Example code and data for "Identifying physical structures in our Galaxy with Gaussian Mixture Models: An unsupervised machine learning technique"

Tiwari, MaitraiyeeKievit, RensKabanovic, SlawaBonne, LarsFalasca, F.Guevara, CristianHiggins, RonanJusten, M.Karim, RamseyPabst, CorneliaPound, Marc W.Schneider, NicolaSimon, R.Stutzki, JurgenWolfire, MarkTielens, Alexander G. G. M.See README.md.We present a python software repository implementing the PyGMMis (Melchior & Goudling 2018) method to astronomical data cubes of velocity resolved line observations. This implementation is described extensively in Tiwari et al. 2023, ApJ. An example is included in /example/ containing the SOFIA data of RCW120 used in Tiwari et al. 2023, ApJ, along with example scripts describing the full implementation of our code. The majority of parameter tweaking can be performed within 'rcw120-params.txt' which is continuously called during the procedure. A full description of the code and how to use it is in README.md (markdown file).en-USmachine learningstar-forming regionsinterstellar mediumPython programming languageExample code and data for "Identifying physical structures in our Galaxy with Gaussian Mixture Models: An unsupervised machine learning technique"Software