### How to download the software Use <https://www.openpiv.net/downloads.html> for the shortcuts to the zipped software packages or obtain the source code from <https://github.com/openpiv> ### How to contribute 1. Open Github account 2. Visit our Git repositories through <https://github.com/OpenPIV> 3. Fork your favorite repository, Matlab, Python or C++ 4. Fix, commit, push to your repository and send us a pull request or a patch. 5. register on openpiv-develop mailing list by sending us an [e-mai](mailto:openpiv2008@gmail.com) ### What is the development plan? The big plan is: 1. move all the core algorithms for PIV and post-PIV analysis to a library, `libopenpiv` that will include Python or C/C++ code compiled through Cython. The user shall not worry about the arguments or call changes - it has to be simple and transparent. for example, the FFTW based cross-correlation from C++ https://github.com/OpenPIV/openpiv-c--qt/blob/master/src/fftcrosscorrelate.cpp to create Cython (https://docs.cython.org/src/userguide/wrapping_CPlusPlus.html) thin layer to allow their use from Python, like we already have in C: https://github.com/OpenPIV/openpiv-python/blob/master/openpiv/src/process.pyx 2. create test suite for the library - using one of the Python recommended unit test frameworks, py.test or pyunit, etc. 3. From C++ Qt-based user interface create a clone for the Python version. We started but stopped, cloning the https://github.com/OpenPIV/openpiv-c--qt/tree/master/ui into https://github.com/OpenPIV/openpiv-python/tree/master/openpiv/ui