Merge pull request #59 from GPflow/remove_default_params

Removal of default params

Author: javdrher

GPflowOpt/acquisition/acquisition.py

@@ -49,7 +49,6 @@ def __init__(self, models=[], optimize_restarts=5):
         """
         super(Acquisition, self).__init__()
         self._models = ParamList([DataScaler(m) for m in np.atleast_1d(models).tolist()])
-        self._default_params = list(map(lambda m: m.get_free_state(), self._models))
 
         assert (optimize_restarts >= 0)
         self.optimize_restarts = optimize_restarts
@@ -72,10 +71,11 @@ def _optimize_models(self):
         if self.optimize_restarts == 0:
             return
 
-        for model, hypers in zip(self.models, self._default_params):
+        for model in self.models:
             runs = []
             for i in range(self.optimize_restarts):
-                model.randomize() if i > 0 else model.set_state(hypers)
+                if i > 0:
+                    model.randomize()
                 try:
                     result = model.optimize()
                     runs.append(result)

testing/test_acquisition.py

@@ -115,10 +115,6 @@ def test_data_indices(self):
     def test_object_integrity(self):
         self.assertEqual(len(self.acquisition.models), 1, msg="Model list has incorrect length.")
         self.assertEqual(self.acquisition.models[0], self.model, msg="Incorrect model stored in ExpectedImprovement")
-        self.assertEqual(len(self.acquisition._default_params), 1)
-        self.assertTrue(
-            np.allclose(np.sort(self.acquisition._default_params[0]), np.sort(np.array([0.5413] * 4)), atol=1e-2),
-            msg="Initial hypers improperly stored")
 
     def test_enable_scaling(self):
         self.assertFalse(
@@ -246,10 +242,6 @@ def test_object_integrity(self):
         self.assertEqual(len(self.acquisition.models), 2, msg="Model list has incorrect length.")
         for m1, m2 in zip(self.acquisition.models, self.model):
             self.assertEqual(m1, m2, msg="Incorrect model stored in ExpectedImprovement")
-        self.assertEqual(len(self.acquisition._default_params), 2)
-        for i in np.arange(2):
-            self.assertTrue(np.allclose(np.sort(self.acquisition._default_params[i]), np.sort(np.array([0.5413] * 3)),
-                                        atol=1e-2), msg="Initial hypers improperly stored")
 
     def test_hvpoi_validity(self):
         scores = self.acquisition.evaluate(self.candidates)
@@ -266,7 +258,6 @@ def test_object_integrity(self):
         for oper in self.acquisition.operands:
             self.assertTrue(isinstance(oper, GPflowOpt.acquisition.Acquisition),
                             msg="All operands should be an acquisition object")
-        self.assertEqual(len(self.acquisition._default_params), 0)
         self.assertListEqual(self.acquisition.models.sorted_params, self.models)
 
     def test_data(self):