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=============================================================================
OpenTURNS (Open source initiative to Treat Uncertainties, Risks'N Statistics)
=============================================================================

OpenTURNS is a scientific C++ and Python library featuring an internal data model and algorithms
dedicated to the treatment of uncertainties. The main goal of this library is to provide
all functionalities needed to treat uncertainties in studies with industrial applications.
Targeted users are all engineers who want to introduce the probabilistic dimension
in their so far deterministic studies. 

Up-to-date information can be found at http://www.openturns.org

License
=======
OpenTURNS is free software distributed under the GNU Lesser General Public License version 3 or, at your option, any later version.
The terms of the GNU LGPL version 3 can be found in the files ``COPYING`` and ``COPYING.LESSER``.
Additional licenses apply to some parts of the library:
please see the ``LICENSE`` file and the other ``COPYING.*`` files.

Release Notes
=============
Please see the ``ChangeLog`` file for a summary of bug fixes and
new features of the current release.

Backwards Compatibility
=======================
The developers strive to preserve backwards compatibility
between releases, but this is not always possible. Where backwards
compatibility is known to be broken, it is clearly marked as an
incompatibility in the ``ChangeLog`` file.

Installation
============
Instructions on how to install
OpenTURNS from binaries and from sources are available `here
<http://openturns.github.io/openturns/latest/install.html>`_.

Documentation
=============
The link http://openturns.github.io/openturns/latest/contents.html will take you to
the documentation of the current release.

In the URL above, replace "latest" with "master" to view the documentation of the current master branch,
or with a version number to view the documentation of that specific version.

Contributing
============
There are many ways you can contribute,
and not all of them involve developer skills.
Please visit `this page
<http://openturns.github.io/openturns/latest/developer_guide/developer_guide.html>`_ for more information.

Acknowledgements
================

Symbolic differentiation is powered in OpenTURNS by a `modified version
<https://github.com/openturns/ev3/>`_ of Leo Liberti's `Ev3
<http://www.lix.polytechnique.fr/Labo/Leo.Liberti/Ev3.pdf>`_ library.

-- The OpenTURNS team
