Topic modelling - Reorder methods by relevance

orangecontrib/text/widgets/owtopicmodeling.py

@@ -267,6 +267,8 @@ def on_done(self, corpus):
         if self.model.name == "Latent Dirichlet Allocation":
             bound = self.model.model.log_perplexity(infer_ngrams_corpus(corpus))
             self.perplexity = "{:.5f}".format(np.exp2(-bound))
+        else:
+            self.perplexity = "n/a"
         # for small corpora it is slower to use more processes
         # there is no good estimation when multiprocessing is helpful, but it is
         # definitely not helpful for corpora smaller than 100

orangecontrib/text/widgets/tests/test_owtopicmodeling.py

@@ -22,7 +22,6 @@ def test_data(self):
         self.assertIsNone(output)
 
     def test_saved_selection(self):
-        self.widget.method_index = 1
         self.send_signal(self.widget.Inputs.corpus, self.corpus)
         self.wait_until_finished()
 
@@ -58,17 +57,16 @@ def test_topic_evaluation(self):
         self.send_signal(self.widget.Inputs.corpus, self.corpus)
         self.wait_until_finished()
 
-        # test LSI
-        self.assertEqual(self.widget.perplexity, "n/a")
-        self.assertNotEqual(self.widget.coherence, "n/a")
-
         # test LDA, which is the only one with log perplexity
+        self.assertNotEqual(self.widget.perplexity, "n/a")
+        self.assertTrue(self.widget.coherence)
+
+        # test LSI
         self.widget.method_index = 1
         self.widget.commit.now()
         self.wait_until_finished()
-
-        self.assertNotEqual(self.widget.perplexity, "n/a")
-        self.assertTrue(self.widget.coherence)
+        self.assertEqual(self.widget.perplexity, "n/a")
+        self.assertNotEqual(self.widget.coherence, "n/a")
 
     def test_migrate_settings_transform(self):
         # 0 used to be LSI in version <2 - it is on index 1 now