points = [] points.append([1,1]) points.append([1.5,1]) points.append([1.8,1.5]) points.append([2.1,1]) points.append([3.1,2]) points.append([4.1,2]) points.append([5.1,2]) points.append([10,10]) points.append([11,10.5]) points.append([9.5,11]) points.append([9.9,11.4]) points.append([15.0, 17.0]) points.append([15.0, 17.0]) points.append([7.5, -5.0]) dbscan = DBSCANClusterer() #Small hacks..in normal usage never set td_matrix by urself #and never populate a dummy document_dict dbscan.td_matrix = points dbscan.document_dict = OrderedDict( [('0','dummy'), ('1', 'dummy'), ('2', 'dummy'),('3', 'dummy'),('4', 'dummy'),('5', 'dummy'), ('6', 'dummy'),('7', 'dummy'),('8', 'dummy'),('9', 'dummy'),('10', 'dummy'),('11', 'dummy'),('12', 'dummy'),('13', 'dummy')]) class Test_Dbscan_clustering(unittest.TestCase): def test_dbscan_cluster(self): clusters = dbscan.run(epsilon, min_pts) print '\n========== Results of Clustering =============' for cluster, members in clusters.iteritems(): print '\n--------Cluster %d---------' % cluster for point in members: print point