[Python-checkins] python/nondist/sandbox/twister _random.c,NONE,1.1 test_random.py,NONE,1.1
rhettinger@users.sourceforge.net
rhettinger@users.sourceforge.net
Mon, 23 Dec 2002 21:06:16 -0800
Update of /cvsroot/python/python/nondist/sandbox/twister
In directory sc8-pr-cvs1:/tmp/cvs-serv27822
Added Files:
_random.c test_random.py
Log Message:
Renamed from MersenneTwister.c and test_twister.py.
--- NEW FILE: _random.c ---
/* Random objects */
/* ------------------------------------------------------------------
The code in this module was based on a download from:
http://www.math.keio.ac.jp/~matumoto/MT2002/emt19937ar.html
It was modified in 2002 by Raymond Hettinger as follows:
* the principal computational lines untouched except for tabbing.
* renamed genrand_res53() to random_random() and wrapped
in python calling/return code.
* genrand_int32() and the helper functions, init_genrand()
and init_by_array(), were declared static, wrapped in
Python calling/return code. also, their global data
references were replaced with structure references.
* unused functions from the original were deleted.
new, original C python code was added to implement the
Random() interface.
The following are the verbatim comments from the original code:
A C-program for MT19937, with initialization improved 2002/1/26.
Coded by Takuji Nishimura and Makoto Matsumoto.
Before using, initialize the state by using init_genrand(seed)
or init_by_array(init_key, key_length).
Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
3. The names of its contributors may not be used to endorse or promote
products derived from this software without specific prior written
permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Any feedback is very welcome.
http://www.math.keio.ac.jp/matumoto/emt.html
email: matumoto@math.keio.ac.jp
*/
/* ---------------------------------------------------------------*/
#include "Python.h"
#include <time.h> // for seeding to current time
/* Period parameters -- These are all magic. Don't change. */
#define N 624
#define M 397
#define MATRIX_A 0x9908b0dfUL /* constant vector a */
#define UPPER_MASK 0x80000000UL /* most significant w-r bits */
#define LOWER_MASK 0x7fffffffUL /* least significant r bits */
typedef struct {
PyObject_HEAD
unsigned long state[N];
int index;
} RandomObject;
static PyTypeObject Random_Type;
#define RandomObject_Check(v) ((v)->ob_type == &Random_Type)
/* Random methods */
/* generates a random number on [0,0xffffffff]-interval */
static unsigned long
genrand_int32(RandomObject *self)
{
unsigned long y;
static unsigned long mag01[2]={0x0UL, MATRIX_A};
/* mag01[x] = x * MATRIX_A for x=0,1 */
unsigned long *mt;
mt = self->state;
if (self->index >= N) { /* generate N words at one time */
int kk;
for (kk=0;kk<N-M;kk++) {
y = (mt[kk]&UPPER_MASK)|(mt[kk+1]&LOWER_MASK);
mt[kk] = mt[kk+M] ^ (y >> 1) ^ mag01[y & 0x1UL];
}
for (;kk<N-1;kk++) {
y = (mt[kk]&UPPER_MASK)|(mt[kk+1]&LOWER_MASK);
mt[kk] = mt[kk+(M-N)] ^ (y >> 1) ^ mag01[y & 0x1UL];
}
y = (mt[N-1]&UPPER_MASK)|(mt[0]&LOWER_MASK);
mt[N-1] = mt[M-1] ^ (y >> 1) ^ mag01[y & 0x1UL];
self->index = 0;
}
y = mt[self->index++];
y ^= (y >> 11);
y ^= (y << 7) & 0x9d2c5680UL;
y ^= (y << 15) & 0xefc60000UL;
y ^= (y >> 18);
return y;
}
static PyObject *
random_random(RandomObject *self)
{
unsigned long y, z;
double result;
y = genrand_int32(self);
z = genrand_int32(self);
result = ((y>>5)*67108864.0+(z>>6))*(1.0/9007199254740992.0);
return PyFloat_FromDouble(result);
}
/* initializes mt[N] with a seed */
static PyObject *
init_genrand(RandomObject *self, unsigned long s)
{
int mti;
unsigned long *mt;
assert(RandomObject_Check(self));
mt = self->state;
mt[0]= s & 0xffffffffUL;
for (mti=1; mti<N; mti++) {
mt[mti] =
(1812433253UL * (mt[mti-1] ^ (mt[mti-1] >> 30)) + mti);
/* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
/* In the previous versions, MSBs of the seed affect */
/* only MSBs of the array mt[]. */
/* 2002/01/09 modified by Makoto Matsumoto */
mt[mti] &= 0xffffffffUL;
/* for >32 bit machines */
}
self->index = mti;
Py_INCREF(Py_None);
return Py_None;
}
/* initialize by an array with array-length */
/* init_key is the array for initializing keys */
/* key_length is its length */
static PyObject *
init_by_array(RandomObject *self, unsigned long init_key[], unsigned long key_length)
{
unsigned int i, j, k; /* was signed in the original code. RDH 12/16/2002 */
unsigned long *mt;
mt = self->state;
init_genrand(self, 19650218UL);
i=1; j=0;
k = (N>key_length ? N : key_length);
for (; k; k--) {
mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1664525UL))
+ init_key[j] + j; /* non linear */
mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */
i++; j++;
if (i>=N) { mt[0] = mt[N-1]; i=1; }
if (j>=key_length) j=0;
}
for (k=N-1; k; k--) {
mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1566083941UL))
- i; /* non linear */
mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */
i++;
if (i>=N) { mt[0] = mt[N-1]; i=1; }
}
mt[0] = 0x80000000UL; /* MSB is 1; assuring non-zero initial array */
Py_INCREF(Py_None);
return Py_None;
}
static PyObject *
random_seed(RandomObject *self, PyObject *args)
{
time_t now;
unsigned long *key;
unsigned long keylength;
unsigned long seed;
unsigned int i;
PyObject *split;
PyObject *result = NULL;
PyObject *arg = NULL;
PyObject *masklower;
PyObject *thirtytwo;
PyObject *little = NULL;
PyObject *newarg;
int err;
long hash;
if (!PyArg_ParseTuple(args, "|O:seed", &arg))
return NULL;
if (arg == NULL || arg == Py_None) {
time(&now);
return init_genrand(self, (unsigned long)now);
}
split = PyList_New(0);
if (split == NULL)
return NULL;
if (PyInt_Check(arg) || PyLong_Check(arg))
arg = PyNumber_Absolute(arg);
else {
hash = PyObject_Hash(arg);
if (hash != -1)
arg = PyLong_FromUnsignedLong((unsigned long)hash);
}
if (arg == NULL) {
Py_DECREF(split);
return NULL;
}
masklower = PyLong_FromUnsignedLong(0xffffffffU);
thirtytwo = PyInt_FromLong(32L);
while (PyObject_IsTrue(arg)) {
little = PyNumber_And(arg, masklower);
if (little == NULL)
goto Done;
assert(PyLong_Check(little));
err = PyList_Append(split, little);
if (err == -1)
goto Done;
newarg = PyNumber_Rshift(arg, thirtytwo);
if (newarg == NULL)
goto Done;
Py_DECREF(arg);
arg = newarg;
}
if (PyList_Size(split) == 0)
PyList_Append(split, PyLong_FromLong(0L));
keylength = PyList_Size(split);
key = (unsigned long *) PyMem_MALLOC(keylength * sizeof(unsigned long));
if (key == NULL)
goto Done;
for (i=0; i<keylength ; i++) {
seed = PyLong_AsUnsignedLong(PyList_GET_ITEM(split, i));
if (seed == -1 && PyErr_Occurred()) {
PyMem_FREE(key);
goto Done;
}
key[i] = seed;
}
result = init_by_array(self, key, keylength);
PyMem_FREE(key);
Done:
Py_DECREF(masklower);
Py_DECREF(thirtytwo);
Py_XDECREF(little);
Py_DECREF(arg);
Py_DECREF(split);
return result;
}
static PyObject *
random_getstate(RandomObject *self)
{
PyObject *state;
PyObject *element;
int i;
state = PyTuple_New(N+1);
if (state == NULL)
return NULL;
for (i=0; i<N ; i++) {
element = PyInt_FromLong((long)(self->state[i]));
if (element == NULL)
goto Fail;
PyTuple_SET_ITEM(state, i, element);
}
element = PyInt_FromLong((long)(self->index));
if (element == NULL)
goto Fail;
PyTuple_SET_ITEM(state, i, element);
return state;
Fail:
for (i=i-1; i>=0 ; i--)
Py_DECREF(PyTuple_GET_ITEM(state, i));
Py_DECREF(state);
return NULL;
}
static PyObject *
random_setstate(RandomObject *self, PyObject *state)
{
int i;
long element;
if (!PyTuple_Check(state)) {
PyErr_SetString(PyExc_TypeError,
"state vector must be a tuple");
return NULL;
}
if (PyTuple_Size(state) != N+1) {
PyErr_SetString(PyExc_ValueError,
"state vector is the wrong size");
return NULL;
}
for (i=0; i<N ; i++) {
element = PyInt_AsLong(PyTuple_GET_ITEM(state, i));
if (element == -1 && PyErr_Occurred())
return NULL;
self->state[i] = (unsigned long)element;
}
element = PyInt_AsLong(PyTuple_GET_ITEM(state, i));
if (element == -1 && PyErr_Occurred())
return NULL;
self->index = (int)element;
Py_INCREF(Py_None);
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
implementing 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 consequetive 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;
assert(RandomObject_Check(self));
mt = self->state;
for (i=N-1 ; i>1 ; i--) {
iobj = PyInt_FromLong(i);
remobj = PyNumber_Remainder(n, iobj);
Py_DECREF(iobj);
if (remobj == NULL)
return NULL;
j = PyInt_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_new(PyTypeObject *type, PyObject *args, PyObject *kwds)
{
RandomObject *self;
self = (RandomObject *)type->tp_alloc(type, 0);
if (self == NULL)
return NULL;
if (random_seed(self, args) == NULL) {
Py_DECREF(self);
return NULL;
}
return (PyObject *)self;
}
static PyMethodDef random_methods[] = {
{"random", (PyCFunction)random_random, METH_NOARGS,
PyDoc_STR("random() -> x in the interval [0,1).")},
{"seed", (PyCFunction)random_seed, METH_VARARGS,
PyDoc_STR("seed([n]) -> None. Defaults to current time")},
{"getstate", (PyCFunction)random_getstate, METH_NOARGS,
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 a new state from\n\
the existing state and the supplied integer.")},
{NULL, NULL} /* sentinel */
};
PyDoc_STRVAR(random_doc,
"Random() -> create a random number generator with its own internal state.");
static PyTypeObject Random_Type = {
PyObject_HEAD_INIT(NULL)
0, /*ob_size*/
"_random.Random", /*tp_name*/
sizeof(RandomObject), /*tp_basicsize*/
0, /*tp_itemsize*/
/* methods */
(destructor)PyObject_Del, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
0, /*tp_compare*/
0, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
PyObject_GenericGetAttr, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /*tp_flags*/
random_doc, /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
random_methods, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
PyType_GenericAlloc, /*tp_alloc*/
random_new, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
};
PyDoc_STRVAR(module_doc,
"Module implements the Mersenne Twister random number generator .");
static PyMethodDef module_functions[] = {
{NULL, NULL} /* sentinel */
};
PyMODINIT_FUNC
init_random(void)
{
PyObject *m;
Random_Type.ob_type = &PyType_Type;
m = Py_InitModule3("_random", module_functions, module_doc);
PyModule_AddObject(m, "Random", (PyObject *)&Random_Type);
}
--- NEW FILE: test_random.py ---
#!/usr/bin/env python
import unittest
import operator
import random
import time
from test import test_support
class TestBasicOps(unittest.TestCase):
## Superclass with tests common to all generators
def randomlist(self, n):
"""Helper function to make a list of random numbers"""
return [self.gen.random() for i in xrange(n)]
def test_autoseed(self):
self.gen.seed()
state1 = self.gen.getstate()
time.sleep(1)
self.gen.seed() # diffent seeds at different times
state2 = self.gen.getstate()
self.assertNotEqual(state1, state2)
def test_saverestore(self):
N = 1000
self.gen.seed()
state = self.gen.getstate()
randseq = self.randomlist(N)
self.gen.setstate(state) # should regenerate the same sequence
self.assertEqual(randseq, self.randomlist(N))
def test_seedargs(self):
for arg in [None, 0, 0L, 1, 1L, -1, -1L, 10**20, -(10**20),
3.14, 1+2j, 'a', tuple('abc')]:
self.gen.seed(arg)
for arg in [range(3), dict(one=1)]:
self.assertRaises(TypeError, self.gen.seed, arg)
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)
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
N = 100
population = xrange(N)
for k in xrange(N+1):
s = self.gen.sample(population, k)
self.assertEqual(len(s), k)
uniq = dict.fromkeys(s)
self.assertEqual(len(uniq), k)
self.failIf(None in uniq)
class WichmannHill_TestBasicOps(TestBasicOps):
def setUp(self):
self.gen = random.WichmannHill()
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 xrange(N):
self.gen.random()
r2 = self.gen.random()
self.assertEqual(r1, r2)
class MersenneTwister_TestBasicOps(TestBasicOps):
def setUp(self):
self.gen = random.Random()
def test_referenceImplementation(self):
## Compare the python implementation with results from the original
## code. Create 2000 53-bit precision random floats. Compare only
## the last ten entries to show that the independent implementations
## are tracking. Here is the main() function needed to create the
## list of expected random numbers:
## void main(void){
## int i;
## unsigned long init[4]={61731, 24903, 614, 42143}, length=4;
## init_by_array(init, length);
## for (i=0; i<2000; i++) {
## printf("%.15f ", genrand_res53());
## if (i%5==4) printf("\n");
## }
## }
expected = [0.458398030737133, 0.860578152019788, 0.928483317267822,
0.359326811197825, 0.081823493762450, 0.143322264701693,
0.084297823823520, 0.538148646718315, 0.089215024911993,
0.784861961053729]
self.gen.seed(61731L + (24903L<<32) + (614L<<64) + (42143L<<96))
actual = self.randomlist(2000)[-10:]
for a, e in zip(actual, expected):
self.assertEqual(round(a-e, 14), 0)
class TestModule(unittest.TestCase):
def assertAlmostEqual(self, computed, expected):
"""Helper function to test constants being within a given tolerance"""
self.failIf(abs(computed - expected) > 1e-7)
def testMagicConstants(self):
self.assertAlmostEqual(random.NV_MAGICCONST, 1.71552776992141)
self.assertAlmostEqual(random.TWOPI, 6.28318530718)
self.assertAlmostEqual(random.LOG4, 1.38629436111989)
self.assertAlmostEqual(random.SG_MAGICCONST, 2.50407739677627)
def test__all__(self):
# tests validity but not completeness of the __all__ list
defined = dict.fromkeys(dir(random))
for entry in random.__all__:
self.failUnless(entry in defined)
def test_main():
suite = unittest.TestSuite()
suite.addTest(unittest.makeSuite(WichmannHill_TestBasicOps))
suite.addTest(unittest.makeSuite(MersenneTwister_TestBasicOps))
suite.addTest(unittest.makeSuite(TestModule))
test_support.run_suite(suite)
if __name__ == "__main__":
test_main()