%global _empty_manifest_terminate_build 0
Name:		python-pycox
Version:	0.2.3
Release:	1
Summary:	Survival analysis with PyTorch
License:	BSD license
URL:		https://github.com/havakv/pycox
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/b4/bd/6cd4cc35313b2d2c1d6b9c19486c6f706db64dbac8685b5c705d7e010d85/pycox-0.2.3.tar.gz
BuildArch:	noarch

Requires:	python3-torchtuples
Requires:	python3-feather-format
Requires:	python3-h5py
Requires:	python3-numba
Requires:	python3-scikit-learn
Requires:	python3-requests
Requires:	python3-py7zr

%description

**pycox** is a python package for survival analysis and time-to-event prediction with [PyTorch](https://pytorch.org/).
It is built on the [torchtuples](https://github.com/havakv/torchtuples) package for training [PyTorch](https://pytorch.org/) models.

Read the documentation at: https://github.com/havakv/pycox

The package contains

- survival models: (Logistic-Hazard, DeepHit, DeepSurv, Cox-Time, MTLR, etc.)
- evaluation criteria (concordance, Brier score, Binomial log-likelihood, etc.)
- event-time datasets (SUPPORT, METABRIC, KKBox, etc)
- simulation studies
- illustrative examples




%package -n python3-pycox
Summary:	Survival analysis with PyTorch
Provides:	python-pycox
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-pycox

**pycox** is a python package for survival analysis and time-to-event prediction with [PyTorch](https://pytorch.org/).
It is built on the [torchtuples](https://github.com/havakv/torchtuples) package for training [PyTorch](https://pytorch.org/) models.

Read the documentation at: https://github.com/havakv/pycox

The package contains

- survival models: (Logistic-Hazard, DeepHit, DeepSurv, Cox-Time, MTLR, etc.)
- evaluation criteria (concordance, Brier score, Binomial log-likelihood, etc.)
- event-time datasets (SUPPORT, METABRIC, KKBox, etc)
- simulation studies
- illustrative examples




%package help
Summary:	Development documents and examples for pycox
Provides:	python3-pycox-doc
%description help

**pycox** is a python package for survival analysis and time-to-event prediction with [PyTorch](https://pytorch.org/).
It is built on the [torchtuples](https://github.com/havakv/torchtuples) package for training [PyTorch](https://pytorch.org/) models.

Read the documentation at: https://github.com/havakv/pycox

The package contains

- survival models: (Logistic-Hazard, DeepHit, DeepSurv, Cox-Time, MTLR, etc.)
- evaluation criteria (concordance, Brier score, Binomial log-likelihood, etc.)
- event-time datasets (SUPPORT, METABRIC, KKBox, etc)
- simulation studies
- illustrative examples




%prep
%autosetup -n pycox-0.2.3

%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-pycox -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.2.3-1
- Package Spec generated