A PureMT generator is immutable, so must be threaded through the monad in which you are sampling. There are RandomSource instances provided for a few special cases, including "IORef PureMT" in the IO monad. For example: main = do mt <- newPureMT src <- newIORef mt flips <- runRVar (replicateM 20 flipCoin) src print flips Alternatively, the functions in the module you mentioned can be used to define additional instances, such as: instance MonadRandom (State PureMT) where supportedPrims _ _ = True getSupportedRandomPrim = getRandomPrimFromPureMTState And RandomSource instances look almost the same. See the Data.Random.Source.PureMT source for examples. (I thought I had included this particular instance in the distribution but I apparently missed it. The next release will probably include this as well as corresponding instances for the 'transformers' package, possibly separated out into 'random-fu-mtl' and 'random-fu-transformers' packages). The "StdRandom" type is a convenient "RandomSource" designating this instance in the State PureMT monad. Personally, I prefer to use the "sample" function for this purpose, as well as the "sampleFrom" function in place of runRVar/runRVarT. GHCi does not display the "sample" functions' types properly - they are defined for RVarT as well as for all Distribution instances. Sorry it took so long responding. -- James On Sep 2, 2010, at 10:01 AM, Alex Rozenshteyn wrote:
I seem to be having confusion at the runRVar level of random-fu.
I can't figure out how to use the Data.Random.Source.PureMT module to get a meaningful random source (I can't get my code to type-check).
I wrote a [trivial] flipCoin function
flipCoin = uniform False True and am trying to fill in the final place of runRVar :t runRVar (replicateM 20 flipCoin) runRVar (replicateM 20 flipCoin) :: (RandomSource m s) => s -> m [Bool]
-- Alex R
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