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Data-driven, hierarchical models of Milky Way stars

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Starlight

Data-driven, hierarchical models of Milky Way stars Fluxes, colors, parallaxes, and population/hierarchical parameters

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Tests: pytest for unit tests, PEP8 for code style, coveralls for test coverage.

Content

./paper/: journal paper describing the method
./starlight/: main code (Python/Cython)
./tests/: test suite for the main code
./cluster_sources/: Open clusters members
./notebooks/: demo notebooks using starlight
./data/: some useful inputs for tests/demos

Requirements

Python 3.5, cython, numpy, scipy, pytest, sfdmap, astropy, coveralls, matplotlib

If you run the notebooks, you will need the 3D dust maps, as packaged in dustmaps.

Authors

Boris Leistedt (NYU)
David W. Hogg (NYU) (Flatiron)

License

Copyright 2016-2017 the authors. The code in this repository is released under the open-source MIT License. See the file LICENSE for more details.

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  • Jupyter Notebook 95.0%
  • TeX 3.4%
  • Python 1.6%