Sarracen documentation
Sarracen is a Python library for analysis and visualization of smoothed article hydrodynamics (SPH) data.
Our goal is to leverage the rich data science toolkits available in Python for the analysis of SPH data. Sarracen is built upon the pandas and Matplotlib data and visualization libraries. SPH data can be loaded into a pandas DataFrame structure that has been extended to support SPH. Sarracen should be familiar to you if you have previous experience with Matplotlib, NumPy or pandas. Our primary intended application is for astrophysical SPH simulations.
Visualizations of the data use the SPH kernel, and a variety of rendering options are available. All SPH interpolation functions are optimized into machine code using Numba with both multi-threaded and CUDA enabled routines. Our aim is to provide common analyses tasks as part of Sarracen, for example, calculating surface density profiles. This aids in correctness, performance and reproducibility.
Visit the quick start guide to learn the basics of Sarracen. For details on specific functions, consult the API reference. The codebase can be found on GitHub.