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|
%global _empty_manifest_terminate_build 0
Name: python-Pytrad
Version: 0.1.1.5
Release: 1
Summary: Pytrad Python Package
License: MIT License
URL: https://github.com/cmu-phil/pytrad
Source0: https://mirrors.aliyun.com/pypi/web/packages/6e/dd/924f75bed29d14de5368343e3448aa65bfe879f4f0fd46de772a1d002a8a/Pytrad-0.1.1.5.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-scipy
Requires: python3-scikit-learn
Requires: python3-graphviz
Requires: python3-statsmodels
Requires: python3-pandas
Requires: python3-matplotlib
Requires: python3-networkx
Requires: python3-pydot
%description
# Pytrad: Causal Discovery for Python
Pytrad is an open-source causal discovery library for Python, which is a Python translation and extension of [Tetrad](https://github.com/cmu-phil/tetrad).
The package is on its very first version and we are actively developing it. Please, as a beta user, if you are willing, would you please kindly share any feedbacks (issues, suggestions, etc.) about it with us?
# Package Overview
Our Pytrad implements methods for causal discovery:
* Constrained-based causal discovery methods.
* Score-based causal discovery methods.
* Causal discovery methods based on constrained functional causal models.
* Hidden causal representation learning.
* Granger causality.
* Multiple utilities for building your own method, such as independence tests, score functions, graph operations, and evaluations.
# Install
Pytrad needs the following packages to be installed beforehand:
* python 3
* numpy
* networkx
* pandas
* scipy
* scikit-learn
* statsmodels
* pydot
(For visualization)
* matplotlib
* graphviz
To use Pytrad, we could install it using [pip](https://pypi.org/project/sqlparse/):
```
pip install pytrad
```
# Documentation
Please kindly refer to [Pytrad Doc](https://pytrad-docs.readthedocs.io/en/latest/) for detailed tutorials and usages.
%package -n python3-Pytrad
Summary: Pytrad Python Package
Provides: python-Pytrad
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-Pytrad
# Pytrad: Causal Discovery for Python
Pytrad is an open-source causal discovery library for Python, which is a Python translation and extension of [Tetrad](https://github.com/cmu-phil/tetrad).
The package is on its very first version and we are actively developing it. Please, as a beta user, if you are willing, would you please kindly share any feedbacks (issues, suggestions, etc.) about it with us?
# Package Overview
Our Pytrad implements methods for causal discovery:
* Constrained-based causal discovery methods.
* Score-based causal discovery methods.
* Causal discovery methods based on constrained functional causal models.
* Hidden causal representation learning.
* Granger causality.
* Multiple utilities for building your own method, such as independence tests, score functions, graph operations, and evaluations.
# Install
Pytrad needs the following packages to be installed beforehand:
* python 3
* numpy
* networkx
* pandas
* scipy
* scikit-learn
* statsmodels
* pydot
(For visualization)
* matplotlib
* graphviz
To use Pytrad, we could install it using [pip](https://pypi.org/project/sqlparse/):
```
pip install pytrad
```
# Documentation
Please kindly refer to [Pytrad Doc](https://pytrad-docs.readthedocs.io/en/latest/) for detailed tutorials and usages.
%package help
Summary: Development documents and examples for Pytrad
Provides: python3-Pytrad-doc
%description help
# Pytrad: Causal Discovery for Python
Pytrad is an open-source causal discovery library for Python, which is a Python translation and extension of [Tetrad](https://github.com/cmu-phil/tetrad).
The package is on its very first version and we are actively developing it. Please, as a beta user, if you are willing, would you please kindly share any feedbacks (issues, suggestions, etc.) about it with us?
# Package Overview
Our Pytrad implements methods for causal discovery:
* Constrained-based causal discovery methods.
* Score-based causal discovery methods.
* Causal discovery methods based on constrained functional causal models.
* Hidden causal representation learning.
* Granger causality.
* Multiple utilities for building your own method, such as independence tests, score functions, graph operations, and evaluations.
# Install
Pytrad needs the following packages to be installed beforehand:
* python 3
* numpy
* networkx
* pandas
* scipy
* scikit-learn
* statsmodels
* pydot
(For visualization)
* matplotlib
* graphviz
To use Pytrad, we could install it using [pip](https://pypi.org/project/sqlparse/):
```
pip install pytrad
```
# Documentation
Please kindly refer to [Pytrad Doc](https://pytrad-docs.readthedocs.io/en/latest/) for detailed tutorials and usages.
%prep
%autosetup -n Pytrad-0.1.1.5
%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-Pytrad -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.1.5-1
- Package Spec generated
|
