Merge pull request #18679 from JuliaLang/jn/backports265.1

backport of changes in #17057 that don't require new worlds

Author: vtjnash

base/abstractarray.jl

@@ -1,32 +1,7 @@
 # This file is a part of Julia. License is MIT: http://julialang.org/license
 
-## Type aliases for convenience ##
-
-typealias AbstractVector{T} AbstractArray{T,1}
-typealias AbstractMatrix{T} AbstractArray{T,2}
-typealias AbstractVecOrMat{T} Union{AbstractVector{T}, AbstractMatrix{T}}
-typealias RangeIndex Union{Int, Range{Int}, AbstractUnitRange{Int}, Colon}
-typealias DimOrInd Union{Integer, AbstractUnitRange}
-typealias IntOrInd Union{Int, AbstractUnitRange}
-typealias DimsOrInds{N} NTuple{N,DimOrInd}
-typealias NeedsShaping Union{Tuple{Integer,Vararg{Integer}}, Tuple{OneTo,Vararg{OneTo}}}
-
-macro _inline_pure_meta()
-    Expr(:meta, :inline, :pure)
-end
-
 ## Basic functions ##
 
-vect() = Array{Any,1}(0)
-vect{T}(X::T...) = T[ X[i] for i=1:length(X) ]
-
-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.
-    copy!(Array{T,1}(length(X)), X)
-end
-
 """
     size(A::AbstractArray, [dim...])
 

base/array.jl

@@ -2,6 +2,17 @@
 
 ## array.jl: Dense arrays
 
+## Type aliases for convenience ##
+
+typealias AbstractVector{T} AbstractArray{T,1}
+typealias AbstractMatrix{T} AbstractArray{T,2}
+typealias AbstractVecOrMat{T} Union{AbstractVector{T}, AbstractMatrix{T}}
+typealias RangeIndex Union{Int, Range{Int}, AbstractUnitRange{Int}, Colon}
+typealias DimOrInd Union{Integer, AbstractUnitRange}
+typealias IntOrInd Union{Int, AbstractUnitRange}
+typealias DimsOrInds{N} NTuple{N,DimOrInd}
+typealias NeedsShaping Union{Tuple{Integer,Vararg{Integer}}, Tuple{OneTo,Vararg{OneTo}}}
+
 typealias Vector{T} Array{T,1}
 typealias Matrix{T} Array{T,2}
 typealias VecOrMat{T} Union{Vector{T}, Matrix{T}}
@@ -14,6 +25,16 @@ typealias DenseVecOrMat{T} Union{DenseVector{T}, DenseMatrix{T}}
 
 import Core: arraysize, arrayset, arrayref
 
+vect() = Array{Any,1}(0)
+vect{T}(X::T...) = T[ X[i] for i=1:length(X) ]
+
+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 copy!(Array{T,1}(length(X)), X)
+end
+
 size(a::Array, d) = arraysize(a, d)
 size(a::Vector) = (arraysize(a,1),)
 size(a::Matrix) = (arraysize(a,1), arraysize(a,2))

base/coreimg.jl

@@ -45,8 +45,8 @@ Symbol(a::Array{UInt8,1}) =
     ccall(:jl_symbol_n, Ref{Symbol}, (Ptr{UInt8}, Int32), a, length(a))
 
 # core array operations
-include("abstractarray.jl")
 include("array.jl")
+include("abstractarray.jl")
 
 #TODO: eliminate Dict from inference
 include("hashing.jl")