Fix calculation error when ref is empty

.gitignore

@@ -22,3 +22,30 @@ glove2word2vec.py
 
 .idea/
 venv/
+
+# General
+.DS_Store
+.AppleDouble
+.LSOverride
+
+# Icon must end with two \r
+Icon
+
+# Thumbnails
+._*
+
+# Files that might appear in the root of a volume
+.DocumentRevisions-V100
+.fseventsd
+.Spotlight-V100
+.TemporaryItems
+.Trashes
+.VolumeIcon.icns
+.com.apple.timemachine.donotpresent
+
+# Directories potentially created on remote AFP share
+.AppleDB
+.AppleDesktop
+Network Trash Folder
+Temporary Items
+.apdisk

nlgeval/tests/test_nlgeval.py

@@ -103,6 +103,36 @@ def test_compute_metrics_omit(self):
         self.assertAlmostEqual(0.960771, scores['GreedyMatchingScore'], places=5)
         self.assertEqual(7, len(scores))
 
+    def test_compute_metricsa(self):
+        n = NLGEval()
+
+        # # Individual Metrics
+        scores = n.compute_individual_metrics(ref=["Chocolate , a New Way to Get Cancer "],
+                                              hyp="Chocolate , a Healthy Food")
+        print("Chocolate , a New Way to Get Cancer ", scores)
+
+        scores = n.compute_individual_metrics(ref=["Chocolate and an Interview "],
+                                              hyp="Chocolate , a Healthy Food")
+        print(scores)
+        #
+        # # Individual Metrics
+        # scores = n.compute_individual_metrics(ref=["old people are helping in fact "],
+        #                                       hyp="old people are easy to get along with ")
+        # print("old people are helping in fact ",scores)
+        #
+        # scores = n.compute_individual_metrics(ref=["old people are always happy "],
+        #                                       hyp="old people are easy to get along with ")
+        # print("old people are always happy ",scores)
+
+        # Individual Metrics
+        # scores = n.compute_individual_metrics(ref=["help us to become a shy person"],
+        #                                       hyp="block our chances for a successful life")
+        # print("help us to become a shy person", scores)
+        #
+        # scores = n.compute_individual_metrics(ref=["bring us great changes"],
+        #                                       hyp="block our chances for a successful life")
+        # print(scores)
+
     def test_compute_metrics_empty(self):
         n = NLGEval()
 
@@ -160,3 +190,11 @@ def test_compute_metrics(self):
         self.assertAlmostEqual(0.568696, scores['VectorExtremaCosineSimilarity'], places=5)
         self.assertAlmostEqual(0.784205, scores['GreedyMatchingScore'], places=5)
         self.assertEqual(12, len(scores))
+
+    def test_compute_metricss(self):
+        # The example from the README.
+        root_dir = os.path.join(os.path.dirname(__file__), '..', '..')
+        hypothesis = os.path.join(root_dir, 'examples/6.csv')
+        references = os.path.join(root_dir, 'examples/7.pt_beam_1.csv')
+        scores = nlgeval.compute_metrics(hypothesis, [references])
+        print(scores)