Metadata-Version: 1.1
Name: mosfit
Version: 0.5.9
Summary: Modular software for fitting semi-analytical model predictions to observed astronomical transient data.
Home-page: https://github.com/guillochon/mosfit
Author: James Guillochon & Matt Nicholl
Author-email: guillochon@gmail.com
License: MIT
Download-URL: https://github.com/guillochon/mosfit/tarball/0.5.9
Description: ``MOSFiT`` (**M**\ odular **O**\ pen-\ **S**\ ource **Fi**\ tter for
        **T**\ ransients) is a Python 2.7/3.x package that performs maximum
        likelihood analysis to fit semi-analytical model predictions to observed
        transient data. Data can be provided by the user, or can be pulled
        automatically from the `Open Supernova Catalog <https://sne.space>`__ by
        its name, and thus the code can be used to fit *any* supernova within
        that database, or any database that shares the format described in the
        `OSC
        schema <https://github.com/astrocatalogs/supernovae/blob/master/SCHEMA.md>`__
        (such as the `Open TDE Catalog <https://tde.space>`__ or the `Open Nova
        Catalog <https://opennova.space>`__). With the use of an optional upload
        flag, fits performed by users can then be uploaded back to the
        aforementioned catalogs.
        
        Installation
        ------------
        
        ``MOSFiT`` is available on pip, and can be installed in the standard
        way:
        
        .. code:: bash
        
            pip install mosfit
        
        To assist in the development of ``MOSFiT``, the repository should be
        cloned from GitHub and then installed into your Python environment via
        the ``setup.py`` file:
        
        .. code:: bash
        
            git clone https://github.com/guillochon/MOSFiT.git
            cd MOSFiT
            python setup.py install
        
        Using MOSFiT
        ------------
        
        For detailed instructions on using MOSFiT, please see our documentation
        on RTD: http://mosfit.readthedocs.io/
        
Keywords: astronomy,fitting,monte carlo,modeling
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Physics
