Unit tests for the analysis.clustering package. ''' import datetime, unittest from database.warehouse import WarehouseServer from analysis.clustering.kmeans import OrangeKmeansClusterer from tests.test_document import get_orange_clustering_test_data ########################################### # GLOBALS # ########################################### ws = WarehouseServer() sample_docs = get_orange_clustering_test_data() oc = OrangeKmeansClusterer(k=2) for s in sample_docs: oc.add_document(s) class TestOrangeClustering(unittest.TestCase): ########################################### # ORANGE TESTS # ########################################### def test_orange_sample_doc_kmeans(self): km = oc.run("orange_clustering_test") expected = [0, 0, 0, 1, 1, 1] self.assertEqual(expected, km.clusters) def test_orange_with_tweets_kmeans(self): import time start = time.time() from_date = datetime.datetime(2011, 1, 26, 0, 0, 0)
''' Created on 26 Jan 2012 @author: george ''' import unittest, numpy from analysis.clustering.kmeans import OrangeKmeansClusterer from tests.test_document import get_test_documents ########################################### # GLOBALS # ########################################### ignore, ignore, samples = get_test_documents() oc = OrangeKmeansClusterer(k=2) for sample in samples: oc.add_document(sample) class Test(unittest.TestCase): def test_orange_cluster_term_document_matrix(self): oc.construct_term_doc_matrix() calculated = oc.td_matrix expected = numpy.array( [[0.31388923, 0.11584717, 0, 0, 0, 0, 0.47083384], [0, 0.13515504, 0.3662041, 0, 0.3662041, 0, 0], [0, 0, 0, 0.54930614, 0, 0.549306140, 0]]) self.assertEqual(expected.all(), calculated.all()) def test_orange_save_matrix_to_tab_file(self): oc.construct_term_doc_matrix()
''' Created on 26 Jan 2012 @author: george ''' import unittest, numpy from analysis.clustering.kmeans import OrangeKmeansClusterer from tests.test_document import get_test_documents ########################################### # GLOBALS # ########################################### ignore, ignore, samples = get_test_documents() oc = OrangeKmeansClusterer(k=2) for sample in samples: oc.add_document(sample) class Test(unittest.TestCase): def test_orange_cluster_term_document_matrix(self): oc.construct_term_doc_matrix() calculated = oc.td_matrix expected = numpy.array([[ 0.31388923, 0.11584717, 0, 0, 0, 0, 0.47083384], [ 0, 0.13515504, 0.3662041, 0, 0.3662041, 0, 0 ], [ 0, 0, 0, 0.54930614, 0, 0.549306140, 0 ]]) self.assertEqual(expected.all(), calculated.all()) def test_orange_save_matrix_to_tab_file(self): oc.construct_term_doc_matrix() oc.save_table("sample_table_orange")
Unit tests for the analysis.clustering package. ''' import datetime, unittest from database.warehouse import WarehouseServer from analysis.clustering.kmeans import OrangeKmeansClusterer from tests.test_document import get_orange_clustering_test_data ########################################### # GLOBALS # ########################################### ws = WarehouseServer() sample_docs = get_orange_clustering_test_data() oc = OrangeKmeansClusterer(k=2) for s in sample_docs: oc.add_document(s) class TestOrangeClustering(unittest.TestCase): ########################################### # ORANGE TESTS # ########################################### def test_orange_sample_doc_kmeans(self): km = oc.run("orange_clustering_test") expected = [0, 0, 0, 1, 1, 1] self.assertEqual(expected, km.clusters) def test_orange_with_tweets_kmeans(self): import time start = time.time()