Metadata-Version: 2.1
Name: ezaero
Version: 0.1.dev4
Summary: Aerodynamics in Python.
Home-page: https://github.com/partmor/ezaero
Author: Pedro Arturo Morales Maries
Author-email: part.morales@gmail.com
License: MIT
Download-URL: https://github.com/partmor/ezaero
Project-URL: Source, https://github.com/partmor/ezaero
Project-URL: Tracker, https://github.com/partmor/ezaero/issues
Keywords: aero,aerospace,engineering,aerodynamics,vlm
Platform: any
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: <3.9,>=3.7
Requires-Dist: matplotlib (>=2.0)
Requires-Dist: numpy
Provides-Extra: dev
Requires-Dist: tox ; extra == 'dev'
Provides-Extra: docs
Requires-Dist: pillow ; extra == 'docs'
Requires-Dist: sphinx ; extra == 'docs'
Requires-Dist: sphinx-gallery ; extra == 'docs'
Requires-Dist: sphinx-rtd-theme ; extra == 'docs'

.. |travisci| image:: https://img.shields.io/travis/partmor/ezaero/master.svg?style=flat-square&logo=travis
   :target: https://travis-ci.org/partmor/ezaero

.. |appveyor| image:: https://img.shields.io/appveyor/ci/partmor/ezaero/master.svg?style=flat-square&logo=appveyor
   :target: https://ci.appveyor.com/project/partmor/ezaero/branch/master

.. |license| image:: https://img.shields.io/badge/license-MIT-blue.svg?style=flat-square
   :target: https://github.com/partmor/ezaero/raw/master/LICENSE

.. |docs| image:: https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat-square
   :target: https://ezaero.readthedocs.io/en/latest/?badge=latest
   :alt: Documentation Status

.. |pypi_v| image:: https://img.shields.io/pypi/v/ezaero.svg
   :target: https://pypi.org/project/ezaero/
   :alt: Latest PyPI version

.. |pyversions| image:: https://img.shields.io/pypi/pyversions/ezaero.svg
   :target: https://pypi.org/project/ezaero/
   :alt: Python versions

.. |codecov| image:: https://img.shields.io/codecov/c/github/partmor/ezaero.svg?style=flat-square
   :target: https://codecov.io/github/partmor/ezaero?branch=master


ezaero
======

|travisci| |appveyor| |codecov| |docs| |license| |pypi_v| |pyversions| 

ezaero *(easy-aero)* is an open source Python package oriented to implement numerical
methods for Aerodynamics, such as the 3D Vortex lattice Method for lifting surfaces.

.. image:: https://github.com/partmor/ezaero/raw/master/docs/examples/cl_distribution.png
   :align: center
   :width: 200px


Documentation
-------------
|docs|

API documentation and examples can be found on https://ezaero.readthedocs.io.


Examples
--------

You can check out the examples in the `gallery`_, and export them as .py scripts or Jupyter notebooks to continue exploring!

.. _`gallery`: https://ezaero.readthedocs.io/en/latest/auto_examples/


Installation
------------

To install the package, simply use pip:

.. code-block::

    $ pip install ezaero


Requirements
------------
ezaero has the following dependencies:

* Python (>=3.7)
* NumPy
* matplotlib

ezaero is tested on Linux, Windows and OS X on Python 3.7 and 3.8.

==============  ============  ===================
Platform        Site          Status
==============  ============  ===================
Linux / OS X    Travis CI     |travisci|
Windows x64     Appveyor      |appveyor|
==============  ============  ===================


Contributing
------------

All contributions and suggestions are welcome! For more details, check out `CONTRIBUTING.rst`_.

.. _`CONTRIBUTING.rst`: https://github.com/partmor/ezaero/blob/master/CONTRIBUTING.rst


Motivation
----------

This library is a free-time project. I am using as a means to:

1) Experiment the performance of several scientific computing packages and tools applied to a computation-intensive application.
2) Dive deep into the Python Open Source community.
3) Redo *properly* (in terms of performance optimization, SW best practices, ...) a project I enjoyed a lot during my Master Thesis, back in 2014.


My thesis covered the analysis of the aeroelastic response of an UAV in a gust scenario.

My plan is to implement the following modules:

+ 3D steady VLM [Done]
+ 3D unsteady VLM
+ Wing motion equation solver (aeroelastic response)

If for some reason you run across this project, and find it useful or have suggestions,
don't be shy! feel free to contribute or `drop me a line <mailto:part.morales@gmail.com>`_.


