Introduction
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What are we doing here?
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Sampyl provides `Markov Chain Monte Carlo `_ (MCMC) samplers for drawing from probability distributions. Typically, this is used to sample from the posterior distribution of a Bayesian model. Other MCMC packages such as `PyMC `_ and `PyStan `_, while great and you should check them out, require you to create models using non-Pythonic syntax and semantics. Sampyl allows you to create models completely with Python and Numpy. All that is required is a function that calculates :math:`\log{P(X)}` for the sampling distribution. You can create this function however you want.
Installation
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You can install Sampyl from PyPI with ::
pip install sampyl-mcmc
Sampyl depends on Numpy, Scipy, and `autograd`_. You'll also need matplotlib for the examples notebooks.
.. _autograd: https://github.com/HIPS/autograd/