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subarray.jl
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subarray.jl
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# This file is a part of Julia. License is MIT: http://julialang.org/license
typealias NonSliceIndex Union{Colon, Range{Int}, UnitRange{Int}, Array{Int,1}}
typealias ViewIndex Union{Int, NonSliceIndex}
# LD is the last dimension up through which this object has efficient
# linear indexing. If LD==length(I), then the object itself has efficient
# linear indexing.
immutable SubArray{T,N,P<:AbstractArray,I<:Tuple{Vararg{ViewIndex}},LD} <: AbstractArray{T,N}
parent::P
indexes::I
dims::NTuple{N,Int}
first_index::Int # for linear indexing and pointer
stride1::Int # used only for linear indexing
end
typealias StridedArray{T,N,A<:DenseArray,I<:Tuple{Vararg{RangeIndex}}} Union{DenseArray{T,N}, SubArray{T,N,A,I}}
typealias StridedVector{T,A<:DenseArray,I<:Tuple{Vararg{RangeIndex}}} Union{DenseArray{T,1}, SubArray{T,1,A,I}}
typealias StridedMatrix{T,A<:DenseArray,I<:Tuple{Vararg{RangeIndex}}} Union{DenseArray{T,2}, SubArray{T,2,A,I}}
typealias StridedVecOrMat{T} Union{StridedVector{T}, StridedMatrix{T}}
# Simple utilities
eltype{T,N,P,I}(V::SubArray{T,N,P,I}) = T
eltype{T,N,P,I}(::Type{SubArray{T,N,P,I}}) = T
ndims{T,N,P,I}(V::SubArray{T,N,P,I}) = N
ndims{T,N,P,I}(::Type{SubArray{T,N,P,I}}) = N
size(V::SubArray) = V.dims
# size(V::SubArray, d::Integer) = d <= ndims(V) ? (@inbounds ret = V.dims[d]; ret) : 1
length(V::SubArray) = prod(V.dims)
similar(V::SubArray, T, dims::Dims) = similar(V.parent, T, dims)
copy(V::SubArray) = copy!(similar(V.parent, size(V)), V)
parent(V::SubArray) = V.parent
parentindexes(V::SubArray) = V.indexes
parent(a::AbstractArray) = a
parentindexes(a::AbstractArray) = ntuple(i->1:size(a,i), ndims(a))
## SubArray creation
# Drops singleton dimensions (those indexed with a scalar)
slice(A::AbstractArray, I::ViewIndex...) = _slice(A, I)
slice(A::AbstractArray, I::Tuple{Vararg{ViewIndex}}) = _slice(A, I)
function _slice(A, I)
checkbounds(A, I...)
slice_unsafe(A, I)
end
# The most complicated part of this is matching the axes between the
# input index tuples (denoted by J), the index tuples that get stored
# in the view (denoted by I), and the overall dimensionality of the
# view.
# The complexities increase when you create a view-of-a-view, because
# then there is also the index tuple of the parent view (denoted IV)
# to consider.
#
# Examples:
# S1 = sub(A::Matrix, 2, 3:5) ndims(S1) == length(I) == length(J) == 2
# S2 = slice(A::Matrix, 2, 3:5) ndims(S2) == 1, length(I) == length(J) == 2
# S3 = sub(A::Matrix, 4:17) ndims(S3) == length(I) == length(J) == 1
# S4 = sub(S2, 1:2) ndims(S4) == length(J) == 1, length(I) == 2
# S3 addresses the trailing dimensions of the parent by linear indexing.
# For S4, J[1] corresponds to I[2], because of the slice along
# dimension 1 in S2
@generated function slice_unsafe{T,NP,IndTypes}(A::AbstractArray{T,NP}, J::IndTypes)
N = 0
sizeexprs = Array(Any, 0)
Jp = J.parameters
for Jindex = 1:length(Jp)
j = Jp[Jindex]
if !(j <: Real)
N += 1
push!(sizeexprs, dimsizeexpr(j, Jindex, length(Jp), :A, :J))
end
end
dims = :(tuple($(sizeexprs...)))
LD = subarray_linearindexing_dim(A, J)
strideexpr = stride1expr(A, Jp, :A, :J, LD)
exfirst = first_index_expr(:A, :J, length(Jp))
quote
$exfirst
SubArray{$T,$N,$A,$J,$LD}(A, J, $dims, f, $strideexpr)
end
end
# Conventional style (drop trailing singleton dimensions, keep any
# other singletons by converting them to ranges, e.g., 3:3)
sub(A::AbstractArray, I::ViewIndex...) = _sub(A, I)
sub(A::AbstractArray, I::Tuple{Vararg{ViewIndex}}) = _sub(A, I)
function _sub(A, I)
checkbounds(A, I...)
sub_unsafe(A, I)
end
@generated function sub_unsafe{T,NP,IndTypes}(A::AbstractArray{T,NP}, J::IndTypes)
sizeexprs = Array(Any, 0)
Itypes = Array(Any, 0)
Iexprs = Array(Any, 0)
Jp = J.parameters
N = length(Jp)
while N > 0 && Jp[N] <: Real
N -= 1
end
for Jindex = 1:length(Jp)
j = Jp[Jindex]
if Jindex <= N
push!(sizeexprs, dimsizeexpr(j, Jindex, length(Jp), :A, :J))
end
if Jindex < N && j <: Real
push!(Itypes, UnitRange{Int})
push!(Iexprs, :(Int(J[$Jindex]):Int(J[$Jindex])))
else
push!(Itypes, j)
push!(Iexprs, :(J[$Jindex]))
end
end
dims = :(tuple($(sizeexprs...)))
Iext = :(tuple($(Iexprs...)))
It = Tuple{Itypes...}
LD = subarray_linearindexing_dim(A, J)
strideexpr = stride1expr(A, Jp, :A, :J, LD)
exfirst = first_index_expr(:A, :J, length(Itypes))
quote
$exfirst
SubArray{$T,$N,$A,$It,$LD}(A, $Iext, $dims, f, $strideexpr)
end
end
# Constructing from another SubArray
# This "pops" the old SubArray and creates a more compact one
@generated function slice_unsafe{T,NV,PV,IV,PLD,IndTypes}(V::SubArray{T,NV,PV,IV,PLD}, J::IndTypes)
N = 0
sizeexprs = Array(Any, 0)
indexexprs = Array(Any, 0)
Itypes = Array(Any, 0)
Jp = J.parameters
# The next two Ints, if nonzero, record information about the place
# in the index tuple at which trailing dimensions got packed into a
# single Vector{Int}. For stride1 computation, we need to keep track
# of whether the index that triggered this had uniform stride.
# Iindex_lin is the spot in the resulting index tuple
# Jindex_lin is the corresponding spot in the input index tuple
Iindex_lin = Jindex_lin = 0
# Linear indexing inference makes use of the following variables:
# LD: the last dimension up through which linear indexing is efficient
# isLDdone: true if we've quit incrementing LD
# die_next_vector: if true, stop incrementing LD on the next
# "extended" input index
# jprev: holds the previous input index type
LD, die_next_vector, jprev, isLDdone = 0, false, Void, false # for linear indexing inference
Jindex = 0
IVp = IV.parameters
for IVindex = 1:length(IVp)
iv = IVp[IVindex]
if iv <: Real
push!(indexexprs, :(V.indexes[$IVindex]))
push!(Itypes, iv)
if !isLDdone
LD += 1
end
else
Jindex += 1
j = Jp[Jindex]
if Jindex < length(Jp) || Jindex == NV || IVindex == length(IVp)
if !(j <: Real)
N += 1
push!(sizeexprs, dimsizeexpr(j, Jindex, length(Jp), :V, :J))
end
push!(indexexprs, :(reindex(V.indexes[$IVindex], J[$Jindex])))
push!(Itypes, rangetype(iv, j))
else
# We have a linear index that spans more than one
# dimension of the parent
N += 1
push!(sizeexprs, dimsizeexpr(j, Jindex, length(Jp), :V, :J))
push!(indexexprs, :(merge_indexes(V, V.indexes[$IVindex:end], size(V.parent)[$IVindex:end], J[$Jindex], $Jindex)))
push!(Itypes, Array{Int, 1})
Iindex_lin = length(Itypes)
Jindex_lin = Jindex
break
end
if !isLDdone
if LD < PLD
LD += 1
jprev, LD, die_next_vector, isdone = nextLD(jprev, j, LD, die_next_vector)
isLDdone |= isdone
else
if j <: Real
LD += 1
else
isLDdone = true
end
end
end
end
end
for Jind = Jindex+1:length(Jp)
j = Jp[Jind]
if !(j <: Real)
N += 1
push!(sizeexprs, dimsizeexpr(j, Jind, length(Jp), :V, :J))
isLDdone = true
elseif !isLDdone
LD += 1
end
push!(indexexprs, :(J[$Jind]))
push!(Itypes, j)
end
Inew = :(tuple($(indexexprs...)))
dims = :(tuple($(sizeexprs...)))
It = Tuple{Itypes...}
LD = max(LD, subarray_linearindexing_dim(PV, It))
strideexpr = stride1expr(PV, Itypes, :(V.parent), :Inew, LD, :J, Iindex_lin, Jindex_lin)
exfirst = first_index_expr(:(V.parent), :Inew, length(Itypes))
quote
Inew = $Inew
$exfirst
SubArray{$T,$N,$PV,$It,$LD}(V.parent, Inew, $dims, f, $strideexpr)
end
end
@generated function sub_unsafe{T,NV,PV,IV,PLD,IndTypes}(V::SubArray{T,NV,PV,IV,PLD}, J::IndTypes)
Jp = J.parameters
IVp = IV.parameters
N = length(Jp)
while N > 0 && Jp[N] <: Real
N -= 1
end
sizeexprs = Array(Any, 0)
indexexprs = Array(Any, 0)
Itypes = Array(Any, 0)
ItypesLD = Array(Any, 0)
preexprs = Array(Any, 0)
LD, die_next_vector, jprev, isLDdone = 0, false, Void, false
Jindex = 0
for IVindex = 1:length(IVp)
iv = IVp[IVindex]
if iv <: Real
push!(indexexprs, :(V.indexes[$IVindex]))
push!(Itypes, iv)
push!(ItypesLD, iv)
if !isLDdone
LD += 1
end
else
Jindex += 1
j = Jp[Jindex]
if Jindex <= N
push!(sizeexprs, dimsizeexpr(j, Jindex, length(Jp), :V, :J))
end
if Jindex < N && j <: Real
# convert scalar to a range
sym = gensym()
push!(preexprs, :($sym = reindex(V.indexes[$IVindex], Int(J[$Jindex]))))
push!(indexexprs, :($sym:$sym))
push!(Itypes, UnitRange{Int})
push!(ItypesLD, j)
elseif Jindex < length(Jp) || Jindex == NV || IVindex == length(IVp)
# simple indexing
push!(indexexprs, :(reindex(V.indexes[$IVindex], J[$Jindex])))
push!(Itypes, rangetype(iv, j))
push!(ItypesLD, Itypes[end])
else
# We have a linear index that spans more than one dimension of the parent
push!(indexexprs, :(merge_indexes(V, V.indexes[$IVindex:end], size(V.parent)[$IVindex:end], J[$Jindex], $Jindex)))
push!(Itypes, Array{Int, 1})
push!(ItypesLD, Itypes[end])
break
end
if !isLDdone
if LD < PLD
LD += 1
jprev, LD, die_next_vector, isdone = nextLD(jprev, j, LD, die_next_vector)
isLDdone |= isdone
else
if j <: Real
LD += 1
else
isLDdone = true
end
end
end
end
end
for Jind = Jindex+1:length(Jp)
j = Jp[Jind]
if Jind <= N
push!(sizeexprs, dimsizeexpr(j, Jind, length(Jp), :V, :J))
end
push!(indexexprs, :(J[$Jind]))
push!(Itypes, j)
push!(ItypesLD, Itypes[end])
end
Inew = :(tuple($(indexexprs...)))
dims = :(tuple($(sizeexprs...)))
It = Tuple{Itypes...}
LD = max(LD, subarray_linearindexing_dim(PV, It))
strideexpr = stride1expr(PV, ItypesLD, :(V.parent), :Inew, LD)
preex = isempty(preexprs) ? nothing : Expr(:block, preexprs...)
exfirst = first_index_expr(:(V.parent), :Inew, length(Itypes))
quote
$preex
Inew = $Inew
$exfirst
SubArray{$T,$N,$PV,$It,$LD}(V.parent, Inew, $dims, f, $strideexpr)
end
end
function rangetype(T1, T2)
rt = return_types(getindex, Tuple{T1, T2})
length(rt) == 1 || error("Can't infer return type")
rt[1]
end
reindex(a, b) = a[b]
reindex(a::UnitRange, b::UnitRange{Int}) = range(oftype(first(a), first(a)+first(b)-1), length(b))
reindex(a::UnitRange, b::StepRange{Int}) = range(oftype(first(a), first(a)+first(b)-1), step(b), length(b))
reindex(a::StepRange, b::Range{Int}) = range(oftype(first(a), first(a)+(first(b)-1)*step(a)), step(a)*step(b), length(b))
reindex(a, b::Int) = unsafe_getindex(a, b)
dimsizeexpr(Itype, d::Int, len::Int, Asym::Symbol, Isym::Symbol) = :(length($Isym[$d]))
function dimsizeexpr(Itype::Type{Colon}, d::Int, len::Int, Asym::Symbol, Isym::Symbol)
if d < len
:(size($Asym, $d))
else
:(tailsize($Asym, $d))
end
end
dimsize(P, d, I) = length(I)
dimsize(P, d::Int, ::Colon) = size(P, d)
dimsize(P, d::Dims, ::Colon) = prod(size(P)[d])
function tailsize(P, d)
s = 1
for i = d:ndims(P)
s *= size(P, i)
end
s
end
@generated function linearindexing{T,N,P,I,LD}(A::SubArray{T,N,P,I,LD})
length(I.parameters) == LD ? (:(LinearFast())) : (:(LinearSlow()))
end
@generated function linearindexing{A<:SubArray}(::Type{A})
T,N,P,I,LD = A.parameters
length(I.parameters) == LD ? (:(LinearFast())) : (:(LinearSlow()))
end
getindex(::Colon, i) = to_index(i)
unsafe_getindex(v::Colon, i) = to_index(i)
step(::Colon) = 1
first(::Colon) = 1
isempty(::Colon) = false
in(::Int, ::Colon) = true
## Strides
@generated function strides{T,N,P,I}(V::SubArray{T,N,P,I})
Ip = I.parameters
all(map(x->x<:Union{RangeIndex,Colon}, Ip)) || throw(ArgumentError("strides valid only for RangeIndex indexing"))
strideexprs = Array(Any, N+1)
strideexprs[1] = 1
i = 1
Vdim = 1
for i = 1:length(Ip)
if Ip[i] != Int
strideexprs[Vdim+1] = copy(strideexprs[Vdim])
strideexprs[Vdim] = :(step(V.indexes[$i])*$(strideexprs[Vdim]))
Vdim += 1
end
strideexprs[Vdim] = :(size(V.parent, $i) * $(strideexprs[Vdim]))
end
:(tuple($(strideexprs[1:N]...)))
end
stride(V::SubArray, d::Integer) = d <= ndims(V) ? strides(V)[d] : strides(V)[end] * size(V)[end]
function stride1expr(Atype::Type, Itypes, Aexpr, Isym, LD, Jsym=Isym, Iindex_lin=0, Jindex_lin=0)
if LD == 0
return 0
end
ex = 1
for d = 1:min(LD, length(Itypes))
I = Itypes[d]
if I <: Real
ex = :($ex * size($Aexpr, $d))
else
if d == Iindex_lin
ex = :($ex * step_sa($Jsym[$Jindex_lin]))
else
ex = :($ex * step($Isym[$d]))
end
break
end
end
ex
end
step_sa(arg) = step(arg)
step_sa(::Integer) = 1
# This might be conservative, but better safe than sorry
function iscontiguous{T,N,P,I,LD}(::Type{SubArray{T,N,P,I,LD}})
Ip = I.parameters
LD == length(Ip) || return false
length(Ip) < 1 && return true
Ip[1] == Colon && return true
if Ip[1] <: UnitRange
# It might be stride1 == 1, or this might be because `sub` was
# used with an integer for the first index
for j = 2:length(Ip)
(Ip[j] == Colon || (Ip[j] <: AbstractVector)) && return false
end
return true
end
false
end
iscontiguous(S::SubArray) = iscontiguous(typeof(S))
first_index(V::SubArray) = first_index(V.parent, V.indexes)
function first_index(P::AbstractArray, indexes::Tuple)
f = 1
s = 1
for i = 1:length(indexes)
f += (first(indexes[i])-1)*s
s *= size(P, i)
end
f
end
function first_index_expr(Asym, Isym::Symbol, n::Int)
ex = :(f = s = 1)
for i = 1:n
ex = quote
$ex
if isempty($Isym[$i])
f = s = 0
else
f += (first($Isym[$i])-1)*s
s *= size($Asym, $i)
end
end
end
ex
end
# Detecting whether one can support fast linear indexing
function nextLD(jprev, j, LD, die_next_vector)
isdone = false
if j <: Real
if jprev != Void && !(jprev <: Real)
die_next_vector = true
end
elseif die_next_vector || j <: Vector
LD -= 1
isdone = true
elseif j == Colon
elseif j <: UnitRange
die_next_vector = true
elseif j <: Range
if !(jprev == Void || jprev <: Real)
LD -= 1
isdone = true
end
die_next_vector = true
else
error("This shouldn't happen (linear indexing inference)")
end
jprev = j
return jprev, LD, die_next_vector, isdone
end
function subarray_linearindexing_dim{A<:AbstractArray}(::Type{A}, It::Type)
isa(Base.linearindexing(A), Base.LinearSlow) && return 0
isempty(It.parameters) && return 0
jprev = Void
LD = 0
die_next_vector = false
while LD < length(It.parameters)
LD += 1
I = It.parameters[LD]
jprev, LD, die_next_vector, isdone = nextLD(jprev, I, LD, die_next_vector)
if isdone
break
end
end
LD
end
unsafe_convert{T,N,P<:Array,I<:Tuple{Vararg{RangeIndex}}}(::Type{Ptr{T}}, V::SubArray{T,N,P,I}) =
pointer(V.parent) + (V.first_index-1)*sizeof(T)
unsafe_convert{T,N,P<:Array,I<:Tuple{Vararg{RangeIndex}}}(::Type{Ptr{Void}}, V::SubArray{T,N,P,I}) =
convert(Ptr{Void}, unsafe_convert(Ptr{T}, V))
pointer(V::SubArray, i::Int) = pointer(V, ind2sub(size(V), i))
function pointer{T,N,P<:Array,I<:Tuple{Vararg{RangeIndex}}}(V::SubArray{T,N,P,I}, is::Tuple{Vararg{Int}})
index = first_index(V)
strds = strides(V)
for d = 1:length(is)
index += (is[d]-1)*strds[d]
end
return pointer(V.parent, index)
end
## Convert
convert{T,S,N}(::Type{Array{T,N}}, V::SubArray{S,N}) = copy!(Array(T, size(V)), V)
## Compatability
# deprecate?
function parentdims(s::SubArray)
nd = ndims(s)
dimindex = Array(Int, nd)
sp = strides(s.parent)
sv = strides(s)
j = 1
for i = 1:ndims(s.parent)
r = s.indexes[i]
if j <= nd && (isa(r,Union{Colon,Range}) ? sp[i]*step(r) : sp[i]) == sv[j]
dimindex[j] = i
j += 1
end
end
dimindex
end
## Scalar indexing
# While it'd be nice to explicitly check bounds against the SubArray dimensions,
# the lack of an extensible @inbounds mechanism makes it difficult for users to
# avoid the cost of the bounds check without rewriting their syntax to use the
# unwieldy unsafe_getindex/unsafe_setindex! function calls. So instead we define
# getindex to rely upon the bounds checks in the parent array. It's still
# advantageous to define the unsafe_ variants without any bounds checks since
# the abstract indexing fallbacks can make use of them.
@generated function getindex{T,N,P,IV,LD}(V::SubArray{T,N,P,IV,LD}, I::Int...)
ni = length(I)
if ni == 1 && length(IV.parameters) == LD # linear indexing
meta = Expr(:meta, :inline)
if iscontiguous(V)
return :($meta; getindex(V.parent, V.first_index + I[1] - 1))
end
return :($meta; getindex(V.parent, V.first_index + V.stride1*(I[1]-1)))
end
Isyms = [:(I[$d]) for d = 1:ni]
exhead, idxs = index_generate(ndims(P), IV, :V, Isyms)
quote
$exhead
getindex(V.parent, $(idxs...))
end
end
@generated function unsafe_getindex{T,N,P,IV,LD}(V::SubArray{T,N,P,IV,LD}, I::Int...)
ni = length(I)
if ni == 1 && length(IV.parameters) == LD # linear indexing
meta = Expr(:meta, :inline)
if iscontiguous(V)
return :($meta; unsafe_getindex(V.parent, V.first_index + I[1] - 1))
end
return :($meta; unsafe_getindex(V.parent, V.first_index + V.stride1*(I[1]-1)))
end
Isyms = [:(I[$d]) for d = 1:ni]
exhead, idxs = index_generate(ndims(P), IV, :V, Isyms)
quote
$exhead
unsafe_getindex(V.parent, $(idxs...))
end
end
@generated function setindex!{T,N,P,IV,LD}(V::SubArray{T,N,P,IV,LD}, v, I::Int...)
ni = length(I)
if ni == 1 && length(IV.parameters) == LD # linear indexing
meta = Expr(:meta, :inline)
if iscontiguous(V)
return :($meta; setindex!(V.parent, v, V.first_index + I[1] - 1))
end
return :($meta; setindex!(V.parent, v, V.first_index + V.stride1*(I[1]-1)))
end
Isyms = [:(I[$d]) for d = 1:ni]
exhead, idxs = index_generate(ndims(P), IV, :V, Isyms)
quote
$exhead
setindex!(V.parent, v, $(idxs...))
end
end
@generated function unsafe_setindex!{T,N,P,IV,LD}(V::SubArray{T,N,P,IV,LD}, v, I::Int...)
ni = length(I)
if ni == 1 && length(IV.parameters) == LD # linear indexing
meta = Expr(:meta, :inline)
if iscontiguous(V)
return :($meta; unsafe_setindex!(V.parent, v, V.first_index + I[1] - 1))
end
return :($meta; unsafe_setindex!(V.parent, v, V.first_index + V.stride1*(I[1]-1)))
end
Isyms = [:(I[$d]) for d = 1:ni]
exhead, idxs = index_generate(ndims(P), IV, :V, Isyms)
quote
$exhead
unsafe_setindex!(V.parent, v, $(idxs...))
end
end
# Indexing with non-scalars. For now, this returns a copy, but changing that
# is just a matter of deleting the explicit call to copy.
getindex{T,N,P,IV}(V::SubArray{T,N,P,IV}, I::ViewIndex...) = copy(sub(V, I...))
getindex{T,N,P,IV}(V::SubArray{T,N,P,IV}, I::Union{Real, AbstractVector, Colon}...) = getindex(V, to_indexes(I...)...)
unsafe_getindex{T,N,P,IV}(V::SubArray{T,N,P,IV}, I::ViewIndex...) = copy(sub_unsafe(V, I))
unsafe_getindex{T,N,P,IV}(V::SubArray{T,N,P,IV}, I::Union{Real, AbstractVector, Colon}...) = unsafe_getindex(V, to_indexes(I...)...)
# Nonscalar setindex! falls back to the AbstractArray versions
# NP is parent dimensionality, Itypes is the tuple typeof(V.indexes)
# NP may not be equal to length(Itypes), because a view of a 2d matrix A
# can be constructed as V = A[5:13] or as V = A[2:4, 1:3, 1].
function index_generate(NP, Itypes, Vsym, Isyms)
Itypes = Itypes.parameters
if isempty(Isyms)
Isyms = Any[1] # this handles the syntax getindex(V)
end
exhead = :nothing
NV = 0
for I in Itypes
NV += !(I == Int)
end
if length(Isyms) < NV
# Linear indexing in the last index
n = NV - length(Isyms)
m = length(Isyms)
strides = [gensym() for i = 1:n]
indexes = [gensym() for i = 1:n+1]
resid = gensym()
linblock = Array(Expr, 2n+2)
linblock[1] = :($(strides[1]) = size($Vsym, $m))
for k = 2:n
m += 1
linblock[k] = :($(strides[k]) = $(strides[k-1]) * size($Vsym, $m))
end
k = n+1
linblock[k] = :($resid = $(Isyms[end])-1)
for i = n:-1:1
k += 1
linblock[k] = quote
$(indexes[i+1]), $resid = divrem($resid, $(strides[i]))
$(indexes[i+1]) += 1
end
end
linblock[end] = :($(indexes[1]) = $resid+1)
exhead = Expr(:block, linblock...)
pop!(Isyms)
append!(Isyms, indexes)
end
L = length(Itypes)
indexexprs = Array(Any, L)
j = 0
for i = 1:L
if Itypes[i] <: Real
indexexprs[i] = :($Vsym.indexes[$i])
else
j += 1
indexexprs[i] = :(unsafe_getindex($Vsym.indexes[$i], $(Isyms[j])))
end
end
# Note that we drop any extra indices. We're trusting that the indices are
# already checked to be in-bounds, so any extra indices must be 1 (and no-op)
if exhead == :nothing
exhead = Expr(:meta, :inline)
end
exhead, indexexprs
end