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SF bug #812202: randint is always even

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* Added C coded getrandbits(k) method that runs in linear time.
* Call the new method from randrange() for ranges >= 2**53.
* Adds a warning for generators not defining getrandbits() whenever they
  have a call to randrange() with too large of a population.
This commit is contained in:
Raymond Hettinger 2003-10-05 09:09:15 +00:00
parent 5c68ef04b7
commit 2f726e9093
5 changed files with 196 additions and 10 deletions
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64
Lib/random.py
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@ -39,6 +39,8 @@ General notes on the underlying Mersenne Twister core generator:
"""
from warnings import warn as _warn
from types import MethodType as _MethodType, BuiltinMethodType as _BuiltinMethodType
from math import log as _log, exp as _exp, pi as _pi, e as _e
from math import sqrt as _sqrt, acos as _acos, cos as _cos, sin as _sin
from math import floor as _floor
@ -47,12 +49,14 @@ __all__ = ["Random","seed","random","uniform","randint","choice","sample",
"randrange","shuffle","normalvariate","lognormvariate",
"expovariate","vonmisesvariate","gammavariate",
"gauss","betavariate","paretovariate","weibullvariate",
"getstate","setstate","jumpahead"]
"getstate","setstate","jumpahead", "WichmannHill", "getrandbits",
"Random"]
NV_MAGICCONST = 4 * _exp(-0.5)/_sqrt(2.0)
TWOPI = 2.0*_pi
LOG4 = _log(4.0)
SG_MAGICCONST = 1.0 + _log(4.5)
BPF = 53 # Number of bits in a float
# Translated by Guido van Rossum from C source provided by
# Adrian Baddeley. Adapted by Raymond Hettinger for use with
@ -72,6 +76,8 @@ class Random(_random.Random):
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().
Optionally, implement a getrandombits() method so that randrange()
can cover arbitrarily large ranges.
"""
@ -131,12 +137,13 @@ class Random(_random.Random):
## -------------------- integer methods -------------------
def randrange(self, start, stop=None, step=1, int=int, default=None):
def randrange(self, start, stop=None, step=1, int=int, default=None,
maxwidth=1L<<BPF):
"""Choose a random item from range(start, stop[, step]).
This fixes the problem with randint() which includes the
endpoint; in Python this is usually not what you want.
Do not supply the 'int' and 'default' arguments.
Do not supply the 'int', 'default', and 'maxwidth' arguments.
"""
# This code is a bit messy to make it fast for the
@ -146,6 +153,8 @@ class Random(_random.Random):
raise ValueError, "non-integer arg 1 for randrange()"
if stop is default:
if istart > 0:
if istart >= maxwidth:
return self._randbelow(istart)
return int(self.random() * istart)
raise ValueError, "empty range for randrange()"
@ -153,36 +162,43 @@ class Random(_random.Random):
istop = int(stop)
if istop != stop:
raise ValueError, "non-integer stop for randrange()"
if step == 1 and istart < istop:
width = istop - istart
if step == 1 and width > 0:
# Note that
# int(istart + self.random()*(istop - istart))
# int(istart + self.random()*width)
# instead would be incorrect. For example, consider istart
# = -2 and istop = 0. Then the guts would be in
# -2.0 to 0.0 exclusive on both ends (ignoring that random()
# might return 0.0), and because int() truncates toward 0, the
# final result would be -1 or 0 (instead of -2 or -1).
# istart + int(self.random()*(istop - istart))
# istart + int(self.random()*width)
# would also be incorrect, for a subtler reason: the RHS
# can return a long, and then randrange() would also return
# a long, but we're supposed to return an int (for backward
# compatibility).
return int(istart + int(self.random()*(istop - istart)))
if width >= maxwidth:
return int(istart + self._randbelow(width))
return int(istart + int(self.random()*width))
if step == 1:
raise ValueError, "empty range for randrange()"
raise ValueError, "empty range for randrange() (%d,%d, %d)" % (istart, istop, width)
# Non-unit step argument supplied.
istep = int(step)
if istep != step:
raise ValueError, "non-integer step for randrange()"
if istep > 0:
n = (istop - istart + istep - 1) / istep
n = (width + istep - 1) / istep
elif istep < 0:
n = (istop - istart + istep + 1) / istep
n = (width + istep + 1) / istep
else:
raise ValueError, "zero step for randrange()"
if n <= 0:
raise ValueError, "empty range for randrange()"
if n >= maxwidth:
return istart + self._randbelow(n)
return istart + istep*int(self.random() * n)
def randint(self, a, b):
@ -191,6 +207,33 @@ class Random(_random.Random):
return self.randrange(a, b+1)
def _randbelow(self, n, _log=_log, int=int, _maxwidth=1L<<BPF,
_Method=_MethodType, _BuiltinMethod=_BuiltinMethodType):
"""Return a random int in the range [0,n)
Handles the case where n has more bits than returned
by a single call to the underlying generator.
"""
try:
getrandbits = self.getrandbits
except AttributeError:
pass
else:
# Only call self.getrandbits if the original random() builtin method
# has not been overridden or if a new getrandbits() was supplied.
# This assures that the two methods correspond.
if type(self.random) is _BuiltinMethod or type(getrandbits) is _Method:
k = int(1.00001 + _log(n-1, 2.0)) # 2**k > n-1 > 2**(k-2)
r = getrandbits(k)
while r >= n:
r = getrandbits(k)
return r
if n >= _maxwidth:
_warn("Underlying random() generator does not supply \n"
"enough bits to choose from a population range this large")
return int(self.random() * n)
## -------------------- sequence methods -------------------
def choice(self, seq):
@ -757,6 +800,7 @@ weibullvariate = _inst.weibullvariate
getstate = _inst.getstate
setstate = _inst.setstate
jumpahead = _inst.jumpahead
getrandbits = _inst.getrandbits
if __name__ == '__main__':
_test()