TurbuStat: Turbulence Statistics in Python

Abstract

We present T urbu S tat (v1.0): a python package for computing turbulence statistics in spectral-line data cubes. T urbu S tat 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 T urbu S tat package and provides representative examples using several different methods. T urbu S tat is an open-source package and we welcome community feedback and contributions.