543 lines
22 KiB
Julia
543 lines
22 KiB
Julia
# This file is a part of Julia. License is MIT: https://julialang.org/license
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abstract type AbstractCartesianIndex{N} end # This is a hacky forward declaration for CartesianIndex
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const ViewIndex = Union{Real, AbstractArray}
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const ScalarIndex = Real
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# L is true if the view itself supports fast linear indexing
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struct SubArray{T,N,P,I,L} <: AbstractArray{T,N}
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parent::P
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indexes::I
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offset1::Int # for linear indexing and pointer, only valid when L==true
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stride1::Int # used only for linear indexing
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function SubArray{T,N,P,I,L}(parent, indexes, offset1, stride1) where {T,N,P,I,L}
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@_inline_meta
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check_parent_index_match(parent, indexes)
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new(parent, indexes, offset1, stride1)
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end
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end
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# Compute the linear indexability of the indices, and combine it with the linear indexing of the parent
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function SubArray(parent::AbstractArray, indexes::Tuple)
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@_inline_meta
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SubArray(IndexStyle(viewindexing(indexes), IndexStyle(parent)), parent, ensure_indexable(indexes), index_dimsum(indexes...))
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end
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function SubArray(::IndexCartesian, parent::P, indexes::I, ::NTuple{N,Any}) where {P,I,N}
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@_inline_meta
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SubArray{eltype(P), N, P, I, false}(parent, indexes, 0, 0)
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end
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function SubArray(::IndexLinear, parent::P, indexes::I, ::NTuple{N,Any}) where {P,I,N}
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@_inline_meta
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# Compute the stride and offset
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stride1 = compute_stride1(parent, indexes)
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SubArray{eltype(P), N, P, I, true}(parent, indexes, compute_offset1(parent, stride1, indexes), stride1)
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end
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check_parent_index_match(parent, indexes) = check_parent_index_match(parent, index_ndims(indexes...))
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check_parent_index_match(parent::AbstractArray{T,N}, ::NTuple{N, Bool}) where {T,N} = nothing
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check_parent_index_match(parent, ::NTuple{N, Bool}) where {N} =
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throw(ArgumentError("number of indices ($N) must match the parent dimensionality ($(ndims(parent)))"))
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# This computes the linear indexing compatability for a given tuple of indices
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viewindexing() = IndexLinear()
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# Leading scalar indexes simply increase the stride
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viewindexing(I::Tuple{ScalarIndex, Vararg{Any}}) = (@_inline_meta; viewindexing(tail(I)))
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# Slices may begin a section which may be followed by any number of Slices
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viewindexing(I::Tuple{Slice, Slice, Vararg{Any}}) = (@_inline_meta; viewindexing(tail(I)))
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# A UnitRange can follow Slices, but only if all other indices are scalar
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viewindexing(I::Tuple{Slice, UnitRange, Vararg{ScalarIndex}}) = IndexLinear()
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# In general, ranges are only fast if all other indices are scalar
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viewindexing(I::Tuple{Union{Range, Slice}, Vararg{ScalarIndex}}) = IndexLinear()
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# All other index combinations are slow
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viewindexing(I::Tuple{Vararg{Any}}) = IndexCartesian()
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# Of course, all other array types are slow
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viewindexing(I::Tuple{AbstractArray, Vararg{Any}}) = IndexCartesian()
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# Simple utilities
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size(V::SubArray) = (@_inline_meta; map(n->Int(unsafe_length(n)), indices(V)))
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similar(V::SubArray, T::Type, dims::Dims) = similar(V.parent, T, dims)
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parent(V::SubArray) = V.parent
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parentindexes(V::SubArray) = V.indexes
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parent(a::AbstractArray) = a
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"""
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parentindexes(A)
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From an array view `A`, returns the corresponding indexes in the parent.
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"""
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parentindexes(a::AbstractArray) = ntuple(i->OneTo(size(a,i)), ndims(a))
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## SubArray creation
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# We always assume that the dimensionality of the parent matches the number of
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# indices that end up getting passed to it, so we store the parent as a
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# ReshapedArray view if necessary. The trouble is that arrays of `CartesianIndex`
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# can make the number of effective indices not equal to length(I).
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_maybe_reshape_parent(A::AbstractArray, ::NTuple{1, Bool}) = reshape(A, Val{1})
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_maybe_reshape_parent(A::AbstractArray{<:Any,1}, ::NTuple{1, Bool}) = reshape(A, Val{1})
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_maybe_reshape_parent(A::AbstractArray{<:Any,N}, ::NTuple{N, Bool}) where {N} = A
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_maybe_reshape_parent(A::AbstractArray, ::NTuple{N, Bool}) where {N} = reshape(A, Val{N}) # TODO: DEPRECATE FOR #14770
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"""
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view(A, inds...)
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Like [`getindex`](@ref), but returns a view into the parent array `A` with the
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given indices instead of making a copy. Calling [`getindex`](@ref) or
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[`setindex!`](@ref) on the returned `SubArray` computes the
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indices to the parent array on the fly without checking bounds.
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```jldoctest
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julia> A = [1 2; 3 4]
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2×2 Array{Int64,2}:
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1 2
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3 4
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julia> b = view(A, :, 1)
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2-element SubArray{Int64,1,Array{Int64,2},Tuple{Base.Slice{Base.OneTo{Int64}},Int64},true}:
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1
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3
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julia> fill!(b, 0)
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2-element SubArray{Int64,1,Array{Int64,2},Tuple{Base.Slice{Base.OneTo{Int64}},Int64},true}:
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0
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0
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julia> A # Note A has changed even though we modified b
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2×2 Array{Int64,2}:
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0 2
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0 4
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```
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"""
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function view(A::AbstractArray, I...)
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@_inline_meta
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J = to_indices(A, I)
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@boundscheck checkbounds(A, J...)
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unsafe_view(_maybe_reshape_parent(A, index_ndims(J...)), J...)
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end
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function unsafe_view(A::AbstractArray, I::ViewIndex...)
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@_inline_meta
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SubArray(A, I)
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end
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# When we take the view of a view, it's often possible to "reindex" the parent
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# view's indices such that we can "pop" the parent view and keep just one layer
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# of indirection. But we can't always do this because arrays of `CartesianIndex`
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# might span multiple parent indices, making the reindex calculation very hard.
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# So we use _maybe_reindex to figure out if there are any arrays of
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# `CartesianIndex`, and if so, we punt and keep two layers of indirection.
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unsafe_view(V::SubArray, I::ViewIndex...) = (@_inline_meta; _maybe_reindex(V, I))
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_maybe_reindex(V, I) = (@_inline_meta; _maybe_reindex(V, I, I))
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_maybe_reindex(V, I, ::Tuple{AbstractArray{<:AbstractCartesianIndex}, Vararg{Any}}) =
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(@_inline_meta; SubArray(V, I))
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# But allow arrays of CartesianIndex{1}; they behave just like arrays of Ints
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_maybe_reindex(V, I, A::Tuple{AbstractArray{<:AbstractCartesianIndex{1}}, Vararg{Any}}) =
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(@_inline_meta; _maybe_reindex(V, I, tail(A)))
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_maybe_reindex(V, I, A::Tuple{Any, Vararg{Any}}) = (@_inline_meta; _maybe_reindex(V, I, tail(A)))
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function _maybe_reindex(V, I, ::Tuple{})
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@_inline_meta
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@inbounds idxs = to_indices(V.parent, reindex(V, V.indexes, I))
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SubArray(V.parent, idxs)
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end
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## Re-indexing is the heart of a view, transforming A[i, j][x, y] to A[i[x], j[y]]
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#
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# Recursively look through the heads of the parent- and sub-indexes, considering
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# the following cases:
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# * Parent index is array -> re-index that with one or more sub-indexes (one per dimension)
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# * Parent index is Colon -> just use the sub-index as provided
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# * Parent index is scalar -> that dimension was dropped, so skip the sub-index and use the index as is
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AbstractZeroDimArray{T} = AbstractArray{T, 0}
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reindex(V, ::Tuple{}, ::Tuple{}) = ()
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# Skip dropped scalars, so simply peel them off the parent indices and continue
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reindex(V, idxs::Tuple{ScalarIndex, Vararg{Any}}, subidxs::Tuple{Vararg{Any}}) =
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(@_propagate_inbounds_meta; (idxs[1], reindex(V, tail(idxs), subidxs)...))
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# Slices simply pass their subindexes straight through
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reindex(V, idxs::Tuple{Slice, Vararg{Any}}, subidxs::Tuple{Any, Vararg{Any}}) =
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(@_propagate_inbounds_meta; (subidxs[1], reindex(V, tail(idxs), tail(subidxs))...))
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# Re-index into parent vectors with one subindex
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reindex(V, idxs::Tuple{AbstractVector, Vararg{Any}}, subidxs::Tuple{Any, Vararg{Any}}) =
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(@_propagate_inbounds_meta; (idxs[1][subidxs[1]], reindex(V, tail(idxs), tail(subidxs))...))
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# Parent matrices are re-indexed with two sub-indices
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reindex(V, idxs::Tuple{AbstractMatrix, Vararg{Any}}, subidxs::Tuple{Any, Any, Vararg{Any}}) =
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(@_propagate_inbounds_meta; (idxs[1][subidxs[1], subidxs[2]], reindex(V, tail(idxs), tail(tail(subidxs)))...))
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# In general, we index N-dimensional parent arrays with N indices
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@generated function reindex(V, idxs::Tuple{AbstractArray{T,N}, Vararg{Any}}, subidxs::Tuple{Vararg{Any}}) where {T,N}
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if length(subidxs.parameters) >= N
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subs = [:(subidxs[$d]) for d in 1:N]
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tail = [:(subidxs[$d]) for d in N+1:length(subidxs.parameters)]
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:(@_propagate_inbounds_meta; (idxs[1][$(subs...)], reindex(V, tail(idxs), ($(tail...),))...))
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else
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:(throw(ArgumentError("cannot re-index $(ndims(V)) dimensional SubArray with fewer than $(ndims(V)) indices\nThis should not occur; please submit a bug report.")))
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end
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end
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# In general, we simply re-index the parent indices by the provided ones
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SlowSubArray{T,N,P,I} = SubArray{T,N,P,I,false}
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function getindex(V::SlowSubArray{T,N}, I::Vararg{Int,N}) where {T,N}
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@_inline_meta
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@boundscheck checkbounds(V, I...)
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@inbounds r = V.parent[reindex(V, V.indexes, I)...]
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r
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end
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FastSubArray{T,N,P,I} = SubArray{T,N,P,I,true}
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function getindex(V::FastSubArray, i::Int)
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@_inline_meta
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@boundscheck checkbounds(V, i)
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@inbounds r = V.parent[V.offset1 + V.stride1*i]
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r
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end
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# We can avoid a multiplication if the first parent index is a Colon or UnitRange
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FastContiguousSubArray{T,N,P,I<:Tuple{Union{Slice, UnitRange}, Vararg{Any}}} = SubArray{T,N,P,I,true}
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function getindex(V::FastContiguousSubArray, i::Int)
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@_inline_meta
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@boundscheck checkbounds(V, i)
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@inbounds r = V.parent[V.offset1 + i]
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r
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end
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function setindex!(V::SlowSubArray{T,N}, x, I::Vararg{Int,N}) where {T,N}
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@_inline_meta
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@boundscheck checkbounds(V, I...)
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@inbounds V.parent[reindex(V, V.indexes, I)...] = x
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V
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end
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function setindex!(V::FastSubArray, x, i::Int)
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@_inline_meta
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@boundscheck checkbounds(V, i)
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@inbounds V.parent[V.offset1 + V.stride1*i] = x
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V
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end
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function setindex!(V::FastContiguousSubArray, x, i::Int)
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@_inline_meta
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@boundscheck checkbounds(V, i)
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@inbounds V.parent[V.offset1 + i] = x
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V
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end
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IndexStyle(::Type{<:FastSubArray}) = IndexLinear()
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IndexStyle(::Type{<:SubArray}) = IndexCartesian()
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# Strides are the distance between adjacent elements in a given dimension,
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# so they are well-defined even for non-linear memory layouts
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strides(V::SubArray) = substrides(V.parent, V.indexes)
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substrides(parent, I::Tuple) = substrides(1, parent, 1, I)
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substrides(s, parent, dim, ::Tuple{}) = ()
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substrides(s, parent, dim, I::Tuple{ScalarIndex, Vararg{Any}}) = (substrides(s*size(parent, dim), parent, dim+1, tail(I))...)
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substrides(s, parent, dim, I::Tuple{Slice, Vararg{Any}}) = (s, substrides(s*size(parent, dim), parent, dim+1, tail(I))...)
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substrides(s, parent, dim, I::Tuple{Range, Vararg{Any}}) = (s*step(I[1]), substrides(s*size(parent, dim), parent, dim+1, tail(I))...)
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substrides(s, parent, dim, I::Tuple{Any, Vararg{Any}}) = throw(ArgumentError("strides is invalid for SubArrays with indices of type $(typeof(I[1]))"))
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stride(V::SubArray, d::Integer) = d <= ndims(V) ? strides(V)[d] : strides(V)[end] * size(V)[end]
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compute_stride1(parent::AbstractArray, I::NTuple{N,Any}) where {N} =
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(@_inline_meta; compute_stride1(1, fill_to_length(indices(parent), OneTo(1), Val{N}), I))
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compute_stride1(s, inds, I::Tuple{}) = s
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compute_stride1(s, inds, I::Tuple{ScalarIndex, Vararg{Any}}) =
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(@_inline_meta; compute_stride1(s*unsafe_length(inds[1]), tail(inds), tail(I)))
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compute_stride1(s, inds, I::Tuple{Range, Vararg{Any}}) = s*step(I[1])
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compute_stride1(s, inds, I::Tuple{Slice, Vararg{Any}}) = s
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compute_stride1(s, inds, I::Tuple{Any, Vararg{Any}}) = throw(ArgumentError("invalid strided index type $(typeof(I[1]))"))
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iscontiguous(A::SubArray) = iscontiguous(typeof(A))
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iscontiguous(::Type{<:SubArray}) = false
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iscontiguous(::Type{<:FastContiguousSubArray}) = true
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first_index(V::FastSubArray) = V.offset1 + V.stride1 # cached for fast linear SubArrays
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function first_index(V::SubArray)
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P, I = parent(V), V.indexes
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s1 = compute_stride1(P, I)
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s1 + compute_offset1(P, s1, I)
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end
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# Computing the first index simply steps through the indices, accumulating the
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# sum of index each multiplied by the parent's stride.
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# The running sum is `f`; the cumulative stride product is `s`.
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# If the parent is a vector, then we offset the parent's own indices with parameters of I
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compute_offset1(parent::AbstractVector, stride1::Integer, I::Tuple{Range}) =
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(@_inline_meta; first(I[1]) - first(indices1(I[1]))*stride1)
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# If the result is one-dimensional and it's a Colon, then linear
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# indexing uses the indices along the given dimension. Otherwise
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# linear indexing always starts with 1.
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compute_offset1(parent, stride1::Integer, I::Tuple) =
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(@_inline_meta; compute_offset1(parent, stride1, find_extended_dims(I)..., I))
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compute_offset1(parent, stride1::Integer, dims::Tuple{Int}, inds::Tuple{Slice}, I::Tuple) =
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(@_inline_meta; compute_linindex(parent, I) - stride1*first(indices(parent, dims[1]))) # index-preserving case
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compute_offset1(parent, stride1::Integer, dims, inds, I::Tuple) =
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(@_inline_meta; compute_linindex(parent, I) - stride1) # linear indexing starts with 1
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function compute_linindex(parent, I::NTuple{N,Any}) where N
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@_inline_meta
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IP = fill_to_length(indices(parent), OneTo(1), Val{N})
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compute_linindex(1, 1, IP, I)
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end
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function compute_linindex(f, s, IP::Tuple, I::Tuple{ScalarIndex, Vararg{Any}})
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@_inline_meta
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Δi = I[1]-first(IP[1])
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compute_linindex(f + Δi*s, s*unsafe_length(IP[1]), tail(IP), tail(I))
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end
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function compute_linindex(f, s, IP::Tuple, I::Tuple{Any, Vararg{Any}})
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@_inline_meta
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Δi = first(I[1])-first(IP[1])
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compute_linindex(f + Δi*s, s*unsafe_length(IP[1]), tail(IP), tail(I))
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end
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compute_linindex(f, s, IP::Tuple, I::Tuple{}) = f
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find_extended_dims(I) = (@_inline_meta; _find_extended_dims((), (), 1, I...))
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_find_extended_dims(dims, inds, dim) = dims, inds
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_find_extended_dims(dims, inds, dim, ::ScalarIndex, I...) =
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(@_inline_meta; _find_extended_dims(dims, inds, dim+1, I...))
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_find_extended_dims(dims, inds, dim, i1, I...) =
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(@_inline_meta; _find_extended_dims((dims..., dim), (inds..., i1), dim+1, I...))
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unsafe_convert(::Type{Ptr{T}}, V::SubArray{T,N,P,<:Tuple{Vararg{RangeIndex}}}) where {T,N,P} =
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unsafe_convert(Ptr{T}, V.parent) + (first_index(V)-1)*sizeof(T)
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pointer(V::FastSubArray, i::Int) = pointer(V.parent, V.offset1 + V.stride1*i)
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pointer(V::FastContiguousSubArray, i::Int) = pointer(V.parent, V.offset1 + i)
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pointer(V::SubArray, i::Int) = _pointer(V, i)
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_pointer(V::SubArray{<:Any,1}, i::Int) = pointer(V, (i,))
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_pointer(V::SubArray, i::Int) = pointer(V, ind2sub(indices(V), i))
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function pointer(V::SubArray{T,N,<:Array,<:Tuple{Vararg{RangeIndex}}}, is::Tuple{Vararg{Int}}) where {T,N}
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index = first_index(V)
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strds = strides(V)
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for d = 1:length(is)
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index += (is[d]-1)*strds[d]
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end
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return pointer(V.parent, index)
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end
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# indices are taken from the range/vector
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# Since bounds-checking is performance-critical and uses
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# indices, it's worth optimizing these implementations thoroughly
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indices(S::SubArray) = (@_inline_meta; _indices_sub(S, S.indexes...))
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_indices_sub(S::SubArray) = ()
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_indices_sub(S::SubArray, ::Real, I...) = (@_inline_meta; _indices_sub(S, I...))
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function _indices_sub(S::SubArray, i1::AbstractArray, I...)
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@_inline_meta
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(unsafe_indices(i1)..., _indices_sub(S, I...)...)
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end
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## Compatability
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# deprecate?
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function parentdims(s::SubArray)
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nd = ndims(s)
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dimindex = Vector{Int}(nd)
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sp = strides(s.parent)
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sv = strides(s)
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j = 1
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for i = 1:ndims(s.parent)
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r = s.indexes[i]
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if j <= nd && (isa(r,Union{Slice,Range}) ? sp[i]*step(r) : sp[i]) == sv[j]
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dimindex[j] = i
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j += 1
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end
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end
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dimindex
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end
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"""
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replace_ref_end!(ex)
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Recursively replace occurrences of the symbol :end in a "ref" expression (i.e. A[...]) `ex`
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with the appropriate function calls (`endof`, `size` or `trailingsize`). Replacement uses
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the closest enclosing ref, so
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A[B[end]]
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should transform to
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A[B[endof(B)]]
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"""
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replace_ref_end!(ex) = replace_ref_end_!(ex, nothing)[1]
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# replace_ref_end_!(ex,withex) returns (new ex, whether withex was used)
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function replace_ref_end_!(ex, withex)
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used_withex = false
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if isa(ex,Symbol) && ex == :end
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withex === nothing && error("Invalid use of end")
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return withex, true
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elseif isa(ex,Expr)
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if ex.head == :ref
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ex.args[1], used_withex = replace_ref_end_!(ex.args[1],withex)
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S = isa(ex.args[1],Symbol) ? ex.args[1]::Symbol : gensym(:S) # temp var to cache ex.args[1] if needed
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used_S = false # whether we actually need S
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# new :ref, so redefine withex
|
||
nargs = length(ex.args)-1
|
||
if nargs == 0
|
||
return ex, used_withex
|
||
elseif nargs == 1
|
||
# replace with endof(S)
|
||
ex.args[2], used_S = replace_ref_end_!(ex.args[2],:($endof($S)))
|
||
else
|
||
n = 1
|
||
J = endof(ex.args)
|
||
for j = 2:J-1
|
||
exj, used = replace_ref_end_!(ex.args[j],:($size($S,$n)))
|
||
used_S |= used
|
||
ex.args[j] = exj
|
||
if isa(exj,Expr) && exj.head == :...
|
||
# splatted object
|
||
exjs = exj.args[1]
|
||
n = :($n + length($exjs))
|
||
elseif isa(n, Expr)
|
||
# previous expression splatted
|
||
n = :($n + 1)
|
||
else
|
||
# an integer
|
||
n += 1
|
||
end
|
||
end
|
||
ex.args[J], used = replace_ref_end_!(ex.args[J],:($trailingsize($S,$n)))
|
||
used_S |= used
|
||
end
|
||
if used_S && S !== ex.args[1]
|
||
S0 = ex.args[1]
|
||
ex.args[1] = S
|
||
ex = Expr(:let, ex, :($S = $S0))
|
||
end
|
||
else
|
||
# recursive search
|
||
for i = eachindex(ex.args)
|
||
ex.args[i], used = replace_ref_end_!(ex.args[i],withex)
|
||
used_withex |= used
|
||
end
|
||
end
|
||
end
|
||
ex, used_withex
|
||
end
|
||
|
||
"""
|
||
@view A[inds...]
|
||
|
||
Creates a `SubArray` from an indexing expression. This can only be applied directly to a
|
||
reference expression (e.g. `@view A[1,2:end]`), and should *not* be used as the target of
|
||
an assignment (e.g. `@view(A[1,2:end]) = ...`). See also [`@views`](@ref)
|
||
to switch an entire block of code to use views for slicing.
|
||
|
||
```jldoctest
|
||
julia> A = [1 2; 3 4]
|
||
2×2 Array{Int64,2}:
|
||
1 2
|
||
3 4
|
||
|
||
julia> b = @view A[:, 1]
|
||
2-element SubArray{Int64,1,Array{Int64,2},Tuple{Base.Slice{Base.OneTo{Int64}},Int64},true}:
|
||
1
|
||
3
|
||
|
||
julia> fill!(b, 0)
|
||
2-element SubArray{Int64,1,Array{Int64,2},Tuple{Base.Slice{Base.OneTo{Int64}},Int64},true}:
|
||
0
|
||
0
|
||
|
||
julia> A
|
||
2×2 Array{Int64,2}:
|
||
0 2
|
||
0 4
|
||
```
|
||
"""
|
||
macro view(ex)
|
||
if Meta.isexpr(ex, :ref)
|
||
ex = replace_ref_end!(ex)
|
||
if Meta.isexpr(ex, :ref)
|
||
ex = Expr(:call, view, ex.args...)
|
||
else # ex replaced by let ...; foo[...]; end
|
||
assert(Meta.isexpr(ex, :let) && Meta.isexpr(ex.args[1], :ref))
|
||
ex.args[1] = Expr(:call, view, ex.args[1].args...)
|
||
end
|
||
Expr(:&&, true, esc(ex))
|
||
else
|
||
throw(ArgumentError("Invalid use of @view macro: argument must be a reference expression A[...]."))
|
||
end
|
||
end
|
||
|
||
############################################################################
|
||
# @views macro code:
|
||
|
||
# maybeview is like getindex, but returns a view for slicing operations
|
||
# (while remaining equivalent to getindex for scalar indices and non-array types)
|
||
@propagate_inbounds maybeview(A, args...) = getindex(A, args...)
|
||
@propagate_inbounds maybeview(A::AbstractArray, args...) = view(A, args...)
|
||
@propagate_inbounds maybeview(A::AbstractArray, args::Number...) = getindex(A, args...)
|
||
@propagate_inbounds maybeview(A) = getindex(A)
|
||
@propagate_inbounds maybeview(A::AbstractArray) = getindex(A)
|
||
|
||
# _views implements the transformation for the @views macro.
|
||
# @views calls esc(_views(...)) to work around #20241,
|
||
# so any function calls we insert (to maybeview, or to
|
||
# size and endof in replace_ref_end!) must be interpolated
|
||
# as values rather than as symbols to ensure that they are called
|
||
# from Base rather than from the caller's scope.
|
||
_views(x) = x
|
||
function _views(ex::Expr)
|
||
if ex.head in (:(=), :(.=))
|
||
# don't use view for ref on the lhs of an assignment,
|
||
# but still use views for the args of the ref:
|
||
lhs = ex.args[1]
|
||
Expr(ex.head, Meta.isexpr(lhs, :ref) ?
|
||
Expr(:ref, _views.(lhs.args)...) : _views(lhs),
|
||
_views(ex.args[2]))
|
||
elseif ex.head == :ref
|
||
Expr(:call, maybeview, _views.(ex.args)...)
|
||
else
|
||
h = string(ex.head)
|
||
# don't use view on the lhs of an op-assignment a[i...] += ...
|
||
if last(h) == '=' && Meta.isexpr(ex.args[1], :ref)
|
||
lhs = ex.args[1]
|
||
|
||
# temp vars to avoid recomputing a and i,
|
||
# which will be assigned in a let block:
|
||
a = gensym(:a)
|
||
i = [gensym(:i) for k = 1:length(lhs.args)-1]
|
||
|
||
# for splatted indices like a[i, j...], we need to
|
||
# splat the corresponding temp var.
|
||
I = similar(i, Any)
|
||
for k = 1:length(i)
|
||
if Meta.isexpr(lhs.args[k+1], :...)
|
||
I[k] = Expr(:..., i[k])
|
||
lhs.args[k+1] = lhs.args[k+1].args[1] # unsplat
|
||
else
|
||
I[k] = i[k]
|
||
end
|
||
end
|
||
|
||
Expr(:let,
|
||
Expr(first(h) == '.' ? :(.=) : :(=), :($a[$(I...)]),
|
||
Expr(:call, Symbol(h[1:end-1]),
|
||
:($maybeview($a, $(I...))),
|
||
_views.(ex.args[2:end])...)),
|
||
:($a = $(_views(lhs.args[1]))),
|
||
[:($(i[k]) = $(_views(lhs.args[k+1]))) for k=1:length(i)]...)
|
||
else
|
||
Expr(ex.head, _views.(ex.args)...)
|
||
end
|
||
end
|
||
end
|
||
|
||
"""
|
||
@views expression
|
||
|
||
Convert every array-slicing operation in the given expression
|
||
(which may be a `begin`/`end` block, loop, function, etc.)
|
||
to return a view. Scalar indices, non-array types, and
|
||
explicit `getindex` calls (as opposed to `array[...]`) are
|
||
unaffected.
|
||
|
||
Note that the `@views` macro only affects `array[...]` expressions
|
||
that appear explicitly in the given `expression`, not array slicing that
|
||
occurs in functions called by that code.
|
||
"""
|
||
macro views(x)
|
||
esc(_views(replace_ref_end!(x)))
|
||
end
|