Distributions.jl provides much but all random number generation is done in Base and right now there is only one RNG, i.e. the Mersenne Twister implementation dSFMT.
2014-04-17 19:24 GMT+02:00 Miguel Bazdresch <[email protected]>: > The distributions.jl package extends Julia's random number capabilities, > it's worth a look: > > https://github.com/JuliaStats/Distributions.jl > > -- mb > > > On Thu, Apr 17, 2014 at 1:18 PM, X Du <[email protected]> wrote: > >> >> Thanks Isaiah, >> >> It seems that srand([*rng*], *seed*) does not work, I always got the >> error rng is not defined. >> I tried to set MersenneTwister([*2*]) and use rand(*rng::AbstractRNG*[, >> *dims...*]) to generate the random number. It did not work. >> >> Could you please give me an example? Many thanks in advance. >> >> Isaac >> >> >> On Thursday, April 17, 2014 12:45:01 PM UTC+2, X Du wrote: >>> >>> >>> Hi All, >>> >>> Is there some comments to save or load a particular state when >>> generating rand numbers? >>> e.g. the code in Matlab: >>> >>> stream = RandStream.getGlobalStream; >>> savedState = stream.State; >>> u1 = rand(1,5) >>> u1 = >>> 0.8147 0.9058 0.1270 0.9134 0.6324 >>> >>> stream.State = savedState; >>> u2 = rand(1,5) >>> u2 = >>> 0.8147 0.9058 0.1270 0.9134 0.6324 >>> >>> which can produce exactly the same random numbers. >>> >>> >>> Thanks! >>> >>> Isaac >>> >>> >>> >>> > -- Med venlig hilsen Andreas Noack Jensen
