diff --git a/GPy/core/parameterization/parameter_core.py b/GPy/core/parameterization/parameter_core.py
index 9cedc46d..e5652d66 100644
--- a/GPy/core/parameterization/parameter_core.py
+++ b/GPy/core/parameterization/parameter_core.py
@@ -17,7 +17,7 @@ from transformations import Logexp, NegativeLogexp, Logistic, __fixed__, FIXED,
 import numpy as np
 import re
 
-__updated__ = '2014-05-20'
+__updated__ = '2014-05-21'
 
 class HierarchyError(Exception):
     """
@@ -389,7 +389,7 @@ class Indexable(Nameable, Observable):
             self[:] = value
 
         index = self._raveled_index()
-        # reconstrained = self.unconstrain()
+        reconstrained = self.unconstrain()
         index = self._add_to_index_operations(self.constraints, index, __fixed__, warning)
         self._highest_parent_._set_fixed(self, index)
         self.notify_observers(self, None if trigger_parent else -np.inf)
diff --git a/GPy/testing/model_tests.py b/GPy/testing/model_tests.py
index 7279ef31..75c0dadc 100644
--- a/GPy/testing/model_tests.py
+++ b/GPy/testing/model_tests.py
@@ -94,22 +94,18 @@ class MiscTests(unittest.TestCase):
         np.testing.assert_equal(m.log_likelihood(), m2.log_likelihood())
 
         m.kern.lengthscale.randomize()
-        m.update_model()
         m2.kern.lengthscale = m.kern.lengthscale
         np.testing.assert_equal(m.log_likelihood(), m2.log_likelihood())
 
         m.kern.lengthscale.randomize()
-        m.update_model()
         m2['.*lengthscale'] = m.kern.lengthscale
         np.testing.assert_equal(m.log_likelihood(), m2.log_likelihood())
 
         m.kern.lengthscale.randomize()
-        m.update_model()
         m2['.*lengthscale'] = m.kern['.*lengthscale']
         np.testing.assert_equal(m.log_likelihood(), m2.log_likelihood())
 
         m.kern.lengthscale.randomize()
-        m.update_model()
         m2.kern.lengthscale = m.kern['.*lengthscale']
         np.testing.assert_equal(m.log_likelihood(), m2.log_likelihood())
 
diff --git a/GPy/testing/observable_tests.py b/GPy/testing/observable_tests.py
index c5022832..05794dc3 100644
--- a/GPy/testing/observable_tests.py
+++ b/GPy/testing/observable_tests.py
@@ -94,12 +94,12 @@ class Test(unittest.TestCase):
     def test_set_params(self):
         self.assertEqual(self.par.params_changed_count, 0, 'no params changed yet')
         self.par.param_array[:] = 1
-        self.par.update_model()
+        self.par._trigger_params_changed()
         self.assertEqual(self.par.params_changed_count, 1, 'now params changed')
         self.assertEqual(self.parent.parent_changed_count, self.par.params_changed_count)
 
         self.par.param_array[:] = 2
-        self.par.update_model()
+        self.par._trigger_params_changed()
         self.assertEqual(self.par.params_changed_count, 2, 'now params changed')
         self.assertEqual(self.parent.parent_changed_count, self.par.params_changed_count)
 
diff --git a/GPy/testing/pickle_tests.py b/GPy/testing/pickle_tests.py
index 13a67744..a98cb7f6 100644
--- a/GPy/testing/pickle_tests.py
+++ b/GPy/testing/pickle_tests.py
@@ -126,8 +126,8 @@ class Test(ListDictTestCase):
     def test_modelrecreation(self):
         par = toy_rbf_1d_50(optimize=0, plot=0)
         pcopy = GPRegression(par.X.copy(), par.Y.copy(), kernel=par.kern.copy())
-        self.assertListEqual(par.param_array.tolist(), pcopy.param_array.tolist())
-        self.assertListEqual(par.gradient_full.tolist(), pcopy.gradient_full.tolist())
+        np.testing.assert_allclose(par.param_array, pcopy.param_array)
+        np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full)
         self.assertSequenceEqual(str(par), str(pcopy))
         self.assertIsNot(par.param_array, pcopy.param_array)
         self.assertIsNot(par.gradient_full, pcopy.gradient_full)
@@ -140,7 +140,7 @@ class Test(ListDictTestCase):
             par.pickle(f)
             f.seek(0)
             pcopy = pickle.load(f)
-        self.assertListEqual(par.param_array.tolist(), pcopy.param_array.tolist())
+        np.testing.assert_allclose(par.param_array, pcopy.param_array)
         np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full)
         self.assertSequenceEqual(str(par), str(pcopy))
         self.assert_(pcopy.checkgrad())