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How to contribute

How to download the software

Use http://www.openpiv.net/downloads.html for the shortcuts to the zipped software packages or obtain the source code from http://github.com/openpiv

How to contribute

  1. Open Github account
  2. Visit our Git repositories through http://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

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 (http://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

  1. create test suite for the library - using one of the Python recommended unit test frameworks, py.test or pyunit, etc.

  2. 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