RadFil: A Python Package for Building and Fitting Radial Profiles for Interstellar Filaments

RadFil: A Python Package for Building and Fitting Radial Profiles for Interstellar Filaments
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DOI:
10.3847/1538-4357/aad3b5
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发表时间:
2018-07
期刊:
The Astrophysical Journal
影响因子:
--
通讯作者:
C. Zucker;H. Chen
C. Zucker;H. Chen
中科院分区:
其他
文献类型:
--
作者:
C. Zucker;H. Chen

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我们推出了 RadFil,这是一个公开可用的 Python 包,让用户可以完全控制如何构建和拟合星际细丝的径向轮廓。 RadFil 通过在灯丝的脊柱上进行径向切割来构建灯丝轮廓,从而在整个长度上保留灯丝的径向结构。预先存在的脊柱可以直接输入 RadFil,或者可以使用 FilFinder 包作为 RadFil 工作流程的一部分进行计算。除了背景减法估计器之外,我们还提供 Gaussian 和 Plummer 内置拟合函数,可以拟合整个径向切口整体或灯丝的平均径向轮廓。用户可以调整径向切割采样间隔、背景扣除估计半径和高斯/普卢默拟合半径等参数。因此,RadFil 可以处理最终的灯丝特性如何依赖于构建和安装过程中的系统学。我们逐步了解典型的 RadFil 工作流程,并将我们的结果与使用相同数据获得的独立径向剖面代码的结果进行比较;我们发现我们的结果是完全一致的。 RadFil 是开源的,可在 GitHub 上获取。我们还以 Jupyter Notebook 的形式提供了代码的完整工作教程,用户可以自行下载和运行。
We present RadFil, a publicly available Python package that gives users full control over how to build and fit radial profiles for interstellar filaments. RadFil builds filament profiles by taking radial cuts across the spine of a filament, thereby preserving the radial structure of the filament across its entire length. Pre-existing spines can be inputted directly into RadFil, or can be computed using the FilFinder package as part of the RadFil workflow. We provide Gaussian and Plummer built-in fitting functions, in addition to a background subtraction estimator, which can be fit to the entire ensemble of radial cuts or an average radial profile for the filament. Users can tweak parameters like the radial cut sampling interval, the background subtraction estimation radii, and the Gaussian/Plummer fitting radii. As a result, RadFil can provide treatment of how the resulting filament properties rely on systematics in the building and fitting process. We walk through the typical RadFil workflow and compare our results to those from an independent radial profile code obtained using the same data; we find that our results are entirely consistent. RadFil is open source and available on GitHub. We also provide a complete working tutorial of the code available as a Jupyter notebook, which users can download and run themselves.