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Rare Event Sampling

This is the python implementation of Thomas Prellberg's stochastic sampling functions. The prerequisites modules of the functions are the following:

  • numpy as np
  • random
  • matplotlib.pyplot as plt
  • scipy.special as sc

The functions implemented are listed below (in order).

1-dimensional random walks

  • simple sampling
  • biased sampling
  • uniform sampling
  • perm sampling
  • blind perm sampling

2-dimensional random walks

  • simple self-avoiding walk (SAW) sampling
  • rosenbluth sampling
  • perm sampling SAW

About

The functions involved in this repository use stochastic growth methods i.e. random walks to sample rare events.

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