Nonlinear Schrödinger equations
Project description
PyNosh
======
|Build Status| |Coverage Status| |Code Health| |Documentation Status|
|doi|
PyNosh is a solver package for nonlinear Schrödinger equations. It
contains the respective model evaluators along with an implementation of
Newton's method and optional preconditioner for its linearization.
PyNosh uses `KryPy <https://github.com/andrenarchy/krypy>`__ for the
solution of linear equation systems and employs its deflation
capabilities. The package `VoroPy <https://github.com/nschloe/voropy>`__
is used to construct the finite-volume discrezation.
Usage
=====
Documentation
~~~~~~~~~~~~~
The documentation is hosted at
`pynosh.readthedocs.org <http://pynosh.readthedocs.org>`__.
Example
~~~~~~~
|Ginzburg-Landau solution| |Ginzburg-Landau solution|
Absolute value and complex argument of a solution of the
*Ginzburg-Landau equations*, a particular instance of nonlinear
Schrödinger equations. The number of nodes in the discretization is
72166 for this example.
Development
===========
PyNosh is currently maintained by `Nico
Schlömer <https://github.com/nschloe>`__. Feel free to contact Nico.
Please submit feature requests and bugs as GitHub issues.
PyNosh is developed with continuous integration. Current status: |Build
Status|
License
=======
PyNosh is free software licensed under the GPL3 License.
References
==========
PyNosh was used to conduct the numerical experiments in the paper
- `Preconditioned Recycling Krylov subspace methods for self-adjoint
problems, A. Gaul and N. Schlömer, arxiv: 1208.0264,
2012 <http://arxiv.org/abs/1208.0264>`__.
.. |Build Status| image:: https://travis-ci.org/nschloe/pynosh.png?branch=master
:target: https://travis-ci.org/nschloe/pynosh
.. |Coverage Status| image:: https://img.shields.io/coveralls/nschloe/pynosh.svg
:target: https://coveralls.io/r/nschloe/pynosh?branch=master
.. |Code Health| image:: https://landscape.io/github/nschloe/pynosh/master/landscape.png
:target: https://landscape.io/github/nschloe/pynosh/master
.. |Documentation Status| image:: https://readthedocs.org/projects/pynosh/badge/?version=latest
:target: https://readthedocs.org/projects/pynosh/?badge=latest
.. |doi| image:: https://zenodo.org/badge/doi/10.5281/zenodo.10341.png
:target: https://zenodo.org/record/10341
.. |Ginzburg-Landau solution| image:: figures/solution-abs.png
.. |Ginzburg-Landau solution| image:: figures/solution-arg.png
======
|Build Status| |Coverage Status| |Code Health| |Documentation Status|
|doi|
PyNosh is a solver package for nonlinear Schrödinger equations. It
contains the respective model evaluators along with an implementation of
Newton's method and optional preconditioner for its linearization.
PyNosh uses `KryPy <https://github.com/andrenarchy/krypy>`__ for the
solution of linear equation systems and employs its deflation
capabilities. The package `VoroPy <https://github.com/nschloe/voropy>`__
is used to construct the finite-volume discrezation.
Usage
=====
Documentation
~~~~~~~~~~~~~
The documentation is hosted at
`pynosh.readthedocs.org <http://pynosh.readthedocs.org>`__.
Example
~~~~~~~
|Ginzburg-Landau solution| |Ginzburg-Landau solution|
Absolute value and complex argument of a solution of the
*Ginzburg-Landau equations*, a particular instance of nonlinear
Schrödinger equations. The number of nodes in the discretization is
72166 for this example.
Development
===========
PyNosh is currently maintained by `Nico
Schlömer <https://github.com/nschloe>`__. Feel free to contact Nico.
Please submit feature requests and bugs as GitHub issues.
PyNosh is developed with continuous integration. Current status: |Build
Status|
License
=======
PyNosh is free software licensed under the GPL3 License.
References
==========
PyNosh was used to conduct the numerical experiments in the paper
- `Preconditioned Recycling Krylov subspace methods for self-adjoint
problems, A. Gaul and N. Schlömer, arxiv: 1208.0264,
2012 <http://arxiv.org/abs/1208.0264>`__.
.. |Build Status| image:: https://travis-ci.org/nschloe/pynosh.png?branch=master
:target: https://travis-ci.org/nschloe/pynosh
.. |Coverage Status| image:: https://img.shields.io/coveralls/nschloe/pynosh.svg
:target: https://coveralls.io/r/nschloe/pynosh?branch=master
.. |Code Health| image:: https://landscape.io/github/nschloe/pynosh/master/landscape.png
:target: https://landscape.io/github/nschloe/pynosh/master
.. |Documentation Status| image:: https://readthedocs.org/projects/pynosh/badge/?version=latest
:target: https://readthedocs.org/projects/pynosh/?badge=latest
.. |doi| image:: https://zenodo.org/badge/doi/10.5281/zenodo.10341.png
:target: https://zenodo.org/record/10341
.. |Ginzburg-Landau solution| image:: figures/solution-abs.png
.. |Ginzburg-Landau solution| image:: figures/solution-arg.png
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