https://github.com/JuliaLang/julia
Revision 6b41538bef339dba09d80568c0065fa236c89b5a authored by Jeff Bezanson on 29 July 2016, 20:22:57 UTC, committed by GitHub on 29 July 2016, 20:22:57 UTC
ensure known_object_data is assigned before deserialize is called again
2 parent s e70de21 + d584142
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Tip revision: 6b41538bef339dba09d80568c0065fa236c89b5a authored by Jeff Bezanson on 29 July 2016, 20:22:57 UTC
Merge pull request #17619 from JuliaLang/jn/ser-typename
Tip revision: 6b41538
tuple.jl
# This file is a part of Julia. License is MIT: http://julialang.org/license

## indexing ##

length(t::Tuple) = nfields(t)
endof(t::Tuple) = length(t)
size(t::Tuple, d) = d==1 ? length(t) : throw(ArgumentError("invalid tuple dimension $d"))
getindex(t::Tuple, i::Int) = getfield(t, i)
getindex(t::Tuple, i::Real) = getfield(t, convert(Int, i))
getindex(t::Tuple, r::AbstractArray) = tuple([t[ri] for ri in r]...)
getindex(t::Tuple, b::AbstractArray{Bool}) = getindex(t,find(b))

## iterating ##

start(t::Tuple) = 1
done(t::Tuple, i::Int) = (length(t) < i)
next(t::Tuple, i::Int) = (t[i], i+1)

eachindex(t::Tuple) = 1:length(t)

function eachindex(t::Tuple, t2::Tuple...)
    @_inline_meta
    1:_maxlength(t, t2...)
end
_maxlength(t::Tuple) = length(t)
function _maxlength(t::Tuple, t2::Tuple, t3::Tuple...)
    @_inline_meta
    max(length(t), _maxlength(t2, t3...))
end

# this allows partial evaluation of bounded sequences of next() calls on tuples,
# while reducing to plain next() for arbitrary iterables.
indexed_next(t::Tuple, i::Int, state) = (t[i], i+1)
indexed_next(a::Array, i::Int, state) = (a[i], i+1)
indexed_next(I, i, state) = done(I,state) ? throw(BoundsError()) : next(I, state)

# Use dispatch to avoid a branch in first
first(::Tuple{}) = throw(ArgumentError("tuple must be non-empty"))
first(t::Tuple) = t[1]

# eltype

eltype(::Type{Tuple{}}) = Bottom
eltype{T}(::Type{Tuple{Vararg{T}}}) = T

# version of tail that doesn't throw on empty tuples (used in array indexing)
safe_tail(t::Tuple) = tail(t)
safe_tail(t::Tuple{}) = ()

# front (the converse of tail: it skips the last entry)

function front(t::Tuple)
    @_inline_meta
    _front((), t...)
end
front(::Tuple{}) = throw(ArgumentError("Cannot call front on an empty tuple"))
_front(out, v) = out
function _front(out, v, t...)
    @_inline_meta
    _front((out..., v), t...)
end

## mapping ##

ntuple(f::Function, n::Integer) =
    n<=0 ? () :
    n==1 ? (f(1),) :
    n==2 ? (f(1),f(2),) :
    n==3 ? (f(1),f(2),f(3),) :
    n==4 ? (f(1),f(2),f(3),f(4),) :
    n==5 ? (f(1),f(2),f(3),f(4),f(5),) :
    tuple(ntuple(f,n-5)..., f(n-4), f(n-3), f(n-2), f(n-1), f(n))

# inferrable ntuple
function ntuple{F,N}(f::F, ::Type{Val{N}})
    Core.typeassert(N, Int)
    _ntuple((), f, Val{N})
end

# Build up the output until it has length N
_ntuple{F,N}(out::NTuple{N}, f::F, ::Type{Val{N}}) = out
function _ntuple{F,N,M}(out::NTuple{M}, f::F, ::Type{Val{N}})
    @_inline_meta
    _ntuple((out..., f(M+1)), f, Val{N})
end

# 1 argument function
map(f, t::Tuple{})              = ()
map(f, t::Tuple{Any,})          = (f(t[1]),)
map(f, t::Tuple{Any, Any})      = (f(t[1]), f(t[2]))
map(f, t::Tuple{Any, Any, Any}) = (f(t[1]), f(t[2]), f(t[3]))
map(f, t::Tuple)                = (@_inline_meta; (f(t[1]), map(f,tail(t))...))
# stop inlining after some number of arguments to avoid code blowup
typealias Any16{N} Tuple{Any,Any,Any,Any,Any,Any,Any,Any,
                         Any,Any,Any,Any,Any,Any,Any,Any,Vararg{Any,N}}
function map(f, t::Any16)
    n = length(t)
    A = Array{Any}(n)
    for i=1:n
        A[i] = f(t[i])
    end
    (A...,)
end
# 2 argument function
map(f, t::Tuple{},        s::Tuple{})        = ()
map(f, t::Tuple{Any,},    s::Tuple{Any,})    = (f(t[1],s[1]),)
map(f, t::Tuple{Any,Any}, s::Tuple{Any,Any}) = (f(t[1],s[1]), f(t[2],s[2]))
function map(f, t::Tuple, s::Tuple)
    @_inline_meta
    (f(t[1],s[1]), map(f, tail(t), tail(s))...)
end
function map(f, t::Any16, s::Any16)
    n = length(t)
    A = Array{Any}(n)
    for i = 1:n
        A[i] = f(t[i], s[i])
    end
    (A...,)
end
# n argument function
heads() = ()
heads(t::Tuple, ts::Tuple...) = (t[1], heads(ts...)...)
tails() = ()
tails(t::Tuple, ts::Tuple...) = (tail(t), tails(ts...)...)
map(f, ::Tuple{}, ts::Tuple...) = ()
map(f, t1::Tuple, t2::Tuple, ts::Tuple...) = (f(heads(t1, t2, ts...)...), map(f, tails(t1, t2, ts...)...)...)


# type-stable padding
fill_to_length{N}(t::Tuple, val, ::Type{Val{N}}) = _ftl((), val, Val{N}, t...)
_ftl{N}(out::NTuple{N}, val, ::Type{Val{N}}) = out
function _ftl{N}(out::NTuple{N}, val, ::Type{Val{N}}, t...)
    @_inline_meta
    throw(ArgumentError("input tuple of length $(N+length(t)), requested $N"))
end
function _ftl{N}(out, val, ::Type{Val{N}}, t1, t...)
    @_inline_meta
    _ftl((out..., t1), val, Val{N}, t...)
end
function _ftl{N}(out, val, ::Type{Val{N}})
    @_inline_meta
    _ftl((out..., val), val, Val{N})
end

## comparison ##

function isequal(t1::Tuple, t2::Tuple)
    if length(t1) != length(t2)
        return false
    end
    for i = 1:length(t1)
        if !isequal(t1[i], t2[i])
            return false
        end
    end
    return true
end

function ==(t1::Tuple, t2::Tuple)
    if length(t1) != length(t2)
        return false
    end
    for i = 1:length(t1)
        if !(t1[i] == t2[i])
            return false
        end
    end
    return true
end

const tuplehash_seed = UInt === UInt64 ? 0x77cfa1eef01bca90 : 0xf01bca90
hash( ::Tuple{}, h::UInt)        = h + tuplehash_seed
hash(x::Tuple{Any,}, h::UInt)    = hash(x[1], hash((), h))
hash(x::Tuple{Any,Any}, h::UInt) = hash(x[1], hash(x[2], hash((), h)))
hash(x::Tuple, h::UInt)          = hash(x[1], hash(x[2], hash(tail(tail(x)), h)))

function isless(t1::Tuple, t2::Tuple)
    n1, n2 = length(t1), length(t2)
    for i = 1:min(n1, n2)
        a, b = t1[i], t2[i]
        if !isequal(a, b)
            return isless(a, b)
        end
    end
    return n1 < n2
end

## functions ##

isempty(x::Tuple{}) = true
isempty(x::Tuple) = false

revargs() = ()
revargs(x, r...) = (revargs(r...)..., x)

reverse(t::Tuple) = revargs(t...)

## specialized reduction ##

# TODO: these definitions cannot yet be combined, since +(x...)
# where x might be any tuple matches too many methods.
sum(x::Tuple{Any, Vararg{Any}}) = +(x...)

# NOTE: should remove, but often used on array sizes
prod(x::Tuple{}) = 1
prod(x::Tuple{Any, Vararg{Any}}) = *(x...)

all(x::Tuple{}) = true
all(x::Tuple{Bool}) = x[1]
all(x::Tuple{Bool, Bool}) = x[1]&x[2]
all(x::Tuple{Bool, Bool, Bool}) = x[1]&x[2]&x[3]
# use generic reductions for the rest

any(x::Tuple{}) = false
any(x::Tuple{Bool}) = x[1]
any(x::Tuple{Bool, Bool}) = x[1]|x[2]
any(x::Tuple{Bool, Bool, Bool}) = x[1]|x[2]|x[3]
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