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

TL;DR

RadFil is an open-source Python package that enables detailed construction and fitting of radial density profiles for interstellar filaments, allowing for customizable analysis and systematic testing of filament properties.

Contribution

It introduces a flexible, user-controlled workflow for building and fitting filament profiles, integrating existing tools and providing comprehensive tutorials.

Findings

Results are consistent with independent methods

RadFil allows systematic exploration of analysis parameters

Provides a reproducible workflow for filament profile analysis

Abstract

We present RadFil, a publicly available Python package that gives users full control over how to build and fit radial density 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 density 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.