%global _empty_manifest_terminate_build 0 Name: python-tdub Version: 0.0.79 Release: 1 Summary: tW analysis tools. License: BSD 3-clause URL: https://github.com/douglasdavis/tdub Source0: https://mirrors.nju.edu.cn/pypi/web/packages/95/eb/57e2f7c6f6f6f2089b5c4a5c3b235e327876a25015d0aec35d0bd7a2bd85/tdub-0.0.79.tar.gz BuildArch: noarch Requires: python3-click Requires: python3-formulate Requires: python3-joblib Requires: python3-lz4 Requires: python3-matplotlib Requires: python3-numexpr Requires: python3-pandas Requires: python3-pycondor Requires: python3-pygram11 Requires: python3-pyyaml Requires: python3-scikit-learn Requires: python3-uproot Requires: python3-xxhash Requires: python3-requests %description # tdub [![Actions Status](https://github.com/douglasdavis/tdub/workflows/Linux/macOS/badge.svg)](https://github.com/douglasdavis/tdub/actions) [![Documentation Status](https://readthedocs.org/projects/tdub/badge/?version=latest)](https://tdub.readthedocs.io/) [![PyPI](https://img.shields.io/pypi/v/tdub?color=teal)](https://pypi.org/project/tdub/) [![Python Version](https://img.shields.io/pypi/pyversions/tdub)](https://pypi.org/project/tdub/) `tdub` is a Python project for handling some downstsream steps in the ATLAS Run 2 *tW* inclusive cross section analysis. The project provides a simple command line interface for performing standard analysis tasks including: - BDT feature selection and hyperparameter optimization. - Training BDT models on our Monte Carlo. - Applying trained BDT models to our data and Monte Carlo. - Generating plots from various raw sources (our ROOT files and Classifier training output). - Generating plots from the output of [`TRExFitter`](https://gitlab.cern.ch/TRExStats/TRExFitter/). For potentially finer-grained tasks the API is fully documented. The API mainly provides quick and easy access to pythonic representations (i.e. dataframes or NumPy arrays) of our datasets (which of course originate from [ROOT](https://root.cern/) files), modularized ML tasks, and a set of utilities tailored for interacting with our specific datasets. %package -n python3-tdub Summary: tW analysis tools. Provides: python-tdub BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-tdub # tdub [![Actions Status](https://github.com/douglasdavis/tdub/workflows/Linux/macOS/badge.svg)](https://github.com/douglasdavis/tdub/actions) [![Documentation Status](https://readthedocs.org/projects/tdub/badge/?version=latest)](https://tdub.readthedocs.io/) [![PyPI](https://img.shields.io/pypi/v/tdub?color=teal)](https://pypi.org/project/tdub/) [![Python Version](https://img.shields.io/pypi/pyversions/tdub)](https://pypi.org/project/tdub/) `tdub` is a Python project for handling some downstsream steps in the ATLAS Run 2 *tW* inclusive cross section analysis. The project provides a simple command line interface for performing standard analysis tasks including: - BDT feature selection and hyperparameter optimization. - Training BDT models on our Monte Carlo. - Applying trained BDT models to our data and Monte Carlo. - Generating plots from various raw sources (our ROOT files and Classifier training output). - Generating plots from the output of [`TRExFitter`](https://gitlab.cern.ch/TRExStats/TRExFitter/). For potentially finer-grained tasks the API is fully documented. The API mainly provides quick and easy access to pythonic representations (i.e. dataframes or NumPy arrays) of our datasets (which of course originate from [ROOT](https://root.cern/) files), modularized ML tasks, and a set of utilities tailored for interacting with our specific datasets. %package help Summary: Development documents and examples for tdub Provides: python3-tdub-doc %description help # tdub [![Actions Status](https://github.com/douglasdavis/tdub/workflows/Linux/macOS/badge.svg)](https://github.com/douglasdavis/tdub/actions) [![Documentation Status](https://readthedocs.org/projects/tdub/badge/?version=latest)](https://tdub.readthedocs.io/) [![PyPI](https://img.shields.io/pypi/v/tdub?color=teal)](https://pypi.org/project/tdub/) [![Python Version](https://img.shields.io/pypi/pyversions/tdub)](https://pypi.org/project/tdub/) `tdub` is a Python project for handling some downstsream steps in the ATLAS Run 2 *tW* inclusive cross section analysis. The project provides a simple command line interface for performing standard analysis tasks including: - BDT feature selection and hyperparameter optimization. - Training BDT models on our Monte Carlo. - Applying trained BDT models to our data and Monte Carlo. - Generating plots from various raw sources (our ROOT files and Classifier training output). - Generating plots from the output of [`TRExFitter`](https://gitlab.cern.ch/TRExStats/TRExFitter/). For potentially finer-grained tasks the API is fully documented. The API mainly provides quick and easy access to pythonic representations (i.e. dataframes or NumPy arrays) of our datasets (which of course originate from [ROOT](https://root.cern/) files), modularized ML tasks, and a set of utilities tailored for interacting with our specific datasets. %prep %autosetup -n tdub-0.0.79 %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-tdub -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue May 30 2023 Python_Bot - 0.0.79-1 - Package Spec generated