TurbuStat: Turbulence Statistics in Python
作者： Eric W. Koch , Erik W. Rosolowsky , Ryan D. Boyden , Blakesley Burkhart , Adam Ginsburg
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摘要: We present TurbuStat (v1.0): a Python package for computing turbulence statistics in spectral-line data cubes. includes implementations of fourteen methods recovering turbulent properties from observational data. Additional features the software include: distance metrics comparing two sets; segmented linear model fitting lines with break-point; two-dimensional elliptical power-law model; multi-core fast-fourier-transform support; suite producing simulated observations fractional Brownian Motion fields, including images and optically-thin HI cubes; functions creating realistic world coordinate system information synthetic observations. This paper summarizes provides representative examples using several different methods. is an open-source we welcome community feedback contributions.
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