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OpenPIV is an open source Particle Image Velocimetry analysis software written in Python and Cython
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README.md

OpenPIV

Build Status Build status DOI

Anaconda-Server Badge Anaconda-Server Badge Anaconda-Server Badge Anaconda-Server Badge Anaconda-Server Badge

OpenPIV consists in a Python and Cython modules for scripting and executing the analysis of a set of PIV image pairs. In addition, a Qt graphical user interface is in development, to ease the use for those users who don't have python skills.

Warning

The OpenPIV python version is still in beta state. This means that it still might have some bugs and the API may change. However, testing and contributing is very welcome, especially if you can contribute with new algorithms and features.

Development is currently done on a Linux/Mac OSX environment, but as soon as possible Windows will be tested. If you have access to one of these platforms please test the code.

Test it without installation

Click the link - thanks to BinderHub, Jupyter and Conda you can now get it in your browser with zero installation: Binder

Installing

Use PyPI: https://pypi.python.org/pypi/OpenPIV:

pip install cython numpy 
pip install openpiv --pre

--pre because sometimes we push pre-releases

Or conda

conda install -c conda-forge openpiv

To build from source

Download the package from the Github: https://github.com/OpenPIV/openpiv-python/archive/master.zip or clone using git

git clone https://github.com/OpenPIV/openpiv-python.git

Using distutils create a local (in the same directory) compilation of the Cython files:

python setup.py build_ext --inplace

Or for the global installation, use:

python setup.py install 

Latest developments

Latest developments go into @alexlib repository https://github.com/alexlib/openpiv-python

Documentation

The OpenPIV documentation is available on the project web page at http://openpiv.readthedocs.org

Demo notebooks

  1. Tutorial Notebook 1
  2. Tutorial notebook 2
  3. Dynamic masking tutorial
  4. Multipass tutorial with WiDiM
  5. Multipass with Windows Deformation

Contributors

  1. Alex Liberzon
  2. Roi Gurka
  3. Zachary J. Taylor
  4. David Lasagna
  5. Mathias Aubert
  6. Pete Bachant
  7. Cameron Dallas
  8. Cecyl Curry
  9. Theo Käufer

Copyright statement: smoothn.py is a Python version of smoothn.m originally created by D. Garcia [https://de.mathworks.com/matlabcentral/fileexchange/25634-smoothn], written by Prof. Lewis and available on Github [https://github.com/profLewis/geogg122/blob/master/Chapter5_Interpolation/python/smoothn.py]. We include a version of it in the openpiv folder for convenience and preservation. We are thankful to the original authors for releasing their work as an open source. OpenPIV license does not relate to this code. Please communicate with the authors regarding their license.

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