%global _empty_manifest_terminate_build 0
Name: python-alphatwirl
Version: 0.30.0
Release: 1
Summary: A Python library for summarizing event data
License: BSD License
URL: https://github.com/alphatwirl/alphatwirl
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/af/ab/f12aeb7b1047d5edfca937668bb178f329c9f20bd5ce1b1b8015a716e224/alphatwirl-0.30.0.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-atpbar
Requires: python3-mantichora
%description
A Python library for summarizing event data into multivariate categorical data
### Description
_AlphaTwirl_ is a Python library that summarizes event data into multivariate categorical data as data frames. Event data, input to AlphaTwirl, are data with one entry (or row) for one event: for example, data in [ROOT](https://root.cern.ch/) [TTrees](https://root.cern.ch/doc/master/classTTree.html) with one entry per collision event of an [LHC](https://home.cern/topics/large-hadron-collider) experiment at [CERN](http://home.cern/). Event data are often large—too large to be loaded in memory—because they have as many entries as events. Multivariate categorical data, the output of AlphaTwirl, have one row for one category. They are usually small—small enough to be loaded in memory—because they only have as many rows as categories. Users can, for example, import them as data frames into [R](https://www.r-project.org/) and [pandas](http://pandas.pydata.org/), which usually load all data in memory, and can perform categorical data analyses with a rich set of data operations available in R and pandas.
****
### Quick start
- Jupyter Notebook: [*Quick start of AlphaTwirl*](https://github.com/alphatwirl/notebook-tutorial-2019-02)
[](https://mybinder.org/v2/gh/alphatwirl/notebook-tutorial-2019-02/master?filepath=tutorial_01.ipynb)
****
### Publication
- Tai Sakuma, *"AlphaTwirl: A Python library for summarizing event data into multivariate categorical data"*,
EPJ Web of Conferences **214**, 02001 (2019), [doi:10.1051/epjconf/201921402001](https://doi.org/10.1051/epjconf/201921402001),
[1905.06609](https://arxiv.org/abs/1905.06609)
****
### License
- AlphaTwirl is licensed under the BSD license.
*****
### Contact
- Tai Sakuma - tai.sakuma@gmail.com
%package -n python3-alphatwirl
Summary: A Python library for summarizing event data
Provides: python-alphatwirl
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-alphatwirl
A Python library for summarizing event data into multivariate categorical data
### Description
_AlphaTwirl_ is a Python library that summarizes event data into multivariate categorical data as data frames. Event data, input to AlphaTwirl, are data with one entry (or row) for one event: for example, data in [ROOT](https://root.cern.ch/) [TTrees](https://root.cern.ch/doc/master/classTTree.html) with one entry per collision event of an [LHC](https://home.cern/topics/large-hadron-collider) experiment at [CERN](http://home.cern/). Event data are often large—too large to be loaded in memory—because they have as many entries as events. Multivariate categorical data, the output of AlphaTwirl, have one row for one category. They are usually small—small enough to be loaded in memory—because they only have as many rows as categories. Users can, for example, import them as data frames into [R](https://www.r-project.org/) and [pandas](http://pandas.pydata.org/), which usually load all data in memory, and can perform categorical data analyses with a rich set of data operations available in R and pandas.
****
### Quick start
- Jupyter Notebook: [*Quick start of AlphaTwirl*](https://github.com/alphatwirl/notebook-tutorial-2019-02)
[](https://mybinder.org/v2/gh/alphatwirl/notebook-tutorial-2019-02/master?filepath=tutorial_01.ipynb)
****
### Publication
- Tai Sakuma, *"AlphaTwirl: A Python library for summarizing event data into multivariate categorical data"*,
EPJ Web of Conferences **214**, 02001 (2019), [doi:10.1051/epjconf/201921402001](https://doi.org/10.1051/epjconf/201921402001),
[1905.06609](https://arxiv.org/abs/1905.06609)
****
### License
- AlphaTwirl is licensed under the BSD license.
*****
### Contact
- Tai Sakuma - tai.sakuma@gmail.com
%package help
Summary: Development documents and examples for alphatwirl
Provides: python3-alphatwirl-doc
%description help
A Python library for summarizing event data into multivariate categorical data
### Description
_AlphaTwirl_ is a Python library that summarizes event data into multivariate categorical data as data frames. Event data, input to AlphaTwirl, are data with one entry (or row) for one event: for example, data in [ROOT](https://root.cern.ch/) [TTrees](https://root.cern.ch/doc/master/classTTree.html) with one entry per collision event of an [LHC](https://home.cern/topics/large-hadron-collider) experiment at [CERN](http://home.cern/). Event data are often large—too large to be loaded in memory—because they have as many entries as events. Multivariate categorical data, the output of AlphaTwirl, have one row for one category. They are usually small—small enough to be loaded in memory—because they only have as many rows as categories. Users can, for example, import them as data frames into [R](https://www.r-project.org/) and [pandas](http://pandas.pydata.org/), which usually load all data in memory, and can perform categorical data analyses with a rich set of data operations available in R and pandas.
****
### Quick start
- Jupyter Notebook: [*Quick start of AlphaTwirl*](https://github.com/alphatwirl/notebook-tutorial-2019-02)
[](https://mybinder.org/v2/gh/alphatwirl/notebook-tutorial-2019-02/master?filepath=tutorial_01.ipynb)
****
### Publication
- Tai Sakuma, *"AlphaTwirl: A Python library for summarizing event data into multivariate categorical data"*,
EPJ Web of Conferences **214**, 02001 (2019), [doi:10.1051/epjconf/201921402001](https://doi.org/10.1051/epjconf/201921402001),
[1905.06609](https://arxiv.org/abs/1905.06609)
****
### License
- AlphaTwirl is licensed under the BSD license.
*****
### Contact
- Tai Sakuma - tai.sakuma@gmail.com
%prep
%autosetup -n alphatwirl-0.30.0
%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-alphatwirl -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri May 05 2023 Python_Bot - 0.30.0-1
- Package Spec generated