• Example code and data for '...

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

Title:
Example code and data for 'Identifying physical structures in our Galaxy with Gaussian Mixture Models: An unsupervised machine learning technique'
Authors:
Tiwari, Maitraiyee, Tiwari, Maitraiyee, Kievit, Rens, Kabanovic, Slawa, Bonne, Lars, Falasca, F., Guevara, Cristian, Higgins, Ronan, Justen, M., Karim, Ramsey, Pabst, Cornelia, Pound, Marc W., Schneider, Nicola, Simon, R., Stutzki, Jurgen, Wolfire, Mark, Tielens, Alexander G. G. M.
Publisher Information:
2023; Astronomy; College of Computer, Mathematical & Natural Sciences; Digital Repository at the University of Maryland
Document Type:
Electronic Resource Electronic Resource
Index Terms:
machine learning, star-forming regions, interstellar medium, Python programming language, Software
URL:
http://hdl.handle.net/1903/30423
Availability:
Open access content. Open access content
Note:
en_US
Other Numbers:
UMC oai:drum.lib.umd.edu:1903/30423
1410387038
Contributing Source:
UNIV OF MARYLAND, COL PARK
From OAIster®, provided by the OCLC Cooperative.
Accession Number:
edsoai.on1410387038
Database:
OAIster

Further Information

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).