[tests] for issue ##146 and #147, fixing parameters inside __init__

GPy/testing/model_tests.py

@@ -447,6 +447,7 @@ class GradientTests(np.testing.TestCase):
         m = GPy.models.GPHeteroscedasticRegression(X, Y, kern)
         self.assertTrue(m.checkgrad())
 
+
     def test_gp_kronecker_gaussian(self):
         N1, N2 = 30, 20
         X1 = np.random.randn(N1, 1)

GPy/testing/observable_tests.py

@@ -130,7 +130,6 @@ class Test(unittest.TestCase):
         self.assertEqual(self._first, self._trigger, 'priority should be second')
         self.assertEqual(self._second, self._trigger_priority, 'priority should be second')
 
-
 if __name__ == "__main__":
     #import sys;sys.argv = ['', 'Test.testName']
     unittest.main()

GPy/testing/parameterized_tests.py

@@ -221,6 +221,31 @@ class ParameterizedTest(unittest.TestCase):
         np.testing.assert_equal(t.x.constraints[Logistic(0,1)], c[Logistic(0,1)])
         np.testing.assert_equal(t.x.constraints['fixed'], c['fixed'])
 
+    def test_parameter_modify_in_init(self):
+        class TestLikelihood(Parameterized):
+            def __init__(self, param1 = 2., param2 = 3.):
+                super(TestLikelihood, self).__init__("TestLike")
+                self.p1 = Param('param1', param1)
+                self.p2 = Param('param2', param2)
+
+                self.link_parameter(self.p1)
+                self.link_parameter(self.p2)
+
+                self.p1.fix()
+                self.p1.unfix()
+                self.p2.constrain_negative()
+                self.p1.fix()
+                self.p2.constrain_positive()
+                self.p2.fix()
+                self.p2.constrain_positive()
+
+        m = TestLikelihood()
+        print m
+        val = m.p1.values.copy()
+        self.assert_(m.p1.is_fixed)
+        self.assert_(m.constraints[GPy.constraints.Logexp()].tolist(), [1])
+        m.randomize()
+        self.assertEqual(m.p1, val)
 
     def test_printing(self):
         print self.test1