Metadata-Version: 1.1
Name: SuperBoL
Version: 0.3.4
Summary: Supernova Bolometric Lightcurves
Home-page: https://github.com/JALusk/SuperBoL
Author: Jeremy A. Lusk
Author-email: jeremy.lusk@gmail.com
License: MIT License
Description: SuperBoL: Supernova Bolometric Lightcurves
        ==========================================
        
        Version 0.3.4
        
        SuperBoL is a python package for calculating the bolometric lightcurves of Type II
        supernovae using observed photometry. Three different methods for calculating
        the bolometric luminosity are currently included. Those are:
        
        * **Quasi-bolometric**: converts observed magnitudes to monochromatic fluxes at
          the effective wavelengths of the filters, then integrates using the
          trapezoidal rule to get an approximation of the total observed flux.
        
        * **Direct**: Calculates the quasi-bolometric lightcurve, then makes UV and IR
          corrections by fitting a blackbody curve to the fluxes, and integrating that
          function beyond the wavelength limits of the observations.
        
        * **Bolometric Correction**: Performs a bolometric correction based on B-V, V-I,
          or B-I color, using the method of Bersten & Hamuy (2009).
        
        Typical usage often looks like this::
        
            from superbol import sn
        
            my_supernova = sn.SN('sn1998a')
            my_supernova.lqbol()                # quasi-bolometric lightcurve
            my_supernova.lbol_direct_bh09()     # direct lightcurve
            my_supernova.lbol_bc_bh09('B', 'V') # B-V bolometric correction lightcurve
        
        SuperBoL propagates uncertainties in the input data through the calculations made
        by the code, allowing for errorbars to be included in plots of the lightcurve.
        
        Installation
        ============
        
        Source code can be found at https://github.com/JALusk/SuperBoL
        
        In order to install SuperBoL system-wide, use::
        
            python setup.py install
        
        If you do not have root priviliges on your machine, then use::
        
            python setup.py install --user
        
        Documentation
        =============
        
        Documentation is hosted at `ReadTheDocs <http://superbol.readthedocs.io>`_.
        
        Documentation is automatically generated via Sphinx.
        To generate the documentation locally, navigate to the ``docs/`` directory and use::
        
            make html
        
        This will generate html files in the ``docs/build/html/`` directory.
        Double-clicking the ``index.html`` file should open the documentation in your
        web browser.
        
        Development
        ===========
        
        Bug reports, feature requests, and contributions are welcome.
        
        Please issue bug reports and feature requests using https://github.com/JALusk/SuperBoL/issues - signing up for a GitHub account is free and easy.
        
        To contribute code, please use the following procedure:
        
        * Fork the SuperBoL repository on GitHub (follow the steps here:
          https://help.github.com/articles/fork-a-repo/)
        
        * Create a branch off of ``develop`` with a descriptive name::
        
            git checkout -b my_feature develop
        
        * Make your changes and additions
        
        * Write documentation for classes and functions using the Google style guide:
          http://www.sphinx-doc.org/en/stable/ext/example_google.html#example-google
        
        * Write new unit tests for your new code
        
        * Run the test suite using::
        
            make test
        
        * Issue a pull request (https://help.github.com/articles/using-pull-requests/)
          to the ``develop`` branch on GitHub
        
        * Your pull request will be reviewed and, after any conflicts are resolved,
          merged into the ``develop`` branch and eventually into the next release!
        
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Scientific/Engineering :: Astronomy
