automatic import of python-AutoDiff-group3openeuler20.03

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+/AutoDiff_group3-0.0.6.tar.gz
diff --git a/python-autodiff-group3.spec b/python-autodiff-group3.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-AutoDiff-group3
+Version:	0.0.6
+Release:	1
+Summary:	Automatic differentiation with dual numbers
+License:	MIT License
+URL:		https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject
+Source0:	https://mirrors.aliyun.com/pypi/web/packages/5b/b4/29b7f91771b8381c08c098ead7a00065da95ae6e39479d965ce28deef129/AutoDiff_group3-0.0.6.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-pytest
+
+%description
+[![Build Status](https://travis-ci.com/cs207-project-erin-bruce-will/cs207-FinalProject.svg?branch=master)](https://travis-ci.com/cs207-project-erin-bruce-will/cs207-FinalProject)
+
+[![Coverage Status](https://coveralls.io/repos/github/cs207-project-erin-bruce-will/cs207-FinalProject/badge.svg)](https://coveralls.io/github/cs207-project-erin-bruce-will/cs207-FinalProject)
+
+# AutoDiff
+
+Developed by: Will Claybaugh, Bruce Xiong, Erin Williams  
+Group #3, CS207 Fall 2018
+
+
+## Introduction
+Autodiff finds the derivatives of a function (to machine precision!) at the same time it finds the value of the function.
+```
+import autodiff.autodiff as ad
+
+x = ad.DualNumber('x', 2)
+y = ad.DualNumber('y', 3)
+
+out = x/y
+out.value # 0.66666, the value of 2 divided by 3
+out.derivatives #{x: 1/3, y: -2/(3**2)}, the gradient of x/y at (2,3)
+```
+Autodiff works for functions and expressions with any number of inputs. Just pass those functions DualNumbers instead of regular ints/floats (and upgrade any math module functions to their autodiff equvalents)
+
+## Installation
+Autodiff is on [PyPi](https://pypi.org/project/AutoDiff-group3/) and can be installed using the command ```pip install AutoDiff-group3```. To import, use ```import autodiff.autodiff as ad```.
+
+Autodiff can also be installed by downloading from [github](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject). Becuase it has no dependencies, you can simply add the repo folder to your python path (```import sys
+sys.path.insert(0, '/path_to_repo/')```) and import as normal. 
+
+## Examples
+
+Using autodiff is very simple:
+```
+import autodiff.autodiff as ad
+
+def f(a,b):
+    return 3*a/b*ad.sin(a*b+2)
+
+out = f(ad.DualNumber('x',2),ad.DualNumber('y',3))
+
+print(out.value)
+1.978716
+
+print(out.derivatives['x'])
+0.116358
+
+print(out.derivatives['y'])
+-1.24157
+
+# get the value and derifative of f at a different point
+out = f(ad.DualNumber('x',0),ad.DualNumber('y',1))
+```
+
+A Python 3 notebook containing more in-depth examples and usage is available [HERE](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject/blob/master/docs/Demo.ipynb)
+
+## Documentation
+
+Click [HERE](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject/blob/master/docs/documentation.md) for full documentation.
+
+## Dependencies
+
+Click [HERE](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject/blob/master/docs/requirements.txt) for a full listing of dependencies.
+
+## License
+
+Click [HERE](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject/blob/master/LICENSE) to view our MIT License.
+
+
+
+
+
+
+%package -n python3-AutoDiff-group3
+Summary:	Automatic differentiation with dual numbers
+Provides:	python-AutoDiff-group3
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-AutoDiff-group3
+[![Build Status](https://travis-ci.com/cs207-project-erin-bruce-will/cs207-FinalProject.svg?branch=master)](https://travis-ci.com/cs207-project-erin-bruce-will/cs207-FinalProject)
+
+[![Coverage Status](https://coveralls.io/repos/github/cs207-project-erin-bruce-will/cs207-FinalProject/badge.svg)](https://coveralls.io/github/cs207-project-erin-bruce-will/cs207-FinalProject)
+
+# AutoDiff
+
+Developed by: Will Claybaugh, Bruce Xiong, Erin Williams  
+Group #3, CS207 Fall 2018
+
+
+## Introduction
+Autodiff finds the derivatives of a function (to machine precision!) at the same time it finds the value of the function.
+```
+import autodiff.autodiff as ad
+
+x = ad.DualNumber('x', 2)
+y = ad.DualNumber('y', 3)
+
+out = x/y
+out.value # 0.66666, the value of 2 divided by 3
+out.derivatives #{x: 1/3, y: -2/(3**2)}, the gradient of x/y at (2,3)
+```
+Autodiff works for functions and expressions with any number of inputs. Just pass those functions DualNumbers instead of regular ints/floats (and upgrade any math module functions to their autodiff equvalents)
+
+## Installation
+Autodiff is on [PyPi](https://pypi.org/project/AutoDiff-group3/) and can be installed using the command ```pip install AutoDiff-group3```. To import, use ```import autodiff.autodiff as ad```.
+
+Autodiff can also be installed by downloading from [github](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject). Becuase it has no dependencies, you can simply add the repo folder to your python path (```import sys
+sys.path.insert(0, '/path_to_repo/')```) and import as normal. 
+
+## Examples
+
+Using autodiff is very simple:
+```
+import autodiff.autodiff as ad
+
+def f(a,b):
+    return 3*a/b*ad.sin(a*b+2)
+
+out = f(ad.DualNumber('x',2),ad.DualNumber('y',3))
+
+print(out.value)
+1.978716
+
+print(out.derivatives['x'])
+0.116358
+
+print(out.derivatives['y'])
+-1.24157
+
+# get the value and derifative of f at a different point
+out = f(ad.DualNumber('x',0),ad.DualNumber('y',1))
+```
+
+A Python 3 notebook containing more in-depth examples and usage is available [HERE](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject/blob/master/docs/Demo.ipynb)
+
+## Documentation
+
+Click [HERE](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject/blob/master/docs/documentation.md) for full documentation.
+
+## Dependencies
+
+Click [HERE](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject/blob/master/docs/requirements.txt) for a full listing of dependencies.
+
+## License
+
+Click [HERE](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject/blob/master/LICENSE) to view our MIT License.
+
+
+
+
+
+
+%package help
+Summary:	Development documents and examples for AutoDiff-group3
+Provides:	python3-AutoDiff-group3-doc
+%description help
+[![Build Status](https://travis-ci.com/cs207-project-erin-bruce-will/cs207-FinalProject.svg?branch=master)](https://travis-ci.com/cs207-project-erin-bruce-will/cs207-FinalProject)
+
+[![Coverage Status](https://coveralls.io/repos/github/cs207-project-erin-bruce-will/cs207-FinalProject/badge.svg)](https://coveralls.io/github/cs207-project-erin-bruce-will/cs207-FinalProject)
+
+# AutoDiff
+
+Developed by: Will Claybaugh, Bruce Xiong, Erin Williams  
+Group #3, CS207 Fall 2018
+
+
+## Introduction
+Autodiff finds the derivatives of a function (to machine precision!) at the same time it finds the value of the function.
+```
+import autodiff.autodiff as ad
+
+x = ad.DualNumber('x', 2)
+y = ad.DualNumber('y', 3)
+
+out = x/y
+out.value # 0.66666, the value of 2 divided by 3
+out.derivatives #{x: 1/3, y: -2/(3**2)}, the gradient of x/y at (2,3)
+```
+Autodiff works for functions and expressions with any number of inputs. Just pass those functions DualNumbers instead of regular ints/floats (and upgrade any math module functions to their autodiff equvalents)
+
+## Installation
+Autodiff is on [PyPi](https://pypi.org/project/AutoDiff-group3/) and can be installed using the command ```pip install AutoDiff-group3```. To import, use ```import autodiff.autodiff as ad```.
+
+Autodiff can also be installed by downloading from [github](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject). Becuase it has no dependencies, you can simply add the repo folder to your python path (```import sys
+sys.path.insert(0, '/path_to_repo/')```) and import as normal. 
+
+## Examples
+
+Using autodiff is very simple:
+```
+import autodiff.autodiff as ad
+
+def f(a,b):
+    return 3*a/b*ad.sin(a*b+2)
+
+out = f(ad.DualNumber('x',2),ad.DualNumber('y',3))
+
+print(out.value)
+1.978716
+
+print(out.derivatives['x'])
+0.116358
+
+print(out.derivatives['y'])
+-1.24157
+
+# get the value and derifative of f at a different point
+out = f(ad.DualNumber('x',0),ad.DualNumber('y',1))
+```
+
+A Python 3 notebook containing more in-depth examples and usage is available [HERE](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject/blob/master/docs/Demo.ipynb)
+
+## Documentation
+
+Click [HERE](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject/blob/master/docs/documentation.md) for full documentation.
+
+## Dependencies
+
+Click [HERE](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject/blob/master/docs/requirements.txt) for a full listing of dependencies.
+
+## License
+
+Click [HERE](https://github.com/cs207-project-erin-bruce-will/cs207-FinalProject/blob/master/LICENSE) to view our MIT License.
+
+
+
+
+
+
+%prep
+%autosetup -n AutoDiff_group3-0.0.6
+
+%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-AutoDiff-group3 -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.6-1
+- Package Spec generated
diff --git a/sources b/sources
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+490e577830222afa09e98fd9687a5aca  AutoDiff_group3-0.0.6.tar.gz