We present TURBUSTAT (v1.0): a PYTHON package for computing turbulence statistics in spectral-line data cubes. TURBUSTAT includes implementations of 14 methods for recovering turbulent properties from observational data. Additional features of the software include: distance metrics for comparing two data sets; a segmented linear model for fitting lines with a break point; a two-dimensional elliptical power-law model; multicore fast-Fourier-transform support; a suite for producing simulated observations of fractional Brownian Motion fields, including two-dimensional images and optically thin H I data cubes; and functions for creating realistic world coordinate system information for synthetic observations. This paper summarizes the TURBUSTAT package and provides representative examples using several different methods. TURBUSTAT is an open-source package and we welcome community feedback and contributions.
The Astronomical Journal
- Pub Date:
- July 2019
- methods: data analysis;
- methods: statistical;
- Astrophysics - Instrumentation and Methods for Astrophysics
- Accepted in AJ. 21 pages, 8 figures