ArviZ is a python package for exploratory analysis of Bayesian models. It is designed as a backend agnostic tool and supports different backends for visualisation and diagnostics. Apart from plotting ArviZ also supports functions for posterior analysis, model checking, comparison and diagnostics.
As ArviZ is mainly a visualisation library, it already has various plotting functions to analyse Bayesian Inference data. Still, it would be nice to extend its visualisation capabilities and add some more plotting functions which the community could use.
This project aims to implement dot plots, quantile dot plots, half-eye plots, ecdf plots, and, if time permits, then also calibration plots for classification into ArviZ for both the backends Matplotlib and Bokeh and also to write tests for all these plot functions.