%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.nju.edu.cn/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). . 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). . 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). . 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). . 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). . 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). . 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 * Wed May 31 2023 Python_Bot - 1.1.4-1 - Package Spec generated