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|
%global _empty_manifest_terminate_build 0
Name: python-genieclust
Version: 1.1.4
Release: 1
Summary: Genie: Fast and Robust Hierarchical Clustering with Noise Points Detection
License: GNU Affero General Public License v3
URL: https://genieclust.gagolewski.com/
Source0: https://mirrors.aliyun.com/pypi/web/packages/5e/96/d8c0cc2ea4d062c96a10802bfaea6dd85f3d598d6a9e1a538ce998f1b68f/genieclust-1.1.4.tar.gz
Requires: python3-numpy
Requires: python3-scipy
Requires: python3-cython
Requires: python3-matplotlib
Requires: python3-scikit-learn
Requires: python3-mlpack
Requires: python3-nmslib
%description
The file `src/c_scipy_rectangular_lsap.h` is adapted from the
**scipy** project (https://scipy.org/scipylib/), source:
`/scipy/optimize/rectangular_lsap/rectangular_lsap.cpp`.
Author: Peter M. Larsen. Distributed under the BSD-3-Clause license.
The implementation of internal cluster validity measures
were adapted from our previous project (Gagolewski, Bartoszuk, Cena, 2021);
see [optim_cvi](https://github.com/gagolews/optim_cvi).
Originally distributed under the GNU Affero General Public License Version 3.
## References
Gagolewski M., genieclust: Fast and robust hierarchical clustering,
*SoftwareX* **15**, 2021, 100722.
[DOI: 10.1016/j.softx.2021.100722](https://doi.org/10.1016/j.softx.2021.100722).
<https://genieclust.gagolewski.com>.
Gagolewski M., Bartoszuk M., Cena A., Genie: A new, fast, and
outlier-resistant hierarchical clustering algorithm, *Information
Sciences* **363**, 2016, 8–23.
[DOI: 10.1016/j.ins.2016.05.003](https://doi.org/10.1016/j.ins.2016.05.003).
Gagolewski M., Bartoszuk M., Cena A., Are cluster validity measures (in)valid?,
*Information Sciences* **581**, 2021, 620–636.
[DOI: 10.1016/j.ins.2021.10.004](https://doi.org/10.1016/j.ins.2021.10.004).
Gagolewski M., Cena A., Bartoszuk M., Brzozowski L.,
*Clustering with minimum spanning trees: How good can it be?*, 2023,
under review (preprint),
[DOI: 10.48550/arXiv.2303.05679](https://doi.org/10.48550/arXiv.2303.05679).
Gagolewski M., *Adjusted asymmetric accuracy: A well-behaving external
cluster validity measure*, 2022, under review (preprint),
[DOI: 10.48550/arXiv.2209.02935](https://doi.org/10.48550/arXiv.2209.02935).
Gagolewski M., A Framework for Benchmarking Clustering Algorithms,
*SoftwareX* **20**, 2022, 101270.
[DOI: 10.1016/j.softx.2022.101270](https://doi.org/10.1016/j.softx.2022.101270).
<https://clustering-benchmarks.gagolewski.com>.
Campello R.J.G.B., Moulavi D., Sander J.,
Density-based clustering based on hierarchical density estimates,
*Lecture Notes in Computer Science* **7819**, 2013, 160–172.
[DOI: 10.1007/978-3-642-37456-2_14](https://doi.org/10.1007/978-3-642-37456-2_14).
Mueller A., Nowozin S., Lampert C.H., Information Theoretic Clustering
using Minimum Spanning Trees, *DAGM-OAGM*, 2012.
Rezaei M., Fränti P., Set matching measures for external cluster validity,
*IEEE Transactions on Knowledge and Data Engineering* **28**(8), 2016,
2173–2186 [DOI: 10.1109/TKDE.2016.2551240](https://doi.org/10.1109/TKDE.2016.2551240).
See the package's [homepage](https://genieclust.gagolewski.com) for more
references.
%package -n python3-genieclust
Summary: Genie: Fast and Robust Hierarchical Clustering with Noise Points Detection
Provides: python-genieclust
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
BuildRequires: python3-cffi
BuildRequires: gcc
BuildRequires: gdb
%description -n python3-genieclust
The file `src/c_scipy_rectangular_lsap.h` is adapted from the
**scipy** project (https://scipy.org/scipylib/), source:
`/scipy/optimize/rectangular_lsap/rectangular_lsap.cpp`.
Author: Peter M. Larsen. Distributed under the BSD-3-Clause license.
The implementation of internal cluster validity measures
were adapted from our previous project (Gagolewski, Bartoszuk, Cena, 2021);
see [optim_cvi](https://github.com/gagolews/optim_cvi).
Originally distributed under the GNU Affero General Public License Version 3.
## References
Gagolewski M., genieclust: Fast and robust hierarchical clustering,
*SoftwareX* **15**, 2021, 100722.
[DOI: 10.1016/j.softx.2021.100722](https://doi.org/10.1016/j.softx.2021.100722).
<https://genieclust.gagolewski.com>.
Gagolewski M., Bartoszuk M., Cena A., Genie: A new, fast, and
outlier-resistant hierarchical clustering algorithm, *Information
Sciences* **363**, 2016, 8–23.
[DOI: 10.1016/j.ins.2016.05.003](https://doi.org/10.1016/j.ins.2016.05.003).
Gagolewski M., Bartoszuk M., Cena A., Are cluster validity measures (in)valid?,
*Information Sciences* **581**, 2021, 620–636.
[DOI: 10.1016/j.ins.2021.10.004](https://doi.org/10.1016/j.ins.2021.10.004).
Gagolewski M., Cena A., Bartoszuk M., Brzozowski L.,
*Clustering with minimum spanning trees: How good can it be?*, 2023,
under review (preprint),
[DOI: 10.48550/arXiv.2303.05679](https://doi.org/10.48550/arXiv.2303.05679).
Gagolewski M., *Adjusted asymmetric accuracy: A well-behaving external
cluster validity measure*, 2022, under review (preprint),
[DOI: 10.48550/arXiv.2209.02935](https://doi.org/10.48550/arXiv.2209.02935).
Gagolewski M., A Framework for Benchmarking Clustering Algorithms,
*SoftwareX* **20**, 2022, 101270.
[DOI: 10.1016/j.softx.2022.101270](https://doi.org/10.1016/j.softx.2022.101270).
<https://clustering-benchmarks.gagolewski.com>.
Campello R.J.G.B., Moulavi D., Sander J.,
Density-based clustering based on hierarchical density estimates,
*Lecture Notes in Computer Science* **7819**, 2013, 160–172.
[DOI: 10.1007/978-3-642-37456-2_14](https://doi.org/10.1007/978-3-642-37456-2_14).
Mueller A., Nowozin S., Lampert C.H., Information Theoretic Clustering
using Minimum Spanning Trees, *DAGM-OAGM*, 2012.
Rezaei M., Fränti P., Set matching measures for external cluster validity,
*IEEE Transactions on Knowledge and Data Engineering* **28**(8), 2016,
2173–2186 [DOI: 10.1109/TKDE.2016.2551240](https://doi.org/10.1109/TKDE.2016.2551240).
See the package's [homepage](https://genieclust.gagolewski.com) for more
references.
%package help
Summary: Development documents and examples for genieclust
Provides: python3-genieclust-doc
%description help
The file `src/c_scipy_rectangular_lsap.h` is adapted from the
**scipy** project (https://scipy.org/scipylib/), source:
`/scipy/optimize/rectangular_lsap/rectangular_lsap.cpp`.
Author: Peter M. Larsen. Distributed under the BSD-3-Clause license.
The implementation of internal cluster validity measures
were adapted from our previous project (Gagolewski, Bartoszuk, Cena, 2021);
see [optim_cvi](https://github.com/gagolews/optim_cvi).
Originally distributed under the GNU Affero General Public License Version 3.
## References
Gagolewski M., genieclust: Fast and robust hierarchical clustering,
*SoftwareX* **15**, 2021, 100722.
[DOI: 10.1016/j.softx.2021.100722](https://doi.org/10.1016/j.softx.2021.100722).
<https://genieclust.gagolewski.com>.
Gagolewski M., Bartoszuk M., Cena A., Genie: A new, fast, and
outlier-resistant hierarchical clustering algorithm, *Information
Sciences* **363**, 2016, 8–23.
[DOI: 10.1016/j.ins.2016.05.003](https://doi.org/10.1016/j.ins.2016.05.003).
Gagolewski M., Bartoszuk M., Cena A., Are cluster validity measures (in)valid?,
*Information Sciences* **581**, 2021, 620–636.
[DOI: 10.1016/j.ins.2021.10.004](https://doi.org/10.1016/j.ins.2021.10.004).
Gagolewski M., Cena A., Bartoszuk M., Brzozowski L.,
*Clustering with minimum spanning trees: How good can it be?*, 2023,
under review (preprint),
[DOI: 10.48550/arXiv.2303.05679](https://doi.org/10.48550/arXiv.2303.05679).
Gagolewski M., *Adjusted asymmetric accuracy: A well-behaving external
cluster validity measure*, 2022, under review (preprint),
[DOI: 10.48550/arXiv.2209.02935](https://doi.org/10.48550/arXiv.2209.02935).
Gagolewski M., A Framework for Benchmarking Clustering Algorithms,
*SoftwareX* **20**, 2022, 101270.
[DOI: 10.1016/j.softx.2022.101270](https://doi.org/10.1016/j.softx.2022.101270).
<https://clustering-benchmarks.gagolewski.com>.
Campello R.J.G.B., Moulavi D., Sander J.,
Density-based clustering based on hierarchical density estimates,
*Lecture Notes in Computer Science* **7819**, 2013, 160–172.
[DOI: 10.1007/978-3-642-37456-2_14](https://doi.org/10.1007/978-3-642-37456-2_14).
Mueller A., Nowozin S., Lampert C.H., Information Theoretic Clustering
using Minimum Spanning Trees, *DAGM-OAGM*, 2012.
Rezaei M., Fränti P., Set matching measures for external cluster validity,
*IEEE Transactions on Knowledge and Data Engineering* **28**(8), 2016,
2173–2186 [DOI: 10.1109/TKDE.2016.2551240](https://doi.org/10.1109/TKDE.2016.2551240).
See the package's [homepage](https://genieclust.gagolewski.com) for more
references.
%prep
%autosetup -n genieclust-1.1.4
%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-genieclust -f filelist.lst
%dir %{python3_sitearch}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri Jun 09 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.4-1
- Package Spec generated
|
