Welcome to pgmuvi’s documentation!

pgmuvi is a package for interpreting astronomical timeseries data (although there’s no reason you can’t use it for other kinds of data!) using Gaussian processes. It is built on top of the gpytorch package, and is designed to be easy to use and flexible. It is currently under active development, and we welcome contributions!

User Guide

Installation and Quickstart

pgmuvi can be installed easily with pip:

$ pip install pgmuvi

You can also clone the latest version of pgmuvi from Github, for all the latest bugs but increased risk of features:

$ git clone git://github.com/ICSM/pgmuvi.git

and then you can install it:

$ cd pgmuvi
$ pip install .

If you want to contribute to pgmuvi and develop new features, you might want an editable install:

$ pip install -e .

this way you can test how things change as you go along.

Citing pgmuvi

pgmuvi is currently under review in the Journal of Open Source Software. If you use pgmuvi in your research, please cite the paper (details will be given here when the paper is accepted!)

API reference


We very much welcome contributions to pgmuvi! Please take a look at our github repository for more information on how to contribute!

Indices and tables