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|
%global _empty_manifest_terminate_build 0
Name: python-OpenPIV
Version: 0.25.0
Release: 1
Summary: please add a summary manually as the author left a blank one
License: GNU General Public License v3 (GPLv3)
URL: https://pypi.org/project/OpenPIV/
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/6b/35/2b4e6a31fa99468800930232c2c7f9e0cb3163841dc5eccb1508c3526369/OpenPIV-0.25.0.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-imageio
Requires: python3-matplotlib
Requires: python3-scikit-image
Requires: python3-scipy
Requires: python3-natsort
Requires: python3-tqdm
Requires: python3-importlib-resources
Requires: python3-pytest
%description
# OpenPIV
[](https://travis-ci.org/OpenPIV/openpiv-python)
[](https://doi.org/10.5281/zenodo.4409178)
[](https://anaconda.org/conda-forge/openpiv)
[](https://anaconda.org/conda-forge/openpiv)
[](https://conda.anaconda.org/conda-forge)
[](https://anaconda.org/conda-forge/openpiv)
[](https://anaconda.org/conda-forge/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:
[](https://mybinder.org/v2/gh/openpiv/openpiv-python/master?filepath=openpiv%2Fexamples%2Fnotebooks%2Ftutorial1.ipynb)
## Installing
Use PyPI: <https://pypi.python.org/pypi/OpenPIV>:
pip install openpiv
## Or `conda`
conda install -c conda-forge 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
1. [Tutorial Notebook 1](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/tutorial1.ipynb)
2. [Tutorial notebook 2](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/tutorial2.ipynb)
3. [Dynamic masking tutorial](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/masking_tutorial.ipynb)
4. [Multipass with Windows Deformation](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/window_deformation_comparison.ipynb)
5. [Multiple sets in one notebook](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/all_test_cases_sample.ipynb)
6. [3D PIV](https://nbviewer.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/PIV_3D_example.ipynb)
These and many additional examples are in another repository: [OpenPIV-Python-Examples](https://github.com/OpenPIV/openpiv-python-examples)
## Contributors
1. [Alex Liberzon](http://github.com/alexlib)
2. [Roi Gurka](http://github.com/roigurka)
3. [Zachary J. Taylor](http://github.com/zjtaylor)
4. [David Lasagna](http://github.com/gasagna)
5. [Mathias Aubert](http://github.com/MathiasAubert)
6. [Pete Bachant](http://github.com/petebachant)
7. [Cameron Dallas](http://github.com/CameronDallas5000)
8. [Cecyl Curry](http://github.com/leycec)
9. [Theo Käufer](http://github.com/TKaeufer)
10. [Andreas Bauer](https://github.com/AndreasBauerGit)
11. [David Bohringer](https://github.com/davidbhr)
12. [Erich Zimmer](https://github.com/ErichZimmer)
13. [Peter Vennemann](https://github.com/eguvep)
14. [Lento Manickathan](https://github.com/lento234)
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
[](https://doi.org/10.5281/zenodo.4409178)
%package -n python3-OpenPIV
Summary: please add a summary manually as the author left a blank one
Provides: python-OpenPIV
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-OpenPIV
# OpenPIV
[](https://travis-ci.org/OpenPIV/openpiv-python)
[](https://doi.org/10.5281/zenodo.4409178)
[](https://anaconda.org/conda-forge/openpiv)
[](https://anaconda.org/conda-forge/openpiv)
[](https://conda.anaconda.org/conda-forge)
[](https://anaconda.org/conda-forge/openpiv)
[](https://anaconda.org/conda-forge/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:
[](https://mybinder.org/v2/gh/openpiv/openpiv-python/master?filepath=openpiv%2Fexamples%2Fnotebooks%2Ftutorial1.ipynb)
## Installing
Use PyPI: <https://pypi.python.org/pypi/OpenPIV>:
pip install openpiv
## Or `conda`
conda install -c conda-forge 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
1. [Tutorial Notebook 1](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/tutorial1.ipynb)
2. [Tutorial notebook 2](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/tutorial2.ipynb)
3. [Dynamic masking tutorial](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/masking_tutorial.ipynb)
4. [Multipass with Windows Deformation](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/window_deformation_comparison.ipynb)
5. [Multiple sets in one notebook](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/all_test_cases_sample.ipynb)
6. [3D PIV](https://nbviewer.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/PIV_3D_example.ipynb)
These and many additional examples are in another repository: [OpenPIV-Python-Examples](https://github.com/OpenPIV/openpiv-python-examples)
## Contributors
1. [Alex Liberzon](http://github.com/alexlib)
2. [Roi Gurka](http://github.com/roigurka)
3. [Zachary J. Taylor](http://github.com/zjtaylor)
4. [David Lasagna](http://github.com/gasagna)
5. [Mathias Aubert](http://github.com/MathiasAubert)
6. [Pete Bachant](http://github.com/petebachant)
7. [Cameron Dallas](http://github.com/CameronDallas5000)
8. [Cecyl Curry](http://github.com/leycec)
9. [Theo Käufer](http://github.com/TKaeufer)
10. [Andreas Bauer](https://github.com/AndreasBauerGit)
11. [David Bohringer](https://github.com/davidbhr)
12. [Erich Zimmer](https://github.com/ErichZimmer)
13. [Peter Vennemann](https://github.com/eguvep)
14. [Lento Manickathan](https://github.com/lento234)
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
[](https://doi.org/10.5281/zenodo.4409178)
%package help
Summary: Development documents and examples for OpenPIV
Provides: python3-OpenPIV-doc
%description help
# OpenPIV
[](https://travis-ci.org/OpenPIV/openpiv-python)
[](https://doi.org/10.5281/zenodo.4409178)
[](https://anaconda.org/conda-forge/openpiv)
[](https://anaconda.org/conda-forge/openpiv)
[](https://conda.anaconda.org/conda-forge)
[](https://anaconda.org/conda-forge/openpiv)
[](https://anaconda.org/conda-forge/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:
[](https://mybinder.org/v2/gh/openpiv/openpiv-python/master?filepath=openpiv%2Fexamples%2Fnotebooks%2Ftutorial1.ipynb)
## Installing
Use PyPI: <https://pypi.python.org/pypi/OpenPIV>:
pip install openpiv
## Or `conda`
conda install -c conda-forge 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
1. [Tutorial Notebook 1](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/tutorial1.ipynb)
2. [Tutorial notebook 2](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/tutorial2.ipynb)
3. [Dynamic masking tutorial](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/masking_tutorial.ipynb)
4. [Multipass with Windows Deformation](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/window_deformation_comparison.ipynb)
5. [Multiple sets in one notebook](https://nbviewer.jupyter.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/all_test_cases_sample.ipynb)
6. [3D PIV](https://nbviewer.org/github/OpenPIV/openpiv-python-examples/blob/main/notebooks/PIV_3D_example.ipynb)
These and many additional examples are in another repository: [OpenPIV-Python-Examples](https://github.com/OpenPIV/openpiv-python-examples)
## Contributors
1. [Alex Liberzon](http://github.com/alexlib)
2. [Roi Gurka](http://github.com/roigurka)
3. [Zachary J. Taylor](http://github.com/zjtaylor)
4. [David Lasagna](http://github.com/gasagna)
5. [Mathias Aubert](http://github.com/MathiasAubert)
6. [Pete Bachant](http://github.com/petebachant)
7. [Cameron Dallas](http://github.com/CameronDallas5000)
8. [Cecyl Curry](http://github.com/leycec)
9. [Theo Käufer](http://github.com/TKaeufer)
10. [Andreas Bauer](https://github.com/AndreasBauerGit)
11. [David Bohringer](https://github.com/davidbhr)
12. [Erich Zimmer](https://github.com/ErichZimmer)
13. [Peter Vennemann](https://github.com/eguvep)
14. [Lento Manickathan](https://github.com/lento234)
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
[](https://doi.org/10.5281/zenodo.4409178)
%prep
%autosetup -n OpenPIV-0.25.0
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-OpenPIV -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Wed Apr 12 2023 Python_Bot <Python_Bot@openeuler.org> - 0.25.0-1
- Package Spec generated
|
