Remove defunct parts of the random module

1 files changed, 4 insertions, 162 deletions

diff --git a/Lib/random.py b/Lib/random.py
index d8d2c1e..5e57203 100644
--- a/Lib/random.py
+++ b/Lib/random.py
@@ -30,9 +30,6 @@ General notes on the underlying Mersenne Twister core generator:
 
 * The period is 2**19937-1.
 * It is one of the most extensively tested generators in existence.
-* Without a direct way to compute N steps forward, the semantics of
-  jumpahead(n) are weakened to simply jump to another distant state and rely
-  on the large period to avoid overlapping sequences.
 * The random() method is implemented in C, executes in a single Python step,
   and is, therefore, threadsafe.
 
@@ -49,7 +46,7 @@ __all__ = ["Random","seed","random","uniform","randint","choice","sample",
            "randrange","shuffle","normalvariate","lognormvariate",
            "expovariate","vonmisesvariate","gammavariate",
            "gauss","betavariate","paretovariate","weibullvariate",
-           "getstate","setstate","jumpahead", "WichmannHill", "getrandbits",
+           "getstate","setstate", "getrandbits",
            "SystemRandom"]
 
 NV_MAGICCONST = 4 * _exp(-0.5)/_sqrt(2.0)
@@ -70,14 +67,11 @@ class Random(_random.Random):
     """Random number generator base class used by bound module functions.
 
     Used to instantiate instances of Random to get generators that don't
-    share state.  Especially useful for multi-threaded programs, creating
-    a different instance of Random for each thread, and using the jumpahead()
-    method to ensure that the generated sequences seen by each thread don't
-    overlap.
+    share state.
 
     Class Random can also be subclassed if you want to use a different basic
     generator of your own devising: in that case, override the following
-    methods:  random(), seed(), getstate(), setstate() and jumpahead().
+    methods:  random(), seed(), getstate(), and setstate().
     Optionally, implement a getrandombits() method so that randrange()
     can cover arbitrarily large ranges.
 
@@ -615,156 +609,6 @@ class Random(_random.Random):
         u = 1.0 - self.random()
         return alpha * pow(-_log(u), 1.0/beta)
 
-## -------------------- Wichmann-Hill -------------------
-
-class WichmannHill(Random):
-
-    VERSION = 1     # used by getstate/setstate
-
-    def seed(self, a=None):
-        """Initialize internal state from hashable object.
-
-        None or no argument seeds from current time or from an operating
-        system specific randomness source if available.
-
-        If a is not None or an int or long, hash(a) is used instead.
-
-        If a is an int or long, a is used directly.  Distinct values between
-        0 and 27814431486575L inclusive are guaranteed to yield distinct
-        internal states (this guarantee is specific to the default
-        Wichmann-Hill generator).
-        """
-
-        if a is None:
-            try:
-                a = int(_hexlify(_urandom(16)), 16)
-            except NotImplementedError:
-                import time
-                a = int(time.time() * 256) # use fractional seconds
-
-        if not isinstance(a, int):
-            a = hash(a)
-
-        a, x = divmod(a, 30268)
-        a, y = divmod(a, 30306)
-        a, z = divmod(a, 30322)
-        self._seed = int(x)+1, int(y)+1, int(z)+1
-
-        self.gauss_next = None
-
-    def random(self):
-        """Get the next random number in the range [0.0, 1.0)."""
-
-        # Wichman-Hill random number generator.
-        #
-        # Wichmann, B. A. & Hill, I. D. (1982)
-        # Algorithm AS 183:
-        # An efficient and portable pseudo-random number generator
-        # Applied Statistics 31 (1982) 188-190
-        #
-        # see also:
-        #        Correction to Algorithm AS 183
-        #        Applied Statistics 33 (1984) 123
-        #
-        #        McLeod, A. I. (1985)
-        #        A remark on Algorithm AS 183
-        #        Applied Statistics 34 (1985),198-200
-
-        # This part is thread-unsafe:
-        # BEGIN CRITICAL SECTION
-        x, y, z = self._seed
-        x = (171 * x) % 30269
-        y = (172 * y) % 30307
-        z = (170 * z) % 30323
-        self._seed = x, y, z
-        # END CRITICAL SECTION
-
-        # Note:  on a platform using IEEE-754 double arithmetic, this can
-        # never return 0.0 (asserted by Tim; proof too long for a comment).
-        return (x/30269.0 + y/30307.0 + z/30323.0) % 1.0
-
-    def getstate(self):
-        """Return internal state; can be passed to setstate() later."""
-        return self.VERSION, self._seed, self.gauss_next
-
-    def setstate(self, state):
-        """Restore internal state from object returned by getstate()."""
-        version = state[0]
-        if version == 1:
-            version, self._seed, self.gauss_next = state
-        else:
-            raise ValueError("state with version %s passed to "
-                             "Random.setstate() of version %s" %
-                             (version, self.VERSION))
-
-    def jumpahead(self, n):
-        """Act as if n calls to random() were made, but quickly.
-
-        n is an int, greater than or equal to 0.
-
-        Example use:  If you have 2 threads and know that each will
-        consume no more than a million random numbers, create two Random
-        objects r1 and r2, then do
-            r2.setstate(r1.getstate())
-            r2.jumpahead(1000000)
-        Then r1 and r2 will use guaranteed-disjoint segments of the full
-        period.
-        """
-
-        if not n >= 0:
-            raise ValueError("n must be >= 0")
-        x, y, z = self._seed
-        x = int(x * pow(171, n, 30269)) % 30269
-        y = int(y * pow(172, n, 30307)) % 30307
-        z = int(z * pow(170, n, 30323)) % 30323
-        self._seed = x, y, z
-
-    def __whseed(self, x=0, y=0, z=0):
-        """Set the Wichmann-Hill seed from (x, y, z).
-
-        These must be integers in the range [0, 256).
-        """
-
-        if not type(x) == type(y) == type(z) == int:
-            raise TypeError('seeds must be integers')
-        if not (0 <= x < 256 and 0 <= y < 256 and 0 <= z < 256):
-            raise ValueError('seeds must be in range(0, 256)')
-        if 0 == x == y == z:
-            # Initialize from current time
-            import time
-            t = int(time.time() * 256)
-            t = int((t&0xffffff) ^ (t>>24))
-            t, x = divmod(t, 256)
-            t, y = divmod(t, 256)
-            t, z = divmod(t, 256)
-        # Zero is a poor seed, so substitute 1
-        self._seed = (x or 1, y or 1, z or 1)
-
-        self.gauss_next = None
-
-    def whseed(self, a=None):
-        """Seed from hashable object's hash code.
-
-        None or no argument seeds from current time.  It is not guaranteed
-        that objects with distinct hash codes lead to distinct internal
-        states.
-
-        This is obsolete, provided for compatibility with the seed routine
-        used prior to Python 2.1.  Use the .seed() method instead.
-        """
-
-        if a is None:
-            self.__whseed()
-            return
-        a = hash(a)
-        a, x = divmod(a, 256)
-        a, y = divmod(a, 256)
-        a, z = divmod(a, 256)
-        x = (x + a) % 256 or 1
-        y = (y + a) % 256 or 1
-        z = (z + a) % 256 or 1
-        self.__whseed(x, y, z)
-
 ## --------------- Operating System Random Source  ------------------
 
 class SystemRandom(Random):
@@ -789,10 +633,9 @@ class SystemRandom(Random):
         x = int(_hexlify(_urandom(bytes)), 16)
         return x >> (bytes * 8 - k)             # trim excess bits
 
-    def _stub(self, *args, **kwds):
+    def seed(self, *args, **kwds):
         "Stub method.  Not used for a system random number generator."
         return None
-    seed = jumpahead = _stub
 
     def _notimplemented(self, *args, **kwds):
         "Method should not be called for a system random number generator."
@@ -866,7 +709,6 @@ paretovariate = _inst.paretovariate
 weibullvariate = _inst.weibullvariate
 getstate = _inst.getstate
 setstate = _inst.setstate
-jumpahead = _inst.jumpahead
 getrandbits = _inst.getrandbits
 
 if __name__ == '__main__':