Skip to main content

Routines for atmospheric lidar processing.

Project description

Documentation 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.

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.

Documentation

Each function should be documented following the Numpy doc style.

For details see the numpy documentation.

All docstrings are collected to a single documentation file using the Sphinx module. The documentation is located in the docs/ folder. The documentation is written in restructured text format.

You can rebuild the docs by running the following command from the docs folder.

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.

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.

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:

jupyter notebook

Sponsors

The development of this module is supported by Raymetrics S.A..

Raymetrics logo

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lidar_processing-0.3.0.tar.gz (30.2 kB view hashes)

Uploaded Source

Built Distribution

lidar_processing-0.3.0-py3-none-any.whl (34.8 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page