Introduction

Slycat was designed to facilitate understanding large scale numerical simulation data using visualization. Specifically, Slycat is used with multiple runs of numerical simulations, known as ensembles of simulations. Slycat consists of a web server and a companion web application. Most users access and interact with Slycat directly from their web browsers. You can read about Slycat at https://slycat.readthedocs.io/en/latest. Slycat is an open source project and is hosted on github at https://github.com/sandialabs/slycat.

This project, called SlyPI, facilitates using Slycat from Python. It can be used to manipulate Slycat processes normally performed through the web interface, for example model creation. SlyPI can be used to implement batch processing or other automation. It also exposes the algorithms used in Slycat for use in other applications, and lets you use your own algorithms with Slycat as a visualization front end.

In this docmentation, we describe SlyPI and how to use it from Python. We provide examples of model creation in Slycat as well as how you might use your own algorithms in Slycat. The documentation also includes the API calls.