diff --git a/GPy/testing/likelihood_tests.py b/GPy/testing/likelihood_tests.py
index 7276e108..867851a7 100644
--- a/GPy/testing/likelihood_tests.py
+++ b/GPy/testing/likelihood_tests.py
@@ -112,7 +112,7 @@ class TestNoiseModels(object):
         self.f = None
         self.X = None
 
-    def test_noise_models(self):
+    def test_scale2_models(self):
         self.setUp()
 
         ####################################################
@@ -150,64 +150,64 @@ class TestNoiseModels(object):
         noise_models = {"Student_t_default": {
                             "model": GPy.likelihoods.StudentT(deg_free=5, sigma2=self.var),
                             "grad_params": {
-                                "names": [".*t_noise"],
+                                "names": [".*t_scale2"],
                                 "vals": [self.var],
-                                "constraints": [(".*t_noise", constrain_positive), (".*deg_free", constrain_fixed)]
-                                #"constraints": [("t_noise", constrain_positive), ("deg_free", partial(constrain_fixed, value=5))]
+                                "constraints": [(".*t_scale2", constrain_positive), (".*deg_free", constrain_fixed)]
+                                #"constraints": [("t_scale2", constrain_positive), ("deg_free", partial(constrain_fixed, value=5))]
                                 },
                             "laplace": True
                             },
                         "Student_t_1_var": {
                             "model": GPy.likelihoods.StudentT(deg_free=5, sigma2=self.var),
                             "grad_params": {
-                                "names": [".*t_noise"],
+                                "names": [".*t_scale2"],
                                 "vals": [1.0],
-                                "constraints": [(".*t_noise", constrain_positive), (".*deg_free", constrain_fixed)]
+                                "constraints": [(".*t_scale2", constrain_positive), (".*deg_free", constrain_fixed)]
                                 },
                             "laplace": True
                             },
                         "Student_t_small_deg_free": {
                             "model": GPy.likelihoods.StudentT(deg_free=1.5, sigma2=self.var),
                             "grad_params": {
-                                "names": [".*t_noise"],
+                                "names": [".*t_scale2"],
                                 "vals": [self.var],
-                                "constraints": [(".*t_noise", constrain_positive), (".*deg_free", constrain_fixed)]
+                                "constraints": [(".*t_scale2", constrain_positive), (".*deg_free", constrain_fixed)]
                                 },
                             "laplace": True
                             },
                         "Student_t_small_var": {
                             "model": GPy.likelihoods.StudentT(deg_free=5, sigma2=self.var),
                             "grad_params": {
-                                "names": [".*t_noise"],
+                                "names": [".*t_scale2"],
                                 "vals": [0.001],
-                                "constraints": [(".*t_noise", constrain_positive), (".*deg_free", constrain_fixed)]
+                                "constraints": [(".*t_scale2", constrain_positive), (".*deg_free", constrain_fixed)]
                                 },
                             "laplace": True
                             },
                         "Student_t_large_var": {
                             "model": GPy.likelihoods.StudentT(deg_free=5, sigma2=self.var),
                             "grad_params": {
-                                "names": [".*t_noise"],
+                                "names": [".*t_scale2"],
                                 "vals": [10.0],
-                                "constraints": [(".*t_noise", constrain_positive), (".*deg_free", constrain_fixed)]
+                                "constraints": [(".*t_scale2", constrain_positive), (".*deg_free", constrain_fixed)]
                                 },
                             "laplace": True
                             },
                         "Student_t_approx_gauss": {
                             "model": GPy.likelihoods.StudentT(deg_free=1000, sigma2=self.var),
                             "grad_params": {
-                                "names": [".*t_noise"],
+                                "names": [".*t_scale2"],
                                 "vals": [self.var],
-                                "constraints": [(".*t_noise", constrain_positive), (".*deg_free", constrain_fixed)]
+                                "constraints": [(".*t_scale2", constrain_positive), (".*deg_free", constrain_fixed)]
                                 },
                             "laplace": True
                             },
                         "Student_t_log": {
                             "model": GPy.likelihoods.StudentT(gp_link=link_functions.Log(), deg_free=5, sigma2=self.var),
                             "grad_params": {
-                                "names": [".*t_noise"],
+                                "names": [".*t_scale2"],
                                 "vals": [self.var],
-                                "constraints": [(".*t_noise", constrain_positive), (".*deg_free", constrain_fixed)]
+                                "constraints": [(".*t_scale2", constrain_positive), (".*deg_free", constrain_fixed)]
                                 },
                             "laplace": True
                             },