[ascl:2001.004]
FragMent: Fragmentation techniques for studying filaments
FragMent studies fragmentation in filaments by collating a number of different techniques, including nearest neighbour separations, minimum spanning tree, two-point correlation function, and Fourier power spectrum. It also performs model selection using a frequentist and Bayesian approach to find the best descriptor of a filament's fragmentation. While the code was designed to investigate filament fragmentation, the functions are general and may be used for any set of 2D points to study more general cases of fragmentation.
- Code site:
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https://github.com/SeamusClarke/FragMent
- Described in:
-
https://ui.adsabs.harvard.edu/abs/2019MNRAS.484.4024C
- Bibcode:
- 2020ascl.soft01004C