SIMBAD references

2019AJ....158....1K - Astron. J., 158, 1-1 (2019/July-0)

TurbuStat: turbulence statistics in Python.

KOCH E.W., ROSOLOWSKY E.W., BOYDEN R.D., BURKHART B., GINSBURG A., LOEPPKY J.L. and OFFNER S.S.R.

Abstract (from CDS):

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.

Abstract Copyright: © 2019. The American Astronomical Society. All rights reserved.

Journal keyword(s): methods: data analysis - methods: statistical - turbulence

Simbad objects: 1

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