Пакет python-module-mdp: Specfile
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 | %define oname mdp Name: python-module-%oname Version: 3.3 Release: alt1.git20111024 Summary: Modular toolkit for Data Processing Group: Development/Python License: LGPL v2 URL: http://mdp-toolkit.sourceforge.net/ # git://mdp-toolkit.git.sourceforge.net/gitroot/mdp-toolkit/mdp-toolkit Source: %oname-%version.tar.gz Source1: MDP-tutorial.pdf BuildArch: noarch Packager: Eugeny A. Rostovtsev (REAL) <real at altlinux.org> %add_python_req_skip test shogun BuildPreReq: python-devel BuildPreReq: python-module-scipy BuildPreReq: libnumpy-devel Requires: %name-tests = %version-%release %description Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded. The implementation of new algorithms is easy and intuitive. The new implemented units are then automatically integrated with the rest of the library. The base of available algorithms is steadily increasing and includes, to name but the most common, Principal Component Analysis (PCA and NIPALS), several Independent Component Analysis algorithms (CuBICA, FastICA, TDSEP, JADE, and XSFA), Slow Feature Analysis, Gaussian Classifiers, Restricted Boltzmann Machine, and Locally Linear Embedding. %package tests Summary: Tests for Modular toolkit for Data Processing Group: Development/Python Requires: %name = %version-%release %description tests Modular toolkit for Data Processing (MDP) is a Python data processing framework. This package contains tests for MDP. %package pickles Summary: Pickles for Modular toolkit for Data Processing Group: Development/Python %description pickles Modular toolkit for Data Processing (MDP) is a Python data processing framework. This package contains pickles for MDP. %package doc Summary: Documentation for Modular toolkit for Data Processing Group: Development/Documentation BuildArch: noarch %description doc Modular toolkit for Data Processing (MDP) is a Python data processing framework. This package contains documentation for MDP. %package -n python-module-binet Summary: Extension of the pure feed-forward flow concept in MDP Group: Development/Python BuildArch: noarch %add_python_req_skip test %description -n python-module-binet The BiNet package is an extension of the pure feed-forward flow concept in MDP. It defines a framework for far more general flow sequences, involving top-down processes (e.g. for error backpropagation) or even loops. So the 'bi' in BiNet primarily stands for 'bidirectional'. BiNet is implemented by extending both the Node and the Flow concept. Both the new BiNode and BiFlow classes are 'downward' compatible with the classical Nodes and Flows, so they can be combined with BiNet elements. The fundamental addition in BiNet is that BiNodes can specify a target node for their output and that they can send messages to other nodes. A BiFlow is then needed to interpret these arguments, e.g. to continue the flow execution at the specified target node. BiNet is fully integrated with the HiNet and the Parallel packages. This was actually one main motivation for creating BiNet, to leverage the modular design of the other MDP packages. %package -n python-module-binet-tests Summary: Tests for the pure feed-forward flow concept in MDP Group: Development/Python Requires: python-module-binet = %version-%release %description -n python-module-binet-tests The BiNet package is an extension of the pure feed-forward flow concept in MDP. This package contains tests for BitNet. %prep %setup install -p -m644 %SOURCE1 . %build %python_build %install %python_install %files %python_sitelibdir/* %exclude %python_sitelibdir/%oname/test %exclude %python_sitelibdir/bimdp/test #files pickles #dir %python_sitelibdir/%oname #python_sitelibdir/%oname/pickle %files tests %python_sitelibdir/%oname/test %python_sitelibdir/bimdp/test %files doc %doc *.pdf CHANGES CHECKLIST COPYRIGHT %doc README TODO #files -n python-module-binet #python_sitelibdir/binet #exclude %python_sitelibdir/binet/test #files -n python-module-binet-tests #python_sitelibdir/binet/test %changelog * Fri Dec 09 2011 Eugeny A. Rostovtsev (REAL) <real at altlinux.org> 3.3-alt1.git20111024 - Version 3.3 * Mon Oct 24 2011 Vitaly Kuznetsov <vitty@altlinux.ru> 3.2-alt1.git20110415.1 - Rebuild with Python-2.7 * Thu May 12 2011 Eugeny A. Rostovtsev (REAL) <real at altlinux.org> 3.2-alt1.git20110415 - Version 3.2 * Wed Nov 24 2010 Eugeny A. Rostovtsev (REAL) <real at altlinux.org> 2.6-alt1.git20101123 - New snapshot * Wed Jul 28 2010 Eugeny A. Rostovtsev (REAL) <real at altlinux.org> 2.6-alt1.git20100725 - Version 2.6 * Thu Mar 18 2010 Eugeny A. Rostovtsev (REAL) <real at altlinux.org> 2.5-alt1.svn20091007.2 - Extracted tests into separate packages - Added + pickles package + examples * Thu Nov 19 2009 Eugeny A. Rostovtsev (REAL) <real at altlinux.org> 2.5-alt1.svn20091007.1 - Rebuilt with python 2.6 * Fri Oct 09 2009 Eugeny A. Rostovtsev (REAL) <real at altlinux.org> 2.5-alt1.svn20091007 - Initial build for Sisyphus |