Skip to main content

Python version of the Mersenne Twister 64-bit pseudorandom number generator

Project description

PyMT64 Package

                 PyMT64

PyMT64 is a Python version of the Mersenne Twister (MT) 64-bit pseudorandom number generator by Takuji Nishimura and Makoto Matsumoto (see http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt64.html and the references below).

This customised version is thread safe and was interfaced from C to Python (see pymt64.c)

This module provides the following methods:

  • init : initialization of the state vector (mt) used by the pseudorandom number generator (PNG)
  • uniform : generation of an uniform distribution
  • normal : generation of two Normal distributions
  • poisson : generation of a Poisson distribution

The period of the PNG is 2**19937-1.

Example: import time import pymt64 seed = int(time.time()) # the initial seed mt = pymt64.init(seed) # initialisation of the state vector of MT u = pymt64.uniform(mt,10) # generation of an uniform distribution print u [ 0.94295421 0.47222327 0.634552 0.26012686 0.38431784 0.23995444 0.02175826 0.8209848 0.79266556 0.8638286 ]

For a complete example, see pymt64_test.py

Note: the state vector 'mt' returned by pymt64.init has 313 elements instead of the 312 elements of the original C code. This is because the 313th element store the associated counter (mti).

Change history: 1.5 : module interface is now based on Cython, module now compatibily with python 3 1.4 : link problem fixed 1.3 : fixe a compilation problem regading the Numpy include directory 1.2 : the previous implementation of the poisson distribution was not thread safe 1.1 : fix a problem with the initialization of the seed (in the previous version the seed set by init() was not taken into account such that the results were not reproductible) 1.0 : initial version

R. Samadi (LESIA, Observatoire de Paris), 22 Dec. 2012

References: T. Nishimura, Tables of 64-bit Mersenne Twisters'' ACM Transactions on Modeling and Computer Simulation 10. (2000) 348--357. M. Matsumoto and T. Nishimura, Mersenne Twister: a 623-dimensionally equidistributed uniform pseudorandom number generator'' ACM Transactions on Modeling and Computer Simulation 8. (Jan. 1998) 3--30.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

PyMT64-1.5.tar.gz (58.8 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page