T,N}	595,839✔
245	@boundscheck checkbounds(Bool, A, indices...) \|\| return false	595,839✔
246	axp = axes(A.parent)	595,839✔
247	i = offset_if_vec(_sub2ind(size(A), indices...), axp)	595,839✔
248	I = ind2sub_rs(axp, A.mi, i)	595,839✔
249	@inbounds isassigned(A.parent, I...)	595,839✔
250	end
251
252	@inline function getindex(A::ReshapedArrayLF, index::Int)	4,026,726✔
253	@boundscheck checkbounds(A, index)	4,026,726✔
254	@inbounds ret = parent(A)[index]	4,027,025✔
255	ret	4,026,726✔
256	end
257	@inline function getindex(A::ReshapedArray{T,N}, indices::Vararg{Int,N}) where {T,N}	1,136,214✔
258	@boundscheck checkbounds(A, indices...)	1,136,216✔
259	_unsafe_getindex(A, indices...)	1,137,160✔
260	end
261	@inline function getindex(A::ReshapedArray, index::ReshapedIndex)	2✔
262	@boundscheck checkbounds(parent(A), index.parentindex)	2✔
263	@inbounds ret = parent(A)[index.parentindex]	2✔
264	ret	2✔
265	end
266
267	@inline function _unsafe_getindex(A::ReshapedArray{T,N}, indices::Vararg{Int,N}) where {T,N}	1,136,212✔
268	axp = axes(A.parent)	1,136,212✔
269	i = offset_if_vec(_sub2ind(size(A), indices...), axp)	1,136,212✔
270	I = ind2sub_rs(axp, A.mi, i)	1,136,212✔
271	_unsafe_getindex_rs(parent(A), I)	1,137,160✔
272	end
273	@inline _unsafe_getindex_rs(A, i::Integer) = (@inbounds ret = A[i]; ret)	×
274	@inline _unsafe_getindex_rs(A, I) = (@inbounds ret = A[I...]; ret)	2,273,372✔
275
276	@inline function setindex!(A::ReshapedArrayLF, val, index::Int)	258✔
277	@boundscheck checkbounds(A, index)	258✔
278	@inbounds parent(A)[index] = val	258✔
279	val	258✔
280	end
281	@inline function setindex!(A::ReshapedArray{T,N}, val, indices::Vararg{Int,N}) where {T,N}	1,493✔
282	@boundscheck checkbounds(A, indices...)	1,493✔
283	_unsafe_setindex!(A, val, indices...)	1,493✔
284	end
285	@inline function setindex!(A::ReshapedArray, val, index::ReshapedIndex)	1✔
286	@boundscheck checkbounds(parent(A), index.parentindex)	1✔
287	@inbounds parent(A)[index.parentindex] = val	1✔
288	val	1✔
289	end
290
291	@inline function _unsafe_setindex!(A::ReshapedArray{T,N}, val, indices::Vararg{Int,N}) where {T,N}	1,493✔
292	axp = axes(A.parent)	1,493✔
293	i = offset_if_vec(_sub2ind(size(A), indices...), axp)	1,493✔
294	@inbounds parent(A)[ind2sub_rs(axes(A.parent), A.mi, i)...] = val	1,493✔
295	val	1,493✔
296	end
297
298	# helpful error message for a common failure case
299	const ReshapedRange{T,N,A<:AbstractRange} = ReshapedArray{T,N,A,Tuple{}}
300	setindex!(A::ReshapedRange, val, index::Int) = _rs_setindex!_err()	1✔
301	setindex!(A::ReshapedRange{T,N}, val, indices::Vararg{Int,N}) where {T,N} = _rs_setindex!_err()	1✔
302	setindex!(A::ReshapedRange, val, index::ReshapedIndex) = _rs_setindex!_err()	1✔
303
304	@noinline _rs_setindex!_err() = error("indexed assignment fails for a reshaped range; consider calling collect")	3✔
305
306	cconvert(::Type{Ptr{T}}, a::ReshapedArray{T}) where {T} = cconvert(Ptr{T}, parent(a))	6,774✔
307
308	# Add a few handy specializations to further speed up views of reshaped ranges
309	const ReshapedUnitRange{T,N,A<:AbstractUnitRange} = ReshapedArray{T,N,A,Tuple{}}
310	viewindexing(I::Tuple{Slice, ReshapedUnitRange, Vararg{ScalarIndex}}) = IndexLinear()	2✔
311	viewindexing(I::Tuple{ReshapedRange, Vararg{ScalarIndex}}) = IndexLinear()	5✔
312	compute_stride1(s, inds, I::Tuple{ReshapedRange, Vararg{Any}}) = s*step(I[1].parent)	5✔
313	compute_offset1(parent::AbstractVector, stride1::Integer, I::Tuple{ReshapedRange}) =	1✔
314	(@inline; first(I[1]) - first(axes1(I[1]))*stride1)	1✔
315	substrides(strds::NTuple{N,Int}, I::Tuple{ReshapedUnitRange, Vararg{Any}}) where N =	198✔
316	(size_to_strides(strds[1], size(I[1])...)..., substrides(tail(strds), tail(I))...)
317
318	# cconvert(::Type{<:Ptr}, V::SubArray{T,N,P,<:Tuple{Vararg{Union{RangeIndex,ReshapedUnitRange}}}}) where {T,N,P} = V
319	function unsafe_convert(::Type{Ptr{S}}, V::SubArray{T,N,P,<:Tuple{Vararg{Union{RangeIndex,ReshapedUnitRange}}}}) where {S,T,N,P}	725,790✔
320	parent = V.parent	725,851✔
321	p = cconvert(Ptr{T}, parent) # XXX: this should occur in cconvert, the result is not GC-rooted	1,624,315✔
322	Δmem = if _checkcontiguous(Bool, parent)	724,762✔
323	(first_index(V) - firstindex(parent)) * elsize(parent)	1,159,895✔
324	else
325	_memory_offset(parent, map(first, V.indices)...)	22,840✔
326	end
327	return Ptr{S}(unsafe_convert(Ptr{T}, p) + Δmem)	1,624,315✔
328	end
329
330	_checkcontiguous(::Type{Bool}, A::AbstractArray) = false	30,179✔
331	# `strides(A::DenseArray)` calls `size_to_strides` by default.
332	# Thus it's OK to assume all `DenseArray`s are contiguously stored.
333	_checkcontiguous(::Type{Bool}, A::DenseArray) = true	135,295✔
334	_checkcontiguous(::Type{Bool}, A::ReshapedArray) = _checkcontiguous(Bool, parent(A))	1,903✔
335	_checkcontiguous(::Type{Bool}, A::FastContiguousSubArray) = _checkcontiguous(Bool, parent(A))	847,545✔
336
337	function strides(a::ReshapedArray)	1,696✔
338	_checkcontiguous(Bool, a) && return size_to_strides(1, size(a)...)	1,696✔
339	apsz::Dims = size(a.parent)	1,674✔
340	apst::Dims = strides(a.parent)	1,674✔
341	msz, mst, n = merge_adjacent_dim(apsz, apst) # Try to perform "lazy" reshape	1,674✔
342	n == ndims(a.parent) && return size_to_strides(mst, size(a)...) # Parent is stridevector like	1,674✔
343	return _reshaped_strides(size(a), 1, msz, mst, n, apsz, apst)	581✔
344	end
345
346	function _reshaped_strides(::Dims{0}, reshaped::Int, msz::Int, ::Int, ::Int, ::Dims, ::Dims)	581✔
347	reshaped == msz && return ()	581✔
348	throw(ArgumentError("Input is not strided."))	5✔
349	end
350	function _reshaped_strides(sz::Dims, reshaped::Int, msz::Int, mst::Int, n::Int, apsz::Dims, apst::Dims)	2,924✔
351	st = reshaped * mst	2,924✔
352	reshaped = reshaped * sz[1]	2,924✔
353	if length(sz) > 1 && reshaped == msz && sz[2] != 1	2,924✔
354	msz, mst, n = merge_adjacent_dim(apsz, apst, n + 1)	576✔
355	reshaped = 1	576✔
356	end
357	sts = _reshaped_strides(tail(sz), reshaped, msz, mst, n, apsz, apst)	2,937✔
358	return (st, sts...)	2,908✔
359	end
360
361	merge_adjacent_dim(::Dims{0}, ::Dims{0}) = 1, 1, 0	1✔
362	merge_adjacent_dim(apsz::Dims{1}, apst::Dims{1}) = apsz[1], apst[1], 1	3,313✔
363	function merge_adjacent_dim(apsz::Dims{N}, apst::Dims{N}, n::Int = 1) where {N}	2,429✔
364	sz, st = apsz[n], apst[n]	2,412✔
365	while n < N	1,848✔
366	szₙ, stₙ = apsz[n+1], apst[n+1]	942✔
367	if sz == 1	942✔
368	sz, st = szₙ, stₙ	3✔
369	elseif stₙ == st * sz \|\| szₙ == 1	1,544✔
370	sz *= szₙ	351✔
371	else
372	break	588✔
373	end
374	n += 1	354✔
375	end	354✔
376	return sz, st, n	1,494✔
377	end

JuliaLang / julia / #37666

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