Author(s): Paul Miles | Date: August 31, 2018
Note, the pymcmcstat tutorials have moved to a new location. To switch to the new index, please follow this link. Otherwise, selecting any of the tutorials listed below will take you to the appropriate new location.
The pymcmcstat package is a Python program for running Markov Chain Monte Carlo (MCMC) simulations. Included in this package is the abilitity to use different Metropolis based sampling techniques:
The pymcmcstat package is a Python implementation of the MATLAB toolbox mcmcstat. The user interface is designed to be as similar to the MATLAB version as possible, but this implementation has taken advantage of certain data structure concepts more amenable to Python.
Please see the pymcmcstat homepage for more details about the development of this Python package.
This code can be found on the Github project page. The package is available on the PyPI distribution site and the latest version can be installed via,
pip install pymcmcstat
The master branch on Github typically matches the latest release on the PyPI distribution site. To install the master branch directly from Github,
pip install git+https://github.com/prmiles/pymcmcstat.git
You can also clone the repository and run python setup.py install
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There are many built-in features to pymcmcstat that allow it to be tailored to suit your particular problem. Below we have outlined features through a set of examples.
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scipy.optimize.leastsq
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*.mat
file.ctypes
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These tutorials address very specific features of using the package.
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ctypes
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