TurbuStat: Turbulence Statistics in Python
TurbuStat: Turbulence Statistics in Python
复制标题
TurbuStat：Python 中的湍流统计
作者：
E. Koch;E. Rosolowsky;R. D. Boyden;B. Burkhart;A. Ginsburg;Jason L. Loeppky;S. Offner
我们提出TurbuStat（v1.0）：一个python软件包，用于计算谱线数据立方体中的湍流统计。TurbuStat包括14种从观测数据中恢复湍流特性的方法。该软件的其他功能包括：用于比较两个数据集的距离度量;用于拟合具有断点的线的分段线性模型;二维椭圆幂律模型;多核快速傅里叶变换支持;用于生成分数布朗运动场的模拟观测的套件，包括二维图像和光学薄H i数据立方体;以及用于创建用于合成观测的真实世界坐标系信息的功能。本文总结了TurbuStat软件包，并提供了使用几种不同方法的代表性示例。TurbuStat是一个开源软件包，我们欢迎社区的反馈和贡献。
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.
影响因子：
6.5
作者：
Arshakian;Ossenkopf
通讯作者：
Ossenkopf