Metadata-Version: 2.1
Name: pbjam
Version: 0.4.0
Summary: A package for peakbagging solar-like oscillators
Home-page: https://pbjam.readthedocs.io/
Author: Martin Nielsen, Guy Davies, Oliver Hall
Author-email: m.b.nielsen.1@bham.ac.uk
License: MIT
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Science/Research
Classifier: Development Status :: 3 - Alpha
Requires-Dist: numpy (>=1.16.0)
Requires-Dist: scipy (!=1.4.0,!=1.4.1,>=0.19.0)
Requires-Dist: statsmodels (!=0.11.0,>=0.10.0)
Requires-Dist: matplotlib (>=1.5.3)
Requires-Dist: pandas (>=0.25.2)
Requires-Dist: emcee (>=3.0.0)
Requires-Dist: lightkurve (>=1.5.0)
Requires-Dist: astropy (>=3.2.1)
Requires-Dist: corner
Requires-Dist: pymc3
Requires-Dist: sklearn
Requires-Dist: nbsphinx
Requires-Dist: cpnest (>=0.9.9)
Provides-Extra: docs
Requires-Dist: nbsphinx ; extra == 'docs'


PBjam
============================

**Peakbagging made easy**

.. image:: https://img.shields.io/badge/GitHub-PBjam-green.svg
    :target: https://github.com/grd349/PBjam
.. image:: https://readthedocs.org/projects/pbjam/badge/?version=latest
    :target: https://pbjam.readthedocs.io/en/latest/?badge=latest
    :alt: Documentation Status
.. image:: http://img.shields.io/badge/license-MIT-blue.svg?style=flat
    :target: https://github.com/grd349/PBjam/blob/master/LICENSE
.. image:: https://img.shields.io/github/issues-closed/grd349/PBjam.svg
    :target: https://github.com/grd349/PBjam/issues
.. image:: https://badge.fury.io/py/pbjam.svg
    :target: https://badge.fury.io/py/pbjam
.. image:: https://travis-ci.com/grd349/PBjam.svg?branch=master
    :target: https://travis-ci.com/grd349/PBjam

PBjam is toolbox for modeling the oscillation spectra of solar-like oscillators. This involves two main parts: identifying a set of modes of interest, and accurately modeling those modes to measure their frequencies.

Currently, the mode identification is based on fitting the asymptotic relation to the l=2,0 pairs, relying on the cumulative sum of prior knowledge gained from NASA's Kepler mission to inform the fitting process.

Modeling the modes, or 'peakbagging', is done using the HMC sampler from `pymc3 <https://docs.pymc.io/>`_, which fits a Lorentzian to each of the identified modes, with much fewer priors than during he mode ID process. This allows for a more accurate model of the spectrum of frequencies, than the heavily parameterized models like the asymptotic relation.


Read the docs at `pbjam.readthedocs.io <http://pbjam.readthedocs.io/>`_.

.. inclusion_marker0


Contributing
------------
If you want to raise and issue or contribute code to PBjam, see the `guidelines on contributing <https://github.com/grd349/PBjam/blob/master/CONTRIBUTING.rst>`_.


Authors
-------
Main Contributors
^^^^^^^^^^^^^^^^^
- `Guy Davies <https://github.com/grd349>`_
- `Martin Nielsen <https://github.com/nielsenmb>`_
- `Alex Lyttle <https://github.com/alexlyttle>`_
- `Oliver Hall <https://github.com/ojhall94>`_

Chaos Engineers
^^^^^^^^^^^^^^^
- `Warrick Ball <https://github.com/warrickball>`_
- `Joel Ong <https://github.com/darthoctopus>`_
- Bill Chaplin
- `Tanda Li <https://github.com/litanda>`_
- `Rafa Garcia <https://github.com/rgarcibus>`_


