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+%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