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        "author": "Ioannis Binietoglou",
        "author_email": "ioannis@inoe.ro",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2",
            "Topic :: Scientific/Engineering :: Atmospheric Science"
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        "description": ".. image:: https://readthedocs.org/projects/lidar-processing/badge/?version=latest\n   :target: http://lidar-processing.readthedocs.io/en/latest/?badge=latest\n   :alt: Documentation Status\n\n.. image:: https://codeship.com/projects/2e21b760-6eaf-0134-9495-3e75f4fffff1/status?branch=default\n   :target: https://codeship.com/projects/177870\n   :alt: Build Status\n\nDescription\n===========\n\nThis module collects basic processing routines for aerosol lidar systems.\n\nThe module should include only the pre-processing and optical processing functions. Reading data, visualization, etc.\nshould be handled by different modules.\n\n\n\nInstallation\n------------\n\nThe module is tested for Python 2.7.* and slightly for Python 3.6\n\nThe suggested method to install is to clone the repository and install it using the -e command.\n\n.. sourcecode:: console\n\n   pip install -e ./lidar_processing\n\nassuming that the module is cloned in the lidar_processing directory.\n\nThe installation procedure is not yet fully automatic. You may need to install numpy, scipy manually. Probably\nthe best way to install numpy and scipy is through a distribution like `anaconda <https://www.continuum.io/downloads>`_.\n\nYou will also need to install the `lidar_molecular <https://bitbucket.org/iannis_b/lidar_molecular>`_ module. You\ncan do this by\n\n.. sourcecode:: console\n\n   pip install -r requirements.txt\n\nWhen this and the *molecular* modules mature, we should optimize the installation procedure.\n\n\nDocumentation\n-------------\n\nEach function should be documented following the Numpy doc style.\n\nFor details see the `numpy documentation <https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt>`_.\n\n\nAll docstrings are collected to a single documentation file using the `Sphinx <http://www.sphinx-doc.org/>`_ module.\nThe documentation is located in the docs/ folder. The documentation is written in\n`restructured text <http://www.sphinx-doc.org/en/stable/rest.html>`_ format.\n\nYou can rebuild the docs by running the following command from the docs folder.\n\n.. sourcecode:: console\n\n   make html\n\nThe documentation is also built automatically every time you push your changes to the repository. You can find it online\nin `Read the docs <https://readthedocs.org/projects/lidar-processing/>`_.\n\n\nTesting\n-------\nSome tests, based on unittest2 library, are located in the lidar_processing/tests/ folder.\n\nYou can run all the test using the commands from the project directory.\n\n.. sourcecode:: console\n\n   python -m unittest discover\n\n\nNotebooks and data\n------------------\nThe project includes some test data in the /data/ folder. It also includes some ipython notebooks with some\nexample processing of the data. You can run the notebook with the command:\n\n.. sourcecode:: console\n\n   ipython notebook\n\n\n\n\n\n",
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        "keywords": "lidar aerosol processing",
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