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+%global _empty_manifest_terminate_build 0
+Name:		python-neurolab
+Version:	0.3.5
+Release:	1
+Summary:	Simple and powerfull neural network library for python
+License:	LGPL-3
+URL:		http://neurolab.googlecode.com
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/46/fd/47a9a39158b461b6b862d64c0ad7f679b08ed6d316744299f0db89066342/neurolab-0.3.5.tar.gz
+BuildArch:	noarch
+
+
+%description
+Neurolab is a simple and powerful Neural Network Library for Python.

+Contains based neural networks, train algorithms and flexible framework

+to create and explore other neural network types.

+

+

+:Features:

+

+    - Pure python + numpy

+    - API like Neural Network Toolbox (NNT) from MATLAB

+    - Interface to use train algorithms form scipy.optimize

+    - Flexible network configurations and learning algorithms. You may change: train, error, initialization and activation functions

+    - Unlimited number of neural layers and number of neurons in layers

+    - Variety of supported types of Artificial Neural Network and learning algorithms

+

+:Example:

+

+	>>> import numpy as np

+	>>> import neurolab as nl

+	>>> # Create train samples

+	>>> input = np.random.uniform(-0.5, 0.5, (10, 2))

+	>>> target = (input[:, 0] + input[:, 1]).reshape(10, 1)

+	>>> # Create network with 2 inputs, 5 neurons in input layer and 1 in output layer

+	>>> net = nl.net.newff([[-0.5, 0.5], [-0.5, 0.5]], [5, 1])

+	>>> # Train process

+	>>> err = net.train(input, target, show=15)

+	Epoch: 15; Error: 0.150308402918;

+	Epoch: 30; Error: 0.072265865089;

+	Epoch: 45; Error: 0.016931355131;

+	The goal of learning is reached

+	>>> # Test

+	>>> net.sim([[0.2, 0.1]]) # 0.2 + 0.1

+	array([[ 0.28757596]])

+

+:Links:

+

+    - `Home Page <http://code.google.com/p/neurolab/>`_

+    - `PyPI Page <http://pypi.python.org/pypi/neurolab>`_

+    - `Documentation <http://packages.python.org/neurolab/>`_

+    - `Examples <http://packages.python.org/neurolab/example.html>`_
+
+%package -n python3-neurolab
+Summary:	Simple and powerfull neural network library for python
+Provides:	python-neurolab
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-neurolab
+Neurolab is a simple and powerful Neural Network Library for Python.

+Contains based neural networks, train algorithms and flexible framework

+to create and explore other neural network types.

+

+

+:Features:

+

+    - Pure python + numpy

+    - API like Neural Network Toolbox (NNT) from MATLAB

+    - Interface to use train algorithms form scipy.optimize

+    - Flexible network configurations and learning algorithms. You may change: train, error, initialization and activation functions

+    - Unlimited number of neural layers and number of neurons in layers

+    - Variety of supported types of Artificial Neural Network and learning algorithms

+

+:Example:

+

+	>>> import numpy as np

+	>>> import neurolab as nl

+	>>> # Create train samples

+	>>> input = np.random.uniform(-0.5, 0.5, (10, 2))

+	>>> target = (input[:, 0] + input[:, 1]).reshape(10, 1)

+	>>> # Create network with 2 inputs, 5 neurons in input layer and 1 in output layer

+	>>> net = nl.net.newff([[-0.5, 0.5], [-0.5, 0.5]], [5, 1])

+	>>> # Train process

+	>>> err = net.train(input, target, show=15)

+	Epoch: 15; Error: 0.150308402918;

+	Epoch: 30; Error: 0.072265865089;

+	Epoch: 45; Error: 0.016931355131;

+	The goal of learning is reached

+	>>> # Test

+	>>> net.sim([[0.2, 0.1]]) # 0.2 + 0.1

+	array([[ 0.28757596]])

+

+:Links:

+

+    - `Home Page <http://code.google.com/p/neurolab/>`_

+    - `PyPI Page <http://pypi.python.org/pypi/neurolab>`_

+    - `Documentation <http://packages.python.org/neurolab/>`_

+    - `Examples <http://packages.python.org/neurolab/example.html>`_
+
+%package help
+Summary:	Development documents and examples for neurolab
+Provides:	python3-neurolab-doc
+%description help
+Neurolab is a simple and powerful Neural Network Library for Python.

+Contains based neural networks, train algorithms and flexible framework

+to create and explore other neural network types.

+

+

+:Features:

+

+    - Pure python + numpy

+    - API like Neural Network Toolbox (NNT) from MATLAB

+    - Interface to use train algorithms form scipy.optimize

+    - Flexible network configurations and learning algorithms. You may change: train, error, initialization and activation functions

+    - Unlimited number of neural layers and number of neurons in layers

+    - Variety of supported types of Artificial Neural Network and learning algorithms

+

+:Example:

+

+	>>> import numpy as np

+	>>> import neurolab as nl

+	>>> # Create train samples

+	>>> input = np.random.uniform(-0.5, 0.5, (10, 2))

+	>>> target = (input[:, 0] + input[:, 1]).reshape(10, 1)

+	>>> # Create network with 2 inputs, 5 neurons in input layer and 1 in output layer

+	>>> net = nl.net.newff([[-0.5, 0.5], [-0.5, 0.5]], [5, 1])

+	>>> # Train process

+	>>> err = net.train(input, target, show=15)

+	Epoch: 15; Error: 0.150308402918;

+	Epoch: 30; Error: 0.072265865089;

+	Epoch: 45; Error: 0.016931355131;

+	The goal of learning is reached

+	>>> # Test

+	>>> net.sim([[0.2, 0.1]]) # 0.2 + 0.1

+	array([[ 0.28757596]])

+

+:Links:

+

+    - `Home Page <http://code.google.com/p/neurolab/>`_

+    - `PyPI Page <http://pypi.python.org/pypi/neurolab>`_

+    - `Documentation <http://packages.python.org/neurolab/>`_

+    - `Examples <http://packages.python.org/neurolab/example.html>`_
+
+%prep
+%autosetup -n neurolab-0.3.5
+
+%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-neurolab -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.3.5-1
+- Package Spec generated