有没有Python中可用的Mersenne Twister和其他好的随机数生成器的开源实现?我想在教授数学和计算机科学专业时使用。我还在寻找相应的理论支持。
编辑: Mersenne Twister的源代码在各种语言中都可以轻松获得,例如C(random.py
)或伪代码(维基百科),但我找不到Python版本的实现。
有没有Python中可用的Mersenne Twister和其他好的随机数生成器的开源实现?我想在教授数学和计算机科学专业时使用。我还在寻找相应的理论支持。
编辑: Mersenne Twister的源代码在各种语言中都可以轻松获得,例如C(random.py
)或伪代码(维基百科),但我找不到Python版本的实现。
Mersenne Twister是标准Python库中使用的一种实现。您可以在Python发行版的random.py
文件中找到它。
在我的系统(Ubuntu 9.10)中,它位于/usr/lib/python2.6
,在Windows上应该位于C:\Python26\Lib
。
找到以下端口:
#!/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
## matumoto@math.keio.ac.jp
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()
虽然不太符合 Python 风格,但是可以工作