Metadata-Version: 1.1
Name: NebulaBayes
Version: 0.9.9
Summary: Compare observed emission line fluxes to predictions
Home-page: UNKNOWN
Author: Adam D. Thomas
Author-email: adam.thomas@anu.edu.au
License: MIT
Description: NebulaBayes is a package for astronomers that aims to provide a very general
        way to compare observed emission line fluxes to model predictions, in order to
        constrain physical parameters such as the nebular metallicity.
        
        NebulaBayes is provided with two photoionization model grids produced using the
        MAPPINGS 5.1 model.  One grid is a 3D HII-region grid which may be used to
        constrain the oxygen abundance (12 + log O/H), ionisation parameter (log U) and
        gas pressure (log P/k).  The other grid is for AGN narrow-line regions (NLRs)
        and has 4 dimensions, with the added parameter "log E_peak" being a measure of
        the hardness of the ionising continuum.  NebulaBayes accepts model grids in a
        simple table format, and is agnostic to the number of dimensions in the grid,
        the parameter names, and the emission line names.
        
        The ``NebulaBayes.NB_Model`` class is the entry point for performing Bayesian
        parameter estimation.  The class is initialised with a chosen model grid, at
        which point the model flux grids are loaded, interpolated, and stored.  The
        NB_Model instance may then be called one or more times to run Bayesian
        parameter estimation using observed fluxes.  Many outputs are available,
        including tables and figures, and all results and working are stored on the
        object returned when the NB_Model instance is called.
        
        | See the "docs" directory in the installed NebulaBayes package for more
          information, suggestions for getting started, and examples. (Type the
          following at the terminal to show the location of the installed package):
        | ``$ python -c "import NebulaBayes; print(NebulaBayes.__file__)"``
        
        The documentation assumes some knowledge of Bayesian statistics and scientific
        python (numpy, matplotlib and pandas).
        
        NebulaBayes is heavily based on IZI (Blanc+ 2015).
        
        If you use NebulaBayes, please cite
        `<http://adsabs.harvard.edu/abs/2018ApJ...856...89T>`_.
        
        The package has been tested on Python 2.7 and Python 3.5.
Keywords: astronomy,Bayesian statistics
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Astronomy
