Made test docstrings

piskvorky · May 26, 2016 · 2676bb6 · 2676bb6
1 parent b626326
commit 2676bb6
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Showing 2 changed files with 8 additions and 8 deletions.
diff --git a/gensim/models/normmodel.py b/gensim/models/normmodel.py
@@ -20,7 +20,7 @@ class Normmodel(interfaces.TransformationABC):
     The main methods are:
 
     1. Constructor which normalizes the terms in the given corpus document-wise.
-    2. The [] method which normalizes a simple count representation.
+    2. The normalize() method which normalizes a simple count representation.
 
     >>> norm_l2 = Normmodel(corpus)
     >>> print(norm_l2[some_doc])

diff --git a/gensim/test/test_normmodel.py b/gensim/test/test_normmodel.py
@@ -44,13 +44,13 @@ def setUp(self):
         self.model_l2 = normmodel.Normmodel(self.corpus, norm='l2')
 
     def test_tupleInput_l1(self):
-        # Test tuple input for l1 transformation
+        """Test tuple input for l1 transformation"""
         normalized = self.model_l1.normalize(self.doc)
         expected = [(1, 0.25), (5, 0.5), (8, 0.25)]
         self.assertTrue(numpy.allclose(normalized, expected))
 
     def test_sparseCSRInput_l1(self):
-        # Test sparse csr matrix input for l1 transformation
+        """Test sparse csr matrix input for l1 transformation"""
         row = numpy.array([0, 0, 1, 2, 2, 2])
         col = numpy.array([0, 2, 2, 0, 1, 2])
         data = numpy.array([1, 2, 3, 4, 5, 6])
@@ -67,7 +67,7 @@ def test_sparseCSRInput_l1(self):
         self.assertTrue(numpy.allclose(normalized.toarray(), expected))
 
     def test_numpyndarrayInput_l1(self):
-        # Test for numpy ndarray input for l1 transformation
+        """Test for numpy ndarray input for l1 transformation"""
         ndarray_matrix = numpy.array([[1, 0, 2],
                                       [0, 0, 3],
                                       [4, 5, 6]])
@@ -86,13 +86,13 @@ def test_numpyndarrayInput_l1(self):
         self.assertRaises(ValueError, lambda model, doc: model.normalize(doc), self.model_l1, [1, 2, 3])
 
     def test_tupleInput_l2(self):
-        # Test tuple input for l2 transformation
+        """Test tuple input for l2 transformation"""
         normalized = self.model_l2.normalize(self.doc)
         expected = [(1, 0.4082482904638631), (5, 0.8164965809277261), (8, 0.4082482904638631)]
         self.assertTrue(numpy.allclose(normalized, expected))
 
     def test_sparseCSRInput_l2(self):
-        # Test sparse csr matrix input for l2 transformation
+        """Test sparse csr matrix input for l2 transformation"""
         row = numpy.array([0, 0, 1, 2, 2, 2])
         col = numpy.array([0, 2, 2, 0, 1, 2])
         data = numpy.array([1, 2, 3, 4, 5, 6])
@@ -110,7 +110,7 @@ def test_sparseCSRInput_l2(self):
         self.assertTrue(numpy.allclose(normalized.toarray(), expected))
 
     def test_numpyndarrayInput_l2(self):
-        # Test for numpy ndarray input for l2 transformation
+        """Test for numpy ndarray input for l2 transformation"""
         ndarray_matrix = numpy.array([[1, 0, 2],
                                       [0, 0, 3],
                                       [4, 5, 6]])
@@ -129,7 +129,7 @@ def test_numpyndarrayInput_l2(self):
         self.assertRaises(ValueError, lambda model, doc: model.normalize(doc), self.model_l2, [1, 2, 3])
 
     def testInit(self):
-        # Test if error messages raised on unsupported norm
+        """Test if error messages raised on unsupported norm"""
         self.assertRaises(ValueError, normmodel.Normmodel, self.corpus, 'l0')
 
     def testPersistence(self):