""" http://pypi.python.org/pypi/cluster/1.1.1b3 """ from __future__ import absolute_import, division, print_function # # This is part of "python-cluster". A library to group similar items together. # Copyright (C) 2006 Michel Albert # # This library is free software; you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation; either version 2.1 of the License, or (at your option) # any later version. # This library is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # You should have received a copy of the GNU Lesser General Public License # along with this library; if not, write to the Free Software Foundation, Inc., # 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA # from libtbx.cluster import * from difflib import SequenceMatcher import unittest import sys def compare_list(x, y): """ Compare lists by content. Ordering does not matter. Returns True if both lists contain the same items (and are of identical length) """ cmpx = [set(cluster) for cluster in x] cmpy = [set(cluster) for cluster in y] all_ok = True for cset in cmpx: all_ok &= cset in cmpy for cset in cmpy: all_ok &= cset in cmpx return all_ok class HClusterSmallListTestCase(unittest.TestCase): " Test for Bug #1516204 " def testClusterLen1(self): "Testing if hierarchical clustering a set of length 1 returns a set of length 1" cl = HierarchicalClustering([876], lambda x,y: abs(x-y)) self.assertEqual([876], cl.getlevel(40)) def testClusterLen0(self): "Testing if hierarchical clustering an empty list returns an empty list" cl = HierarchicalClustering([], lambda x,y: abs(x-y)) self.assertEqual([], cl.getlevel(40)) class HClusterIntegerTestCase(unittest.TestCase): def setUp(self): self.__data = [791, 956, 676, 124, 564, 84, 24, 365, 594, 940, 398, 971, 131, 365, 542, 336, 518, 835, 134, 391] def testCluster(self): "Basic Hierarchical Clustering test with integers" cl = HierarchicalClustering(self.__data, lambda x,y: abs(x-y)) cl.cluster() self.assertEqual( [ [24], [84, 124, 131, 134], [336, 365, 365, 365, 398, 391], [940, 956, 971], [791], [835], [676], [518, 564, 542] ], cl.getlevel(40)) class HClusterStringTestCase(unittest.TestCase): def sim(self, x, y): sm = SequenceMatcher(lambda x: x in ". -", x, y) return 1-sm.ratio() def setUp(self): self.__data = "Lorem ipsum dolor sit amet, consectetuer adipiscing elit. Ut elit. Phasellus consequat ultricies mi. Sed congue leo at neque. Nullam.". split() def testDataTypes(self): "Test for bug #?" cl = HierarchicalClustering(self.__data, self.sim) for item in cl.getlevel(0.5): self.assertEqual( type(item), type([]), "Every item should be a list!") def testCluster(self): "Basic Hierachical clustering test with strings" cl = HierarchicalClustering(self.__data, self.sim) self.assertEqual([ ['Nullam.'], ['Sed'], ['mi.'], ['ultricies'], ['Phasellus'], ['amet,', 'at'], ['sit', 'elit.', 'elit.', 'elit.'], ['leo', 'Lorem', 'dolor'], ['neque.', 'congue', 'consectetuer', 'consequat'], ['ipsum'], ['adipiscing'] ], cl.getlevel(0.5) ) class KClusterSmallListTestCase(unittest.TestCase): def testClusterLen1(self): "Testing that a search space of length 1 returns only one cluster" cl = KMeansClustering([876]) self.assertEqual([876], cl.getclusters(2)) self.assertEqual([876], cl.getclusters(5)) def testClusterLen0(self): "Testing if clustering an empty set, returns an empty set" cl = KMeansClustering([]) self.assertEqual([], cl.getclusters(2)) self.assertEqual([], cl.getclusters(7)) class KCluster2DTestCase(unittest.TestCase): def testClusterCount(self): "Test that asking for less than 2 clusters raises an error" cl = KMeansClustering([876, 123, 344, 676], distance=lambda x,y: abs(x-y)) self.assertRaises(ClusteringError, cl.getclusters, 0) self.assertRaises(ClusteringError, cl.getclusters, 1) def testNonsenseCluster(self): "Test that asking for more clusters than data-items available raises an error" cl = KMeansClustering([876, 123], distance=lambda x,y: abs(x-y)) self.assertRaises(ClusteringError, cl.getclusters, 5) def testUniformLength(self): "Test if there is an item in the cluster that has a different cardinality" data = [ (1,5), (2,5), (2,6), (3,4), (3,5), (3,6,7), (7,3), (8,1), (8,2), (8), (9,2), (9,3) ] self.assertRaises(ValueError, KMeansClustering, data) def testPointDoubling(self): "test for bug #1604868" data = [ (18,13), (15, 12), (17,12), (18,12), (19,12), (16,11), (18, 11), (19,10), (0,0), (1, 4), (1,2), (2,3), (4,1), (4,3), (5,2), (6,1)] cl = KMeansClustering(data) clusters = cl.getclusters(2) expected = [[(18,13), (15, 12), (17,12), (18,12), (19,12), (16,11), (18, 11), (19,10)], [(0,0), (1, 4), (1,2), (2,3), (4,1), (5,2), (6,1), (4,3)]] self.assertEqual( True, compare_list( clusters, expected ), "Elements differ!\n%s\n%s" % (clusters, expected)) def testClustering(self): "Basic clustering test" data = [ (8,2), (7,3), (2,6), (3,5), (3,6), (1,5), (8,1), (3,4), (8,3), (9,2), (2,5), (9,3) ] cl = KMeansClustering(data) clusters = cl.getclusters(2) self.assertEqual( cl.getclusters(2), [[(8, 2), (8, 1), (8, 3), (7, 3), (9, 2), (9, 3)], [(3, 5), (1, 5), (3, 4), (2, 6), (2, 5), (3, 6)]]) class KClusterSFBugs(unittest.TestCase): def testLostFunctionReference(self): "test for bug #1727558" cl = KMeansClustering([(1,1), (20,40), (20,41)], lambda x,y:x+y) clusters = cl.getclusters(3) expected = [(1,1), (20,40), (20,41)] self.assertEqual( True, compare_list( clusters, expected ), "Elements differ!\n%s\n%s" % (clusters, expected)) if (__name__ == "__main__"): unittest.TextTestRunner(stream=sys.stdout, verbosity=0).run( unittest.TestSuite(( unittest.makeSuite(HClusterSmallListTestCase), unittest.makeSuite(HClusterIntegerTestCase), unittest.makeSuite(HClusterStringTestCase), unittest.makeSuite(KClusterSmallListTestCase), unittest.makeSuite(KCluster2DTestCase), unittest.makeSuite(KClusterSFBugs), )) )