Metadata-Version: 2.1
Name: trtm
Version: 0.1.2
Summary: Titan Radiative Transfer Model package
Home-page: https://github.com/seignovert/trtm
Author: Benoit Seignovert
Author-email: benoit.a.seignovert@jpl.nasa.gov
License: MIT
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
Requires-Dist: numpy

Python parser Titan Radiative Transfer model
============================================

|Build| |PyPI| |Python| |Version| |License|

.. |Build| image:: https://github.com/seignovert/trtm/workflows/Github%20Actions/badge.svg
        :target: https://github.com/seignovert/trtm/actions?query=workflow%3A%22Github+Actions%22
.. |PyPI| image:: https://img.shields.io/badge/PyPI-trtm-blue.svg?logo=python&logoColor=white
        :target: https://pypi.org/project/trtm
.. |Python| image:: https://img.shields.io/pypi/pyversions/trtm.svg?label=Python
        :target: https://pypi.org/project/trtm
.. |Version| image:: https://img.shields.io/pypi/v/trtm.svg?label=Version
        :target: https://pypi.org/project/trtm
.. |License| image:: https://img.shields.io/pypi/l/trtm.svg?label=License
        :target: https://pypi.org/project/trtm


Install
-------

From PyPI:

.. code:: bash

    pip install trtm

From the sources:

.. code:: bash

    git clone https://github.com/seignovert/trtm.git && cd trtm
    python setup.py develop


Usage
-----

.. code:: python

    >>> from trtm import TRTM

    >>> data = TRTM('1590648776_1', root='tests/data', suffix='test_SPSDISORT')

    >>> data.keys()
    [
        'setup',
        'wvlns',
        'outputs',
        'cube',
        ...
        'FH',
        ...
        'I_F',
        ...
        'albedo_corr',
        ...
    ]

    >>> data['setup']
    {
        'Numéro cube et pixel': 'C1590648776_1',
        'NKS': 4,
        ...
    }

    >>> data['NKS']
    4

    >>> out['FH'].shape
    (5, 3)

    >>> out['FH', 3, 5]
    0.900057

    >>> out['I_F'].shape
    (256, 5, 3)

    >>> out['I_F', 5.0].shape
    (5, 3)

    >>> out['I_F', 1, 1].shape
    (256, )

    >>>out['I_F', 1, 1, 5.12]
    0.04082437994

See examples in `Jupyter notebook examples <notebooks/Examples.ipynb>`_.


