Metadata-Version: 2.1
Name: rapoc
Version: 1.0.5
Summary: Rosseland And Planck Opacity Converter
Home-page: https://github.com/ExObsSim/Rapoc-public
Author: Lorenzo V. Mugnai, Darius Modirrousta-Galian
Author-email: lorenzo.mugnai@uniroma1.it
License: BSD-3-Clause
Description: [![PyPI version](https://badge.fury.io/py/rapoc.svg)](https://badge.fury.io/py/rapoc)
        [![Documentation Status](https://readthedocs.org/projects/rapoc-public/badge/?version=latest)](https://rapoc-public.readthedocs.io/en/latest/?badge=latest)
        ![GitHub](https://img.shields.io/github/license/ExObsSim/Rapoc-public)
        
        # RAPOC: Rosseland And Planck Opacity Converter
        
        The `RAPOC` code is written by Lorenzo V. Mugnai and Darius Modirrousta-Galian and is the product 
        of a collaboration between Sapienza Università di Roma, Università degli Studi di Palermo and 
        INAF - Osservatorio Astronomico di Palermo. It uses molecular absorption measurements 
        (i.e. wavelength-dependent opacities) to calculate Rosseland and 
        Planck mean opacities that are commonly used in atmospheric modelling.
        
        `RAPOC` is designed to be simple, straightforward, and easily incorporated 
        into other codes. It is completely written in Python and documented with docstrings. 
        In addition, a Sphinx version of the documentation with a full user guide 
        that includes examples is available in html format.
        
        ### Reports
        `RAPOC` is under development, please report any issues or inaccuracies 
        to the developers to support the implementation.
        
        ### Cite
        If you use this code or its results, please cite `RAPOC: the Rosseland and Planck opacity converter` by Mugnai L. V. and Modirrousta-Galian D. (submitted).
        
        ## Installation
        ### Installing from Pypi
        `RAPOC` can be installed from the Pypi repository with the following script::
        
            pip install rapoc
        
        ### Installing from git
        `RAPOC` may also be cloned from the main git repository::
        
            git clone https://github.com/ExObsSim/Rapoc-public.git
        
        The next step is to move into the `RAPOC` folder::
        
            cd /your_path/Rapoc
        
        Then::
        
            pip install .
        
        To check if one has the correct setup::
        
            python -c "import rapoc"
        
        
        ## Use
        `RAPOC` is designed to be used on its own or in conjunction with other Python 
        codes. Given an ExoMol file in the TauREx.h5 format, Rosseland and Planck mean opacities can be calculated. 
        For example, in order to estimate the mean opacities at a temperature (T) of 1000 K with a pressure (P) of 
        10,000 Pa in the wavelength range of  0.3-50 micron the following script is used,
            
            from rapoc import Rosseland, Planck
        
            r_model = Rosseland(input_data='exomol_file.TauREx.h5')
            opacity = r_model.estimate(P_input=10000 * u.Pa, T_input=1000 * u.K, band=(0.3 *u.um, 50*u.um))
        
            p_model = Planck(input_data='exomol_file.TauREx.h5')
            opacity = p_model.estimate(P_input=10000 * u.Pa, T_input=1000 * u.K, band=(0.3 *u.um, 50*u.um))
        
        ### Inputs
        To run the code you need measured data. The supported file formats are:
        
        - ExoMol opacities (downloadable [here](http://exomol.com/data/data-types/opacity)) with the `TauREx.h5` format.
        
        ## Documentation
        The full documentation is available [here](https://rapoc-public.readthedocs.io/en/latest/) 
        
        Alternatively, `RAPOC` accepts user-defined documentation by using `sphinx`. To install it run
            
            pip install sphinx sphinx_rtd_theme
            
        From the `Rapoc/docs` folder running
            
            cd docs
            make html
        
        This will create a html version of the documentation in `Rapoc/doc/build/html/index.html`.
         
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: POSIX
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Unix
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries
Provides: rapoc
Requires-Python: >=3.8
Description-Content-Type: text/markdown
