CmdStanPy

CmdStanPy is a lightweight interface to Stan for Python users which provides the necessary objects and functions to do Bayesian inference given a probability model written as a Stan program and data. Under the hood, CmdStanPy uses the CmdStan command line interface to compile and run a Stan program.

Goals

• Clean interface to Stan services so that CmdStanPy can keep up with Stan releases.

• Provides complete control - all sampler arguments have corresponding named argument for CmdStanPy sampler function.

• Easy to install,

  • minimal Python library dependencies: numpy, pandas
  • Python code doesn't interface directly with c++, only calls compiled executables

• Modular - CmdStanPy produces a sample from the posterior, downstream modules do the analysis.

Docs

See https://cmdstanpy.readthedocs.io/en/latest/index.html

Source Repository

CmdStan's source-code repository is hosted here on GitHub.

Licensing

The CmdStanPy, CmdStan, and the core Stan C++ code are licensed under new BSD.

Example

::

import os
from cmdstanpy import CmdStanModel, cmdstan_path

# specify Stan file, create, compile CmdStanModel object
bernoulli_path = os.path.join(cmdstan_path(), 'examples', 'bernoulli', 'bernoulli.stan')
bernoulli_model = CmdStanModel(stan_file=bernoulli_path)


# specify data, fit the model
bernoulli_data = { "N" : 10, "y" : [0,1,0,0,0,0,0,0,0,1] }
bernoulli_fit = bernoulli_model.sample(chains=5, cores=3, data=bernoulli_data)

# summarize the results (wraps CmdStan `bin/stansummary`):
bernoulli_fit.summary()