[Python-3000-checkins] r59942 - in python/branches/py3k: Doc/library/random.rst Lib/random.py Lib/test/test_generators.py Lib/test/test_random.py Misc/NEWS Modules/_randommodule.c
raymond.hettinger
python-3000-checkins at python.org
Mon Jan 14 00:40:32 CET 2008
Author: raymond.hettinger
Date: Mon Jan 14 00:40:30 2008
New Revision: 59942
Modified:
python/branches/py3k/Doc/library/random.rst
python/branches/py3k/Lib/random.py
python/branches/py3k/Lib/test/test_generators.py
python/branches/py3k/Lib/test/test_random.py
python/branches/py3k/Misc/NEWS
python/branches/py3k/Modules/_randommodule.c
Log:
Remove defunct parts of the random module
Modified: python/branches/py3k/Doc/library/random.rst
==============================================================================
--- python/branches/py3k/Doc/library/random.rst (original)
+++ python/branches/py3k/Doc/library/random.rst Mon Jan 14 00:40:30 2008
@@ -28,25 +28,14 @@
The functions supplied by this module are actually bound methods of a hidden
instance of the :class:`random.Random` class. You can instantiate your own
-instances of :class:`Random` to get generators that don't share state. This is
-especially useful for multi-threaded programs, creating a different instance of
-:class:`Random` for each thread, and using the :meth:`jumpahead` method to make
-it likely that the generated sequences seen by each thread don't overlap.
+instances of :class:`Random` to get generators that don't share state.
Class :class:`Random` can also be subclassed if you want to use a different
basic generator of your own devising: in that case, override the :meth:`random`,
-:meth:`seed`, :meth:`getstate`, :meth:`setstate` and :meth:`jumpahead` methods.
+:meth:`seed`, :meth:`getstate`, and :meth:`setstate`.
Optionally, a new generator can supply a :meth:`getrandombits` method --- this
allows :meth:`randrange` to produce selections over an arbitrarily large range.
-As an example of subclassing, the :mod:`random` module provides the
-:class:`WichmannHill` class that implements an alternative generator in pure
-Python. The class provides a backward compatible way to reproduce results from
-earlier versions of Python, which used the Wichmann-Hill algorithm as the core
-generator. Note that this Wichmann-Hill generator can no longer be recommended:
-its period is too short by contemporary standards, and the sequence generated is
-known to fail some stringent randomness tests. See the references below for a
-recent variant that repairs these flaws.
Bookkeeping functions:
@@ -79,17 +68,6 @@
the time :func:`setstate` was called.
-.. function:: jumpahead(n)
-
- Change the internal state to one different from and likely far away from the
- current state. *n* is a non-negative integer which is used to scramble the
- current state vector. This is most useful in multi-threaded programs, in
- conjuction with multiple instances of the :class:`Random` class:
- :meth:`setstate` or :meth:`seed` can be used to force all instances into the
- same internal state, and then :meth:`jumpahead` can be used to force the
- instances' states far apart.
-
-
.. function:: getrandbits(k)
Returns a python integer with *k* random bits. This method is supplied with
@@ -224,24 +202,6 @@
Alternative Generators:
-.. class:: WichmannHill([seed])
-
- Class that implements the Wichmann-Hill algorithm as the core generator. Has all
- of the same methods as :class:`Random` plus the :meth:`whseed` method described
- below. Because this class is implemented in pure Python, it is not threadsafe
- and may require locks between calls. The period of the generator is
- 6,953,607,871,644 which is small enough to require care that two independent
- random sequences do not overlap.
-
-
-.. function:: whseed([x])
-
- This is obsolete, supplied for bit-level compatibility with versions of Python
- prior to 2.1. See :func:`seed` for details. :func:`whseed` does not guarantee
- that distinct integer arguments yield distinct internal states, and can yield no
- more than about 2\*\*24 distinct internal states in all.
-
-
.. class:: SystemRandom([seed])
Class that uses the :func:`os.urandom` function for generating random numbers
@@ -281,6 +241,4 @@
equidistributed uniform pseudorandom number generator", ACM Transactions on
Modeling and Computer Simulation Vol. 8, No. 1, January pp.3-30 1998.
- Wichmann, B. A. & Hill, I. D., "Algorithm AS 183: An efficient and portable
- pseudo-random number generator", Applied Statistics 31 (1982) 188-190.
Modified: python/branches/py3k/Lib/random.py
==============================================================================
--- python/branches/py3k/Lib/random.py (original)
+++ python/branches/py3k/Lib/random.py Mon Jan 14 00:40:30 2008
@@ -30,9 +30,6 @@
* 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 @@
"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 @@
"""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 @@
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 @@
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 @@
weibullvariate = _inst.weibullvariate
getstate = _inst.getstate
setstate = _inst.setstate
-jumpahead = _inst.jumpahead
getrandbits = _inst.getrandbits
if __name__ == '__main__':
Modified: python/branches/py3k/Lib/test/test_generators.py
==============================================================================
--- python/branches/py3k/Lib/test/test_generators.py (original)
+++ python/branches/py3k/Lib/test/test_generators.py Mon Jan 14 00:40:30 2008
@@ -444,7 +444,7 @@
>>> roots = sets[:]
>>> import random
->>> gen = random.WichmannHill(42)
+>>> gen = random.Random(42)
>>> while 1:
... for s in sets:
... print(" %s->%s" % (s, s.find()), end='')
@@ -458,29 +458,29 @@
... else:
... break
A->A B->B C->C D->D E->E F->F G->G H->H I->I J->J K->K L->L M->M
-merged D into G
- A->A B->B C->C D->G E->E F->F G->G H->H I->I J->J K->K L->L M->M
-merged C into F
- A->A B->B C->F D->G E->E F->F G->G H->H I->I J->J K->K L->L M->M
+merged I into A
+ A->A B->B C->C D->D E->E F->F G->G H->H I->A J->J K->K L->L M->M
+merged D into C
+ A->A B->B C->C D->C E->E F->F G->G H->H I->A J->J K->K L->L M->M
+merged K into H
+ A->A B->B C->C D->C E->E F->F G->G H->H I->A J->J K->H L->L M->M
merged L into A
- A->A B->B C->F D->G E->E F->F G->G H->H I->I J->J K->K L->A M->M
-merged H into E
- A->A B->B C->F D->G E->E F->F G->G H->E I->I J->J K->K L->A M->M
-merged B into E
- A->A B->E C->F D->G E->E F->F G->G H->E I->I J->J K->K L->A M->M
+ A->A B->B C->C D->C E->E F->F G->G H->H I->A J->J K->H L->A M->M
+merged E into A
+ A->A B->B C->C D->C E->A F->F G->G H->H I->A J->J K->H L->A M->M
+merged B into G
+ A->A B->G C->C D->C E->A F->F G->G H->H I->A J->J K->H L->A M->M
+merged A into F
+ A->F B->G C->C D->C E->F F->F G->G H->H I->F J->J K->H L->F M->M
+merged H into G
+ A->F B->G C->C D->C E->F F->F G->G H->G I->F J->J K->G L->F M->M
+merged F into J
+ A->J B->G C->C D->C E->J F->J G->G H->G I->J J->J K->G L->J M->M
+merged M into C
+ A->J B->G C->C D->C E->J F->J G->G H->G I->J J->J K->G L->J M->C
merged J into G
- A->A B->E C->F D->G E->E F->F G->G H->E I->I J->G K->K L->A M->M
-merged E into G
- A->A B->G C->F D->G E->G F->F G->G H->G I->I J->G K->K L->A M->M
-merged M into G
- A->A B->G C->F D->G E->G F->F G->G H->G I->I J->G K->K L->A M->G
-merged I into K
- A->A B->G C->F D->G E->G F->F G->G H->G I->K J->G K->K L->A M->G
-merged K into A
- A->A B->G C->F D->G E->G F->F G->G H->G I->A J->G K->A L->A M->G
-merged F into A
- A->A B->G C->A D->G E->G F->A G->G H->G I->A J->G K->A L->A M->G
-merged A into G
+ A->G B->G C->C D->C E->G F->G G->G H->G I->G J->G K->G L->G M->C
+merged C into G
A->G B->G C->G D->G E->G F->G G->G H->G I->G J->G K->G L->G M->G
"""
Modified: python/branches/py3k/Lib/test/test_random.py
==============================================================================
--- python/branches/py3k/Lib/test/test_random.py (original)
+++ python/branches/py3k/Lib/test/test_random.py Mon Jan 14 00:40:30 2008
@@ -42,21 +42,6 @@
self.assertRaises(TypeError, self.gen.seed, 1, 2)
self.assertRaises(TypeError, type(self.gen), [])
- def test_jumpahead(self):
- self.gen.seed()
- state1 = self.gen.getstate()
- self.gen.jumpahead(100)
- state2 = self.gen.getstate() # s/b distinct from state1
- self.assertNotEqual(state1, state2)
- self.gen.jumpahead(100)
- state3 = self.gen.getstate() # s/b distinct from state2
- self.assertNotEqual(state2, state3)
-
- self.assertRaises(TypeError, self.gen.jumpahead) # needs an arg
- self.assertRaises(TypeError, self.gen.jumpahead, "ick") # wrong type
- self.assertRaises(TypeError, self.gen.jumpahead, 2.3) # wrong type
- self.assertRaises(TypeError, self.gen.jumpahead, 2, 3) # too many
-
def test_sample(self):
# For the entire allowable range of 0 <= k <= N, validate that
# the sample is of the correct length and contains only unique items
@@ -157,48 +142,6 @@
f.close()
self.assertEqual(r.randrange(1000), value)
-class WichmannHill_TestBasicOps(TestBasicOps):
- gen = random.WichmannHill()
-
- def test_setstate_first_arg(self):
- self.assertRaises(ValueError, self.gen.setstate, (2, None, None))
-
- def test_strong_jumpahead(self):
- # tests that jumpahead(n) semantics correspond to n calls to random()
- N = 1000
- s = self.gen.getstate()
- self.gen.jumpahead(N)
- r1 = self.gen.random()
- # now do it the slow way
- self.gen.setstate(s)
- for i in range(N):
- self.gen.random()
- r2 = self.gen.random()
- self.assertEqual(r1, r2)
-
- def test_gauss_with_whseed(self):
- # Ensure that the seed() method initializes all the hidden state. In
- # particular, through 2.2.1 it failed to reset a piece of state used
- # by (and only by) the .gauss() method.
-
- for seed in 1, 12, 123, 1234, 12345, 123456, 654321:
- self.gen.whseed(seed)
- x1 = self.gen.random()
- y1 = self.gen.gauss(0, 1)
-
- self.gen.whseed(seed)
- x2 = self.gen.random()
- y2 = self.gen.gauss(0, 1)
-
- self.assertEqual(x1, x2)
- self.assertEqual(y1, y2)
-
- def test_bigrand(self):
- # Verify warnings are raised when randrange is too large for random()
- with test_support.catch_warning():
- warnings.filterwarnings("error", "Underlying random")
- self.assertRaises(UserWarning, self.gen.randrange, 2**60)
-
class SystemRandom_TestBasicOps(TestBasicOps):
gen = random.SystemRandom()
@@ -214,10 +157,6 @@
# Doesn't need to do anything except not fail
self.gen.seed(100)
- def test_jumpahead(self):
- # Doesn't need to do anything except not fail
- self.gen.jumpahead(100)
-
def test_gauss(self):
self.gen.gauss_next = None
self.gen.seed(100)
@@ -541,8 +480,7 @@
def test_main(verbose=None):
- testclasses = [WichmannHill_TestBasicOps,
- MersenneTwister_TestBasicOps,
+ testclasses = [MersenneTwister_TestBasicOps,
TestDistributions,
TestModule]
Modified: python/branches/py3k/Misc/NEWS
==============================================================================
--- python/branches/py3k/Misc/NEWS (original)
+++ python/branches/py3k/Misc/NEWS Mon Jan 14 00:40:30 2008
@@ -352,6 +352,9 @@
Library
-------
+- Removed defunct parts of the random module (the Wichmann-Hill generator
+ and the jumpahead() method).
+
- Patch #467924: add ZipFile.extract() and ZipFile.extractall() in the
zipfile module.
Modified: python/branches/py3k/Modules/_randommodule.c
==============================================================================
--- python/branches/py3k/Modules/_randommodule.c (original)
+++ python/branches/py3k/Modules/_randommodule.c Mon Jan 14 00:40:30 2008
@@ -369,72 +369,6 @@
return Py_None;
}
-/*
-Jumpahead should be a fast way advance the generator n-steps ahead, but
-lacking a formula for that, the next best is to use n and the existing
-state to create a new state far away from the original.
-
-The generator uses constant spaced additive feedback, so shuffling the
-state elements ought to produce a state which would not be encountered
-(in the near term) by calls to random(). Shuffling is normally
-implemented by swapping the ith element with another element ranging
-from 0 to i inclusive. That allows the element to have the possibility
-of not being moved. Since the goal is to produce a new, different
-state, the swap element is ranged from 0 to i-1 inclusive. This assures
-that each element gets moved at least once.
-
-To make sure that consecutive calls to jumpahead(n) produce different
-states (even in the rare case of involutory shuffles), i+1 is added to
-each element at position i. Successive calls are then guaranteed to
-have changing (growing) values as well as shuffled positions.
-
-Finally, the self->index value is set to N so that the generator itself
-kicks in on the next call to random(). This assures that all results
-have been through the generator and do not just reflect alterations to
-the underlying state.
-*/
-
-static PyObject *
-random_jumpahead(RandomObject *self, PyObject *n)
-{
- long i, j;
- PyObject *iobj;
- PyObject *remobj;
- unsigned long *mt, tmp;
-
- if (!PyLong_Check(n)) {
- PyErr_Format(PyExc_TypeError, "jumpahead requires an "
- "integer, not '%s'",
- Py_TYPE(n)->tp_name);
- return NULL;
- }
-
- mt = self->state;
- for (i = N-1; i > 1; i--) {
- iobj = PyLong_FromLong(i);
- if (iobj == NULL)
- return NULL;
- remobj = PyNumber_Remainder(n, iobj);
- Py_DECREF(iobj);
- if (remobj == NULL)
- return NULL;
- j = PyLong_AsLong(remobj);
- Py_DECREF(remobj);
- if (j == -1L && PyErr_Occurred())
- return NULL;
- tmp = mt[i];
- mt[i] = mt[j];
- mt[j] = tmp;
- }
-
- for (i = 0; i < N; i++)
- mt[i] += i+1;
-
- self->index = N;
- Py_INCREF(Py_None);
- return Py_None;
-}
-
static PyObject *
random_getrandbits(RandomObject *self, PyObject *args)
{
@@ -506,9 +440,6 @@
PyDoc_STR("getstate() -> tuple containing the current state.")},
{"setstate", (PyCFunction)random_setstate, METH_O,
PyDoc_STR("setstate(state) -> None. Restores generator state.")},
- {"jumpahead", (PyCFunction)random_jumpahead, METH_O,
- PyDoc_STR("jumpahead(int) -> None. Create new state from "
- "existing state and integer.")},
{"getrandbits", (PyCFunction)random_getrandbits, METH_VARARGS,
PyDoc_STR("getrandbits(k) -> x. Generates a long int with "
"k random bits.")},
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