Works like this (on 0.3.0-rc3):
*julia> **methods(rand)*
*# 31 methods for generic function "rand":*
*rand(::Type{Float64}) at random.jl:88*
*rand() at random.jl:89*
*rand(::Type{Float32}) at random.jl:91*
*rand(::Type{Float16}) at random.jl:92*
*rand{T<:Real}(::Type{Complex{T<:Real}}) at random.jl:94*
*rand(r::MersenneTwister) at random.jl:97*
*rand(::Type{Uint8}) at random.jl:104*
*rand(::Type{Uint16}) at random.jl:105*
*rand(::Type{Uint32}) at random.jl:106*
*rand(::Type{Uint64}) at random.jl:107*
*rand(::Type{Uint128}) at random.jl:108*
*rand(::Type{Int8}) at random.jl:110*
*rand(::Type{Int16}) at random.jl:111*
*rand(::Type{Int32}) at random.jl:112*
*rand(::Type{Int64}) at random.jl:113*
*rand(::Type{Int128}) at random.jl:114*
*rand(::Type{Float64},dims::(Int64...,)) at random.jl:118*
*rand(::Type{Float64},dims::Int64...) at random.jl:119*
*rand(dims::(Int64...,)) at random.jl:121*
*rand(dims::Int64...) at random.jl:122*
*rand(r::AbstractRNG,dims::(Int64...,)) at random.jl:124*
*rand(r::AbstractRNG,dims::Int64...) at random.jl:125*
*rand{T<:Number}(::Type{T<:Number}) at random.jl:142*
*rand(T::Type{T<:Top},dims::(Int64...,)) at random.jl:141*
*rand{T<:Number}(::Type{T<:Number},dims::Int64...) at random.jl:143*
*rand{T<:Union(Int64,Uint64)}(g::RandIntGen{T<:Union(Int64,Uint64),Uint64})
at random.jl:185*
*rand{T<:Integer,U<:Unsigned}(g::RandIntGen{T<:Integer,U<:Unsigned}) at
random.jl:201*
*rand{T<:Union(Bool,Unsigned,Char,Signed)}(r::UnitRange{T<:Union(Bool,Unsigned,Char,Signed)})
at random.jl:208*
*rand{T}(r::Range{T}) at random.jl:209*
*rand{T}(r::Range{T},dims::(Int64...,)) at random.jl:236*
*rand(r::Range{T},dims::Int64...) at random.jl:237*
*julia> **rand(Int32)*
*-1091619314*
*julia> **rand(Int32, 10)*
*10-element Array{Int32,1}:*
* -232135574*
* -1289647599*
* -1136027271*
* 575399837*
* -761829090*
* -1955750348*
* -2129358352*
* -554861937*
* -934832989*
* -1179801152*
Am Montag, 11. August 2014 01:14:08 UTC+2 schrieb Jeff Waller:
>
> Seems like the intention is to cover many possibilities. This would be
> the typical rand but with type Int32 not Int64 for example.
>
> *julia> **rand(2)*
>
> *2-element Array{Float64,1}:*
>
> * 0.690068*
>
> * 0.137219*
>
> *julia> **rand(int32(2))*
>
> *ERROR: `rand` has no method matching rand(::Int32)*
>
> Is there a reason for this just kind of got overlooked because the usage
> is rare?
>
