I’m happy to announce that we have officially released ArviZ Python library for Exploratory analysis of Bayesian models. We have a support for PyStan and CmdStan.
pip install arviz
ArviZ provides a general platform for multidimensional MCMC samples called
InferenceData, which is a NetCDF4 format structure build on top of the xarray dataset. In future we hope to support also Variational Inference results.
ArviZ has implemented many core visualizations for Bayesian workflow and all of these are using InferenceData as a base. The current plotting is built on top of the matplotlib and in future, we hope to support also other libraries.
We also provide general Bayesian diagnostics tools, including summary and psis-loo.
It is now the official plotting library for PyStan.
import arviz as az import pystan .... fit =... # plot trace inference_data = az.from_pystan(fit=fit) az.plot_trace(inference_data)
import arviz as az # support for glob strings paths = "./path_to_output/output[0-9].csv" inference_data = az.from_cmdstan(output=paths) az.plot_trace(inference_data)