OpenPIV
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 and Tk graphical user interfaces are in development, to ease the use for those users who don't have python skills.
Warning
The OpenPIV python version is still in its 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.
Test it without installation
Click the link - thanks to BinderHub, Jupyter and Conda you can now get it in your browser with zero installation:
Installing
Recommended: Using uv (fastest)
uv is a fast Python package installer and resolver written in Rust:
pip install uv
uv pip install openpiv
Using pip (standard)
Use PyPI: https://pypi.python.org/pypi/OpenPIV:
pip install openpiv
Or Poetry
poetry add openpiv
Note on Conda/Anaconda
⚠️ Conda packages are no longer actively maintained. The conda-forge package may be outdated.
If you previously installed OpenPIV via conda, you can migrate to pip or uv:
# Remove the conda package
conda remove openpiv
# Install with pip or uv
pip install openpiv
# or
uv pip install 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
Documentation
The OpenPIV documentation is available on the project web page at http://openpiv.readthedocs.org
Demo notebooks
- Tutorial Notebook 1
- Tutorial notebook 2
- Dynamic masking tutorial
- Multipass with Windows Deformation
- Multiple sets in one notebook
- 3D PIV
These and many additional examples are in another repository: OpenPIV-Python-Examples
Contributors
- Alex Liberzon
- Roi Gurka
- Zachary J. Taylor
- David Lasagna
- Mathias Aubert
- Pete Bachant
- Cameron Dallas
- Cecyl Curry
- Theo Käufer
- Andreas Bauer
- David Bohringer
- Erich Zimmer
- Peter Vennemann
- Lento Manickathan
- Yuri Ishizawa
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.
How to cite this work
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