automatic import of python-permutationimportanceopeneuler20.03

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+/PermutationImportance-1.2.1.8.tar.gz
diff --git a/python-permutationimportance.spec b/python-permutationimportance.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-PermutationImportance
+Version:	1.2.1.8
+Release:	1
+Summary:	Important variables determined through data-based variable importance methods
+License:	MIT
+URL:		https://github.com/gelijergensen/PermutationImportance
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/44/78/83c67e1d2f88808904762e3521aecdfe9bfd08505fa9b1f2629a1c7b6e32/PermutationImportance-1.2.1.8.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-pandas
+Requires:	python3-scipy
+Requires:	python3-scikit-learn
+
+%description
+# <span class="permutationimportancetitle">PermutationImportance</span>
+
+[![Build Status](https://travis-ci.com/gelijergensen/PermutationImportance.svg?branch=master)](https://travis-ci.com/gelijergensen/PermutationImportance)
+[![Documentation Status](https://readthedocs.org/projects/permutationimportance/badge/?version=latest)](https://permutationimportance.readthedocs.io/en/latest/?badge=latest)
+
+![PermutationImportance Logo](https://github.com/gelijergensen/PermutationImportance/blob/master/docs/images/favicon.png)
+
+Welcome to the PermutationImportance library!
+
+PermutationImportance is a Python package for Python 2.7 and 3.6+ which provides
+several methods for computing data-based predictor importance. The methods
+implemented are model-agnostic and can be used for any machine learning model in
+many stages of development. The complete documentation can be found at our
+[Read The Docs](https://permutationimportance.readthedocs.io/en/latest/).
+
+## Version History
+
+- 1.2.1.8: Shuffled pandas dataframes now retain the proper row indexing
+- 1.2.1.7: Fixed a bug where pandas dataframes were being unshuffled when 
+  concatenated
+- 1.2.1.5: Added documentation and examples and ensured compatibility with
+  Python 3.5+
+- 1.2.1.4: Original scores are now also bootstrapped to match the other results
+- 1.2.1.3: Corrected an issue with multithreading deadlock when returned scores
+  were too large
+- 1.2.1.1: Provided object to assist in constructing scoring strategies
+  - Also added two new strategies with bootstrapping support
+- 1.2.1.0: Metrics can now accept kwargs and support bootstrapping
+- 1.2.0.0: Added support for Sequential Selection and completely revised backend
+  for proper abstraction and extension
+  - Return object now keeps track of `(context, result)` pairs
+  - `abstract_variable_importance` enables implementation of custom variable
+    importance methods
+  - Backend is now correctly multithreaded (when specified) and is
+    OS-independent
+- 1.1.0.0: Revised return object of Permutation Importance to support easy
+  retrieval of Breiman- and Lakshmanan-style importances
+- 1.0.0.0: Published with `pip` support!
+
+
+
+
+%package -n python3-PermutationImportance
+Summary:	Important variables determined through data-based variable importance methods
+Provides:	python-PermutationImportance
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-PermutationImportance
+# <span class="permutationimportancetitle">PermutationImportance</span>
+
+[![Build Status](https://travis-ci.com/gelijergensen/PermutationImportance.svg?branch=master)](https://travis-ci.com/gelijergensen/PermutationImportance)
+[![Documentation Status](https://readthedocs.org/projects/permutationimportance/badge/?version=latest)](https://permutationimportance.readthedocs.io/en/latest/?badge=latest)
+
+![PermutationImportance Logo](https://github.com/gelijergensen/PermutationImportance/blob/master/docs/images/favicon.png)
+
+Welcome to the PermutationImportance library!
+
+PermutationImportance is a Python package for Python 2.7 and 3.6+ which provides
+several methods for computing data-based predictor importance. The methods
+implemented are model-agnostic and can be used for any machine learning model in
+many stages of development. The complete documentation can be found at our
+[Read The Docs](https://permutationimportance.readthedocs.io/en/latest/).
+
+## Version History
+
+- 1.2.1.8: Shuffled pandas dataframes now retain the proper row indexing
+- 1.2.1.7: Fixed a bug where pandas dataframes were being unshuffled when 
+  concatenated
+- 1.2.1.5: Added documentation and examples and ensured compatibility with
+  Python 3.5+
+- 1.2.1.4: Original scores are now also bootstrapped to match the other results
+- 1.2.1.3: Corrected an issue with multithreading deadlock when returned scores
+  were too large
+- 1.2.1.1: Provided object to assist in constructing scoring strategies
+  - Also added two new strategies with bootstrapping support
+- 1.2.1.0: Metrics can now accept kwargs and support bootstrapping
+- 1.2.0.0: Added support for Sequential Selection and completely revised backend
+  for proper abstraction and extension
+  - Return object now keeps track of `(context, result)` pairs
+  - `abstract_variable_importance` enables implementation of custom variable
+    importance methods
+  - Backend is now correctly multithreaded (when specified) and is
+    OS-independent
+- 1.1.0.0: Revised return object of Permutation Importance to support easy
+  retrieval of Breiman- and Lakshmanan-style importances
+- 1.0.0.0: Published with `pip` support!
+
+
+
+
+%package help
+Summary:	Development documents and examples for PermutationImportance
+Provides:	python3-PermutationImportance-doc
+%description help
+# <span class="permutationimportancetitle">PermutationImportance</span>
+
+[![Build Status](https://travis-ci.com/gelijergensen/PermutationImportance.svg?branch=master)](https://travis-ci.com/gelijergensen/PermutationImportance)
+[![Documentation Status](https://readthedocs.org/projects/permutationimportance/badge/?version=latest)](https://permutationimportance.readthedocs.io/en/latest/?badge=latest)
+
+![PermutationImportance Logo](https://github.com/gelijergensen/PermutationImportance/blob/master/docs/images/favicon.png)
+
+Welcome to the PermutationImportance library!
+
+PermutationImportance is a Python package for Python 2.7 and 3.6+ which provides
+several methods for computing data-based predictor importance. The methods
+implemented are model-agnostic and can be used for any machine learning model in
+many stages of development. The complete documentation can be found at our
+[Read The Docs](https://permutationimportance.readthedocs.io/en/latest/).
+
+## Version History
+
+- 1.2.1.8: Shuffled pandas dataframes now retain the proper row indexing
+- 1.2.1.7: Fixed a bug where pandas dataframes were being unshuffled when 
+  concatenated
+- 1.2.1.5: Added documentation and examples and ensured compatibility with
+  Python 3.5+
+- 1.2.1.4: Original scores are now also bootstrapped to match the other results
+- 1.2.1.3: Corrected an issue with multithreading deadlock when returned scores
+  were too large
+- 1.2.1.1: Provided object to assist in constructing scoring strategies
+  - Also added two new strategies with bootstrapping support
+- 1.2.1.0: Metrics can now accept kwargs and support bootstrapping
+- 1.2.0.0: Added support for Sequential Selection and completely revised backend
+  for proper abstraction and extension
+  - Return object now keeps track of `(context, result)` pairs
+  - `abstract_variable_importance` enables implementation of custom variable
+    importance methods
+  - Backend is now correctly multithreaded (when specified) and is
+    OS-independent
+- 1.1.0.0: Revised return object of Permutation Importance to support easy
+  retrieval of Breiman- and Lakshmanan-style importances
+- 1.0.0.0: Published with `pip` support!
+
+
+
+
+%prep
+%autosetup -n PermutationImportance-1.2.1.8
+
+%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-PermutationImportance -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.2.1.8-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
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--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+75c63d2630d056f232fbadbd5fa8c63e  PermutationImportance-1.2.1.8.tar.gz