Muller
sample Muller's potential
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Implements a suite of sampling algorithms to stochastically draw points from Muller's potential. Provides a framework to perform a comparative analysis of samplers for Monte Carlo integration.
Licensed under Creative Commons BY-NC-SA 3.0.
Questions or comments? Contact Joseph Schlecht.
usage: muller OPTIONS where OPTIONS is one or more of the following: -h, --help Prints program usage. -v, --version Prints program version. --seed=ARG Random seed. --iterations=ARG Number of sampling iterations. --hybrid-leap-iter=ARG Number of hybrid Monte Carlo leapfrog iterations. --start-x=ARG Starting x-coord position. --start-y=ARG Starting y-coord position. --delta-t=ARG Stochastic dynamics integration step-size for Langevin Monte Carlo. --alpha=ARG Stochastic dynamics step-size for Langevin Monte Carlo. --kick=ARG Stochastic dynamics frequency to kick the particle by resetting the momenta. Zero disables any kicking. Must be > 0. --x-sigma=ARG Gaussian sigma for MH proposal of x. Must be > 0. --x-lim=ARG Limits over the range of x. Has format min,max --y-sigma=ARG Gaussian sigma for MH proposal of y. Must be > 0. --y-lim=ARG Limits over the range of y. Has format min,max. --sampler=ARG Type of sampler to use. Must be one of {mh, lange, hyper, stoch, hybrid}. --hyper-bias=ARG Bias parameter for hyper sampling. --hyper-scale=ARG Scale parameter for hyper sampling.