automatic import of python-glimix-core

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+/glimix-core-3.1.13.tar.gz
diff --git a/python-glimix-core.spec b/python-glimix-core.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-glimix-core
+Version:	3.1.13
+Release:	1
+Summary:	Fast inference over mean and covariance parameters for Generalised Linear Mixed Models
+License:	MIT
+URL:		https://github.com/limix/glimix-core
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/b6/2a/c77df3eff97040fdd82bde3dac78c8130823230e56fce7d3ef86b09a17a9/glimix-core-3.1.13.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-brent-search
+Requires:	python3-liknorm
+Requires:	python3-ndarray-listener
+Requires:	python3-numpy
+Requires:	python3-numpy-sugar
+Requires:	python3-optimix
+Requires:	python3-pytest
+Requires:	python3-pytest-doctestplus
+Requires:	python3-scipy
+Requires:	python3-tqdm
+
+%description
+# glimix-core
+
+[![Documentation](https://readthedocs.org/projects/glimix-core/badge/?version=latest)](https://glimix-core.readthedocs.io/en/latest/?badge=latest)
+
+Fast inference over mean and covariance parameters for Generalised Linear Mixed
+Models.
+
+It implements the mathematical tricks of
+[FaST-LMM](https://github.com/MicrosoftGenomics/FaST-LMM) for the special case
+of Linear Mixed Models with a linear covariance matrix and provides an
+interface to perform inference over millions of covariates in seconds.
+The Generalised Linear Mixed Model inference is implemented via Expectation
+Propagation and also makes use of several mathematical tricks to handle large
+data sets with thousands of samples and millions of covariates.
+
+## Install
+
+There are two main ways of installing it.
+Via [pip](https://pypi.python.org/pypi/pip):
+
+```bash
+pip install glimix-core
+```
+
+Or via [conda](http://conda.pydata.org/docs/index.html):
+
+```bash
+conda install -c conda-forge glimix-core
+```
+
+## Running the tests
+
+After installation, you can test it
+
+```bash
+python -c "import glimix_core; glimix_core.test()"
+```
+
+as long as you have [pytest](https://docs.pytest.org/en/latest/).
+
+## Usage
+
+Here it is a very simple example to get you started:
+
+```python
+>>> from numpy import array, ones
+>>> from numpy_sugar.linalg import economic_qs_linear
+>>> from glimix_core.lmm import LMM
+>>>
+>>> X = array([[1, 2], [3, -1], [1.1, 0.5], [0.5, -0.4]], float)
+>>> QS = economic_qs_linear(X, False)
+>>> X = ones((4, 1))
+>>> y = array([-1, 2, 0.3, 0.5])
+>>> lmm = LMM(y, X, QS)
+>>> lmm.fit(verbose=False)
+>>> lmm.lml()
+-2.2726234086180557
+```
+
+We  also provide an extensive [documentation](http://glimix-core.readthedocs.org/) about the library.
+
+## Authors
+
+* [Danilo Horta](https://github.com/horta)
+
+## License
+
+This project is licensed under the [MIT License](https://raw.githubusercontent.com/limix/glimix-core/master/LICENSE.md).
+
+
+
+%package -n python3-glimix-core
+Summary:	Fast inference over mean and covariance parameters for Generalised Linear Mixed Models
+Provides:	python-glimix-core
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-glimix-core
+# glimix-core
+
+[![Documentation](https://readthedocs.org/projects/glimix-core/badge/?version=latest)](https://glimix-core.readthedocs.io/en/latest/?badge=latest)
+
+Fast inference over mean and covariance parameters for Generalised Linear Mixed
+Models.
+
+It implements the mathematical tricks of
+[FaST-LMM](https://github.com/MicrosoftGenomics/FaST-LMM) for the special case
+of Linear Mixed Models with a linear covariance matrix and provides an
+interface to perform inference over millions of covariates in seconds.
+The Generalised Linear Mixed Model inference is implemented via Expectation
+Propagation and also makes use of several mathematical tricks to handle large
+data sets with thousands of samples and millions of covariates.
+
+## Install
+
+There are two main ways of installing it.
+Via [pip](https://pypi.python.org/pypi/pip):
+
+```bash
+pip install glimix-core
+```
+
+Or via [conda](http://conda.pydata.org/docs/index.html):
+
+```bash
+conda install -c conda-forge glimix-core
+```
+
+## Running the tests
+
+After installation, you can test it
+
+```bash
+python -c "import glimix_core; glimix_core.test()"
+```
+
+as long as you have [pytest](https://docs.pytest.org/en/latest/).
+
+## Usage
+
+Here it is a very simple example to get you started:
+
+```python
+>>> from numpy import array, ones
+>>> from numpy_sugar.linalg import economic_qs_linear
+>>> from glimix_core.lmm import LMM
+>>>
+>>> X = array([[1, 2], [3, -1], [1.1, 0.5], [0.5, -0.4]], float)
+>>> QS = economic_qs_linear(X, False)
+>>> X = ones((4, 1))
+>>> y = array([-1, 2, 0.3, 0.5])
+>>> lmm = LMM(y, X, QS)
+>>> lmm.fit(verbose=False)
+>>> lmm.lml()
+-2.2726234086180557
+```
+
+We  also provide an extensive [documentation](http://glimix-core.readthedocs.org/) about the library.
+
+## Authors
+
+* [Danilo Horta](https://github.com/horta)
+
+## License
+
+This project is licensed under the [MIT License](https://raw.githubusercontent.com/limix/glimix-core/master/LICENSE.md).
+
+
+
+%package help
+Summary:	Development documents and examples for glimix-core
+Provides:	python3-glimix-core-doc
+%description help
+# glimix-core
+
+[![Documentation](https://readthedocs.org/projects/glimix-core/badge/?version=latest)](https://glimix-core.readthedocs.io/en/latest/?badge=latest)
+
+Fast inference over mean and covariance parameters for Generalised Linear Mixed
+Models.
+
+It implements the mathematical tricks of
+[FaST-LMM](https://github.com/MicrosoftGenomics/FaST-LMM) for the special case
+of Linear Mixed Models with a linear covariance matrix and provides an
+interface to perform inference over millions of covariates in seconds.
+The Generalised Linear Mixed Model inference is implemented via Expectation
+Propagation and also makes use of several mathematical tricks to handle large
+data sets with thousands of samples and millions of covariates.
+
+## Install
+
+There are two main ways of installing it.
+Via [pip](https://pypi.python.org/pypi/pip):
+
+```bash
+pip install glimix-core
+```
+
+Or via [conda](http://conda.pydata.org/docs/index.html):
+
+```bash
+conda install -c conda-forge glimix-core
+```
+
+## Running the tests
+
+After installation, you can test it
+
+```bash
+python -c "import glimix_core; glimix_core.test()"
+```
+
+as long as you have [pytest](https://docs.pytest.org/en/latest/).
+
+## Usage
+
+Here it is a very simple example to get you started:
+
+```python
+>>> from numpy import array, ones
+>>> from numpy_sugar.linalg import economic_qs_linear
+>>> from glimix_core.lmm import LMM
+>>>
+>>> X = array([[1, 2], [3, -1], [1.1, 0.5], [0.5, -0.4]], float)
+>>> QS = economic_qs_linear(X, False)
+>>> X = ones((4, 1))
+>>> y = array([-1, 2, 0.3, 0.5])
+>>> lmm = LMM(y, X, QS)
+>>> lmm.fit(verbose=False)
+>>> lmm.lml()
+-2.2726234086180557
+```
+
+We  also provide an extensive [documentation](http://glimix-core.readthedocs.org/) about the library.
+
+## Authors
+
+* [Danilo Horta](https://github.com/horta)
+
+## License
+
+This project is licensed under the [MIT License](https://raw.githubusercontent.com/limix/glimix-core/master/LICENSE.md).
+
+
+
+%prep
+%autosetup -n glimix-core-3.1.13
+
+%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-glimix-core -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon May 29 2023 Python_Bot <Python_Bot@openeuler.org> - 3.1.13-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..74a5532
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+ac6696edb4abb6c30810987493fc8c20  glimix-core-3.1.13.tar.gz