X-Git-Url: http://git.megacz.com/?a=blobdiff_plain;f=System%2FRandom.hs;h=09a4a3911a4a6665081e823e1b5bb985f0f6ec79;hb=473718bc252b39bf0c4a1a681fa9ced1827150d8;hp=e83f525de418f3eb6c1485785d0cc53d9aed0686;hpb=7783a84ab51ff149885a96498cefcb7f31c27513;p=ghc-base.git

diff --git a/System/Random.hs b/System/Random.hs
index e83f525..09a4a39 100644
--- a/System/Random.hs
+++ b/System/Random.hs
@@ -56,10 +56,6 @@ import System.IO.Unsafe ( unsafePerformIO )
 import Data.IORef
 import Numeric		( readDec )
 
-#ifdef __GLASGOW_HASKELL__
-import GHC.IOBase	( stToIO )
-#endif
-
 -- The standard nhc98 implementation of Time.ClockTime does not match
 -- the extended one expected in this module, so we lash-up a quick
 -- replacement here.
@@ -72,7 +68,7 @@ getClockTime = do t <- readtime nullPtr;  return (TOD (toInteger t) ())
 
 {- $intro
 
-The "Random" library deals with the common task of pseudo-random
+This library deals with the common task of pseudo-random
 number generation. The library makes it possible to generate
 repeatable results, by starting with a specified initial random
 number generator; or to get different results on each run by using the 
@@ -121,8 +117,8 @@ class RandomGen g where
    -- default mathod
    genRange g = (minBound,maxBound)
 
-{- |The "Random" library provides one instance of 'RandomGen', the abstract data
-type 'StdGen'.
+{- |The "System.Random" library provides one instance of 'RandomGen', the
+abstract data type 'StdGen'.
 
 The result of repeatedly using next should be at least as statistically robust
 as the /Minimal Standard Random Number Generator/ described by
@@ -392,7 +388,7 @@ newStdGen = do
 
 {- |'getStdRandom' uses the supplied function to get a value from the current
 global random generator, and updates the global generator with the new generator
-returned by the function. For example, 'rollDice' gets a random integer between 1 and 6: 
+returned by the function. For example, @rollDice@ gets a random integer between 1 and 6: 
 
 >  rollDice :: IO Int
 >  rollDice = getStdRandom (randomR (1,6))