Python based post-processing PIV data analysis
Merging the three packages:
Use pip
:
pip install pivpy[all]
to include also lvpyio
if you work with Lavision files
pip install pivpy
if you use OpenPIV, PIVlab, etc.
git clone https://github.com/alexlib/pivpy .
cd pivpy
conda create -n pivpy python=3.11
conda activate pivpy
conda install pip
pip install -e .
lvpyio
by Lavision Inc. if you use vc7 filesnetcdf4
if you want to store NetCDF4 files by xarraypyarrow
if you want to store parquet filesvortexfitting
if you want to do vortex analysis ($\lambda_2$ and $Q$ criterions, vortex fitting) numpy
, scipy
, matplotlib
, xarray
are must and installed with the pivpy
Look into the getting started Jupyter notebook
and additional notebooks: Notebooks
From a command line just use:
pip install pytest
pytest
Read the ToDo file and pick one item to program. Use Fork-Develop-Pull Request model to contribute
Using great tutorial http://sphinx-ipynb.readthedocs.org/en/latest/howto.html we now can prepare IPython notebooks (see in /docs/source) and convert those to .rst files, then
python setup.py sphinx-build
sphinx-build -b html docs/source/ docs/build/html
generates docs/build/html
directory with the documentation