https://github.com/belson17/modred

Modred main repository
https://github.com/belson17/modred

dynamic-mode-decomposition dynamical-systems koopman model-reduction proper-orthogonal-decomposition

Last synced: 3 months ago
JSON representation

Modred main repository

• Host: GitHub
• URL: https://github.com/belson17/modred
• Owner: belson17
• License: bsd-2-clause
• Created: 2014-09-04T18:59:53.000Z (over 10 years ago)
• Default Branch: master
• Last Pushed: 2021-05-04T16:01:50.000Z (over 3 years ago)
• Last Synced: 2024-07-31T20:36:46.064Z (5 months ago)
• Topics: dynamic-mode-decomposition, dynamical-systems, koopman, model-reduction, proper-orthogonal-decomposition
• Language: Python
• Homepage:
• Size: 5.05 MB
• Stars: 76
• Watchers: 7
• Forks: 38
• Open Issues: 17
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE.txt

Awesome Lists containing this project

• awesome-fluid-dynamics - belson17/modred - An easy-to-use and parallelized library for finding modal decompositions and reduced-order models.  (Post-processing and Data Analysis / ML / Optical Flow)

README

        
Welcome to the modred library!

------------------------------

This is an easy-to-use and parallelized library for finding modal decompositions

and reduced-order models.

Parallel implementations of the proper orthogonal decomposition (POD), balanced

POD (BPOD), dynamic mode decomposition (DMD), and Petrov-Galerkin projection are

provided, as well as serial implementations of the Observer Kalman filter

Identification method (OKID) and the Eigensystem Realization Algorithm (ERA).

modred is applicable to a wide range of problems and nearly any type of data.

For smaller and simpler datasets, there is a Matlab-like interface.

For larger and more complicated datasets, you can provide modred classes with

functions to interact with your data.

This work was supported by grants from the National Science Foundation (NSF) and

the Air Force Office of Scientific Research (AFOSR).

Installation

------------

To install::

  [sudo] pip install modred

or, download the source code and run::

  [sudo] python setup.py install

To check the installation, you can run the unit tests (parallel requires

mpi4py)::

  python -c 'import modred.tests; modred.tests.run()'

  mpiexec -n 3 python -c 'import modred.tests; modred.tests.run()'

Please report failures and installation problems to

[email protected] with the following information:

1. Copy of the entire output of the tests or installation

2. Python version (``python -V``)

3. Numpy version (``python -c 'import numpy; print numpy.__version__'``)

4. Your operating system

The documentation is available at http://modred.readthedocs.io or can be

built from source by navigating to the install directory and calling::

  sphinx-build doc doc/build

Then simply open index.html in a web browser.  (Note that Sphinx 1.4 or higher

is required.)