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.
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.
Use PyPI: https://pypi.python.org/pypi/OpenPIV:
pip install cython numpy pip install openpiv --pre
--pre because sometimes we push pre-releases
conda install -c conda-forge openpiv
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 go into @alexlib repository https://github.com/alexlib/openpiv-python
The OpenPIV documentation is available on the project web page at http://openpiv.readthedocs.org
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.