%global _empty_manifest_terminate_build 0 Name: python-tesseract Version: 0.1.3 Release: 1 Summary: Tesselation based Recovery of Amorphous halo Concentrations License: UNKNOWN URL: http://vpac00.phy.vanderbilt.edu/~langmm/index.html Source0: https://mirrors.nju.edu.cn/pypi/web/packages/8d/b7/c4fae9af5842f69d9c45bf1195a94aec090628535c102894552a7a7dbe6c/tesseract-0.1.3.tar.gz BuildArch: noarch %description The TesseRACt package is designed to compute concentrations of simulated dark matter halos from volume info for particles generated using Voronoi tesselation. This technique is advantageous as it is non-parametric, does not assume spherical symmetry, and allows for the presence of substructure. For a more complete description of this technique including a comparison to other techniques for calculating concentration, please see the accompanying paper `Lang et al. (2015) `_. This package includes: * **vorovol**: C program for computing the Voronoi diagram of particle data in a number of formats including Gadget-2, Gasoline, binary, and ASCII as well as BGC2 halo catalogues. * routines for compiling, running, and parsing **vorovol** output * routines for computing concentrations using particles volumes, traditional fitting to an NFW profile, and non-parametric techniques that assume spherical symmetry. * routines and test halos for running many of the performance tests presented in `Lang et al. (2015) `_. Below are some useful links associated with TesseRACt: * `PyPI `_ - The most recent stable release. * `Docs `_ - Tutorials and descriptions of the package modules and functions. * `Lang et al. (2015) `_ - The accompanying scientific paper. If you would like more information about TesseRACt, please contact `Meagan Lang `_. %package -n python3-tesseract Summary: Tesselation based Recovery of Amorphous halo Concentrations Provides: python-tesseract BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-tesseract The TesseRACt package is designed to compute concentrations of simulated dark matter halos from volume info for particles generated using Voronoi tesselation. This technique is advantageous as it is non-parametric, does not assume spherical symmetry, and allows for the presence of substructure. For a more complete description of this technique including a comparison to other techniques for calculating concentration, please see the accompanying paper `Lang et al. (2015) `_. This package includes: * **vorovol**: C program for computing the Voronoi diagram of particle data in a number of formats including Gadget-2, Gasoline, binary, and ASCII as well as BGC2 halo catalogues. * routines for compiling, running, and parsing **vorovol** output * routines for computing concentrations using particles volumes, traditional fitting to an NFW profile, and non-parametric techniques that assume spherical symmetry. * routines and test halos for running many of the performance tests presented in `Lang et al. (2015) `_. Below are some useful links associated with TesseRACt: * `PyPI `_ - The most recent stable release. * `Docs `_ - Tutorials and descriptions of the package modules and functions. * `Lang et al. (2015) `_ - The accompanying scientific paper. If you would like more information about TesseRACt, please contact `Meagan Lang `_. %package help Summary: Development documents and examples for tesseract Provides: python3-tesseract-doc %description help The TesseRACt package is designed to compute concentrations of simulated dark matter halos from volume info for particles generated using Voronoi tesselation. This technique is advantageous as it is non-parametric, does not assume spherical symmetry, and allows for the presence of substructure. For a more complete description of this technique including a comparison to other techniques for calculating concentration, please see the accompanying paper `Lang et al. (2015) `_. This package includes: * **vorovol**: C program for computing the Voronoi diagram of particle data in a number of formats including Gadget-2, Gasoline, binary, and ASCII as well as BGC2 halo catalogues. * routines for compiling, running, and parsing **vorovol** output * routines for computing concentrations using particles volumes, traditional fitting to an NFW profile, and non-parametric techniques that assume spherical symmetry. * routines and test halos for running many of the performance tests presented in `Lang et al. (2015) `_. Below are some useful links associated with TesseRACt: * `PyPI `_ - The most recent stable release. * `Docs `_ - Tutorials and descriptions of the package modules and functions. * `Lang et al. (2015) `_ - The accompanying scientific paper. If you would like more information about TesseRACt, please contact `Meagan Lang `_. %prep %autosetup -n tesseract-0.1.3 %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-tesseract -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Sun Apr 23 2023 Python_Bot - 0.1.3-1 - Package Spec generated