| 506 | print "pattern.vector.Model.distance()" |
| 507 | |
| 508 | def test_cluster(self): |
| 509 | # Assert Model document clustering. |
| 510 | v1 = self.model.cluster(method=vector.KMEANS, k=10) |
| 511 | v2 = self.model.cluster(method=vector.HIERARCHICAL, k=1) |
| 512 | self.assertTrue(isinstance(v1, list) and len(v1) == 10) |
| 513 | self.assertTrue(isinstance(v2, vector.Cluster)) |
| 514 | def _test_clustered_documents(cluster): |
| 515 | if self.model[0] in cluster: |
| 516 | self.assertTrue(self.model[1] in cluster \ |
| 517 | and not self.model[2] in cluster) |
| 518 | if self.model[2] in cluster: |
| 519 | self.assertTrue(self.model[3] in cluster \ |
| 520 | and not self.model[1] in cluster) |
| 521 | v2.traverse(_test_clustered_documents) |
| 522 | print "pattern.vector.Model.cluster()" |
| 523 | |
| 524 | def test_centroid(self): |
| 525 | # Assert centroid of recursive Cluster. |