- New function for testing Table.dlearn function in test_Table.py

Tests/test_Table.py

@@ -16,21 +16,30 @@ class TermsTestCase(unittest.TestCase):
 
     # def test_init(self):
 
+    def test_klearn(self):
+        print('A sample of size 5 is used to learn a rectangle (1-term DNF)')
+        self.T = Table(self.training_sample, cost_function='dist')
+
+        # The learning function stops when 'h' reaches k = 1 terms
+        self.T.klearn(k=1, select='f', print_on=False, print_latex=False)
+        # self.assertEqual(self.T.terms, ['1100**'])
+        self.assertEqual(self.T.terms, ['11*0**'])
+
     def test_elearn(self):
         print('A sample of size 5 is used to learn a rectangle (1-term DNF)')
         self.T = Table(self.training_sample, cost_function='dist')
 
         # The learning function stops when 'h' the number of falses positives using the testing_sample is below an error 'e'
-        self.T.elearn(self.testing_sample, e=0.1)
+        self.T.elearn(testing_sample=self.testing_sample, e=0.1, select='f', print_on=False, print_latex=False)
         # self.assertEqual(self.T.terms, ['11001*'])
         self.assertEqual(self.T.terms, ['11*0**'])
 
-    def test_klearn(self):
+    def test_dlearn(self):
         print('A sample of size 5 is used to learn a rectangle (1-term DNF)')
         self.T = Table(self.training_sample, cost_function='dist')
 
         # The learning function stops when 'h' reaches k = 1 terms
-        self.T.klearn(1)
+        self.T.dlearn(threshold=float('inf'), select='f', print_on=False, print_latex=False)
         # self.assertEqual(self.T.terms, ['1100**'])
         self.assertEqual(self.T.terms, ['11*0**'])