def test_lsa(self): # Assert LSA properties. k = 100 lsa = vector.LSA(self.model, k) self.assertEqual(lsa.model, self.model) self.assertEqual(lsa.vectors, lsa.u) self.assertEqual(set(lsa.terms), set(self.model.vector.keys())) self.assertTrue(isinstance(lsa.u, dict)) self.assertTrue(isinstance(lsa.sigma, list)) self.assertTrue(isinstance(lsa.vt, list)) self.assertTrue(len(lsa.u), len(self.model)) self.assertTrue(len(lsa.sigma), len(self.model) - k) self.assertTrue(len(lsa.vt), len(self.model) - k) for document in self.model: v = lsa.vectors[document.id] self.assertTrue(isinstance(v, vector.Vector)) self.assertTrue(len(v) <= k) print("pattern.vector.LSA")
class TestLSA(unittest.TestCase): corpus = None def setUp(self): # Test spam corpus for reduction. if self.__class__.corpus is None: self.__class__.corpus = corpus(top=250) self.corpus = self.__class__.corpus random.seed(0) def tearDown(self): random.seed() def test_lsa(self): try: import numpy except ImportError, e: print e return # Assert LSA properties. k = 100 lsa = vector.LSA(self.corpus, k) self.assertEqual(lsa.corpus, self.corpus) self.assertEqual(lsa.vectors, lsa.u) self.assertEqual(set(lsa.terms), set(self.corpus.vector.keys())) self.assertTrue(isinstance(lsa.u, dict)) self.assertTrue(isinstance(lsa.sigma, list)) self.assertTrue(isinstance(lsa.vt, list)) self.assertTrue(len(lsa.u), len(self.corpus)) self.assertTrue(len(lsa.sigma), len(self.corpus) - k) self.assertTrue(len(lsa.vt), len(self.corpus) - k) for document in self.corpus: v = lsa.vectors[document.id] self.assertTrue(isinstance(v, vector.Vector)) self.assertTrue(len(v) == k) print "pattern.vector.LSA"
class TestLSA(unittest.TestCase): model = None def setUp(self): # Test spam model for reduction. if self.__class__.model is None: self.__class__.model = model(top=250) self.model = self.__class__.model random.seed(0) def tearDown(self): random.seed() def test_lsa(self): try: import numpy except ImportError, e: print(e) return # Assert LSA properties. k = 100 lsa = vector.LSA(self.model, k) self.assertEqual(lsa.model, self.model) self.assertEqual(lsa.vectors, lsa.u) self.assertEqual(set(lsa.terms), set(self.model.vector.keys())) self.assertTrue(isinstance(lsa.u, dict)) self.assertTrue(isinstance(lsa.sigma, list)) self.assertTrue(isinstance(lsa.vt, list)) self.assertTrue(len(lsa.u), len(self.model)) self.assertTrue(len(lsa.sigma), len(self.model)-k) self.assertTrue(len(lsa.vt), len(self.model)-k) for document in self.model: v = lsa.vectors[document.id] self.assertTrue(isinstance(v, vector.Vector)) self.assertTrue(len(v) <= k) print("pattern.vector.LSA")