Is there any good open-source implementation of Mersenne Twister and other good random number generators in Python available? I would like to use in for teaching math and comp sci majors? I am also looking for the corresponding theoretical support.
Edit: Source code of Mersenne Twister is readily available in various languages such as C (random.py) or pseudocode (Wikipedia) but I could not find one in Python.
Mersenne Twister is an implementation that is used by standard python library. You can see it in random.py file in your python distribution.
On my system (Ubuntu 9.10) it is in /usr/lib/python2.6, on Windows it should be in C:\Python26\Lib
Found following port:
#!/usr/bin/python
## a C -> python translation of MT19937, original license below ##
## A C-program for MT19937: Real number version
## genrand() generates one pseudorandom real number (double)
## which is uniformly distributed on [0,1]-interval, for each
## call. sgenrand(seed) set initial values to the working area
## of 624 words. Before genrand(), sgenrand(seed) must be
## called once. (seed is any 32-bit integer except for 0).
## Integer generator is obtained by modifying two lines.
## Coded by Takuji Nishimura, considering the suggestions by
## Topher Cooper and Marc Rieffel in July-Aug. 1997.
## This library is free software; you can redistribute it and/or
## modify it under the terms of the GNU Library General Public
## License as published by the Free Software Foundation; either
## version 2 of the License, or (at your option) any later
## version.
## This library is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
## See the GNU Library General Public License for more details.
## You should have received a copy of the GNU Library General
## Public License along with this library; if not, write to the
## Free Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA
## 02111-1307 USA
## Copyright (C) 1997 Makoto Matsumoto and Takuji Nishimura.
## Any feedback is very welcome. For any question, comments,
## see http://www.math.keio.ac.jp/matumoto/emt.html or email
## [email protected]
import sys
# Period parameters
N = 624
M = 397
MATRIX_A = 0x9908b0dfL # constant vector a
UPPER_MASK = 0x80000000L # most significant w-r bits
LOWER_MASK = 0x7fffffffL # least significant r bits
# Tempering parameters
TEMPERING_MASK_B = 0x9d2c5680L
TEMPERING_MASK_C = 0xefc60000L
def TEMPERING_SHIFT_U(y):
return (y >> 11)
def TEMPERING_SHIFT_S(y):
return (y << 7)
def TEMPERING_SHIFT_T(y):
return (y << 15)
def TEMPERING_SHIFT_L(y):
return (y >> 18)
mt = [] # the array for the state vector
mti = N+1 # mti==N+1 means mt[N] is not initialized
# initializing the array with a NONZERO seed
def sgenrand(seed):
# setting initial seeds to mt[N] using
# the generator Line 25 of Table 1 in
# [KNUTH 1981, The Art of Computer Programming
# Vol. 2 (2nd Ed.), pp102]
global mt, mti
mt = []
mt.append(seed & 0xffffffffL)
for i in xrange(1, N + 1):
mt.append((69069 * mt[i-1]) & 0xffffffffL)
mti = i
# end sgenrand
def genrand():
global mt, mti
mag01 = [0x0L, MATRIX_A]
# mag01[x] = x * MATRIX_A for x=0,1
y = 0
if mti >= N: # generate N words at one time
if mti == N+1: # if sgenrand() has not been called,
sgenrand(4357) # a default initial seed is used
for kk in xrange((N-M) + 1):
y = (mt[kk]&UPPER_MASK)|(mt[kk+1]&LOWER_MASK)
mt[kk] = mt[kk+M] ^ (y >> 1) ^ mag01[y & 0x1]
for kk in xrange(kk, N):
y = (mt[kk]&UPPER_MASK)|(mt[kk+1]&LOWER_MASK)
mt[kk] = mt[kk+(M-N)] ^ (y >> 1) ^ mag01[y & 0x1]
y = (mt[N-1]&UPPER_MASK)|(mt[0]&LOWER_MASK)
mt[N-1] = mt[M-1] ^ (y >> 1) ^ mag01[y & 0x1]
mti = 0
y = mt[mti]
mti += 1
y ^= TEMPERING_SHIFT_U(y)
y ^= TEMPERING_SHIFT_S(y) & TEMPERING_MASK_B
y ^= TEMPERING_SHIFT_T(y) & TEMPERING_MASK_C
y ^= TEMPERING_SHIFT_L(y)
return ( float(y) / 0xffffffffL ) # reals
def main():
sgenrand(4357) # any nonzero integer can be used as a seed
for j in xrange(100):
sys.stdout.write('%5f ' % genrand())
if (j%8) == 7:
print
print
main()
Not very pythonic but works