Metadata-Version: 1.1
Name: lidar_processing
Version: 0.3.0
Summary: Routines for atmospheric lidar processing.
Home-page: https://gitlab.com/ioannis_binietoglou/lidar-processing
Author: Ioannis Binietoglou
Author-email: ioannis@inoe.ro
License: MIT
Description: .. image:: https://readthedocs.org/projects/lidar-processing/badge/?version=latest
           :target: http://lidar-processing.readthedocs.io/en/latest/?badge=latest
           :alt: Documentation Status
        
        ..
           .. image:: https://codeship.com/projects/2e21b760-6eaf-0134-9495-3e75f4fffff1/status?branch=default
              :target: https://codeship.com/projects/177870
              :alt: Build Status
        
        Description
        ===========
        
        This module collects basic processing routines for aerosol lidar systems.
        
        The module should include only the pre-processing and optical processing functions. Reading data, visualization, etc.
        should be handled by different modules.
        
        
        
        Installation
        ------------
        
        The module is tested for Python 2.7.* and slightly for Python 3.6
        
        The suggested method to install is to clone the repository and install it using the -e command.
        
        .. sourcecode:: console
        
           pip install -e ./lidar_processing
        
        assuming that the module is cloned in the lidar_processing directory.
        
        The installation procedure is not yet fully automatic. You may need to install numpy, scipy manually. Probably
        the best way to install numpy and scipy is through a distribution like `anaconda <https://www.continuum.io/downloads>`_.
        
        
        Documentation
        -------------
        
        Each function should be documented following the Numpy doc style.
        
        For details see the `numpy documentation <https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt>`_.
        
        
        All docstrings are collected to a single documentation file using the `Sphinx <http://www.sphinx-doc.org/>`_ module.
        The documentation is located in the docs/ folder. The documentation is written in
        `restructured text <http://www.sphinx-doc.org/en/stable/rest.html>`_ format.
        
        You can rebuild the docs by running the following command from the docs folder.
        
        .. sourcecode:: console
        
           make html
        
        The documentation is also built automatically every time you push your changes to the repository. You can find it online
        in `Read the docs <https://readthedocs.org/projects/lidar-processing/>`_.
        
        
        Testing
        -------
        Some tests, based on unittest2 library, are located in the lidar_processing/tests/ folder.
        
        You can run all the test using the commands from the project directory.
        
        .. sourcecode:: console
        
           python -m unittest discover
        
        
        Notebooks and data
        ------------------
        The project includes some test data in the /data/ folder. It also includes some ipython notebooks with some
        example processing of the data. You can run the notebook with the command:
        
        .. sourcecode:: console
        
           jupyter notebook
        
        
        Sponsors
        --------
        The development of this module is supported by `Raymetrics S.A. <https://www.raymetrics.com/>`_.
        
        .. image:: logos/raymetrics_logo.png
           :target: https://www.raymetrics.com/
           :alt: Raymetrics logo
        
        
        
Keywords: lidar aerosol processing
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
