ArviZ Dashboard

Exploratory analysis of Bayesian models with dashboards.

Project Overview

This project brings dashboards to ArviZ enabling users to compare different visualizations in the same view and interact with them.

Installation

Contributor installation

We will use mamba to create a virtual environment where we will install a development version of ArviZ Dashboard. The first step is to follow the instructions here https://github.com/conda-forge/miniforge#mambaforge to install the correct version of mamba for your operating system. Note that if you have conda installed already, you can exchange the command mamba for conda with the same results.

mamba create --name arviz-dashboard pip python
mamba activate arviz-dashboard

Once the virtual environment has been created, and you have activated it with the above commands, you can install the development requirements for arviz_dashboard with the following commands.

git clone https://github.com/arviz-devs/arviz_dashboard
cd arviz_dashboard
pip install --editable '.[dev,examples]'

Once the package has been installed, we need to install the pre-commit hooks used for maintaining code hygiene. Run the following commands to set up the required pre-commit hooks for development.

pre-commit install

When you commit your changes to your branch, pre-commit will install the tools defined in the config file, and check give feedback about required changes in order for the push to pass linting and formatting tests.

If you add a new hook to the .pre-commit-config.yaml file, run the following command in order to check if your hook is working against all the files.

pre-commit run --all-files

Contributor installation test

TBD

pytest

Usage

Dashboard usually includes multiple visualizations with different purposes. If you have any problems with certain visualizations, you can find more explanations for the ArviZ visualizations in ArviZ and Bayesian Modeling and Computation in Python

Sponsors