getstate > _getstate and setstate > _setstate

GPy/models/bayesian_gplvm.py

@@ -51,17 +51,17 @@ class BayesianGPLVM(SparseGP, GPLVM):
         self.add_parameter(self.q, gradient=self._dbound_dmuS, index=0)
         self.ensure_default_constraints()
 
-    def getstate(self):
+    def _getstate(self):
         """
         Get the current state of the class,
         here just all the indices, rest can get recomputed
         """
-        return SparseGP.getstate(self) + [self.init]
+        return SparseGP._getstate(self) + [self.init]
 
-    def setstate(self, state):
+    def _setstate(self, state):
         self._const_jitter = None
         self.init = state.pop()
-        SparseGP.setstate(self, state)
+        SparseGP._setstate(self, state)
 
 #     def _get_param_names(self):
 #         X_names = sum([['X_%i_%i' % (n, q) for q in range(self.input_dim)] for n in range(self.num_data)], [])

GPy/models/gp_regression.py

@@ -30,8 +30,8 @@ class GPRegression(GP):
 
         super(GPRegression, self).__init__(X, Y, kernel, likelihood, name='gp_regression')
 
-    def getstate(self):
-        return GP.getstate(self)
+    def _getstate(self):
+        return GP._getstate(self)
 
-    def setstate(self, state):
-        return GP.setstate(self, state)
+    def _setstate(self, state):
+        return GP._setstate(self, state)

GPy/models/gplvm.py

@@ -42,11 +42,11 @@ class GPLVM(GP):
             Xr[:PC.shape[0], :PC.shape[1]] = PC
         return Xr
 
-    def getstate(self):
-        return GP.getstate(self)
+    def _getstate(self):
+        return GP._getstate(self)
 
-    def setstate(self, state):
-        GP.setstate(self, state)
+    def _setstate(self, state):
+        GP._setstate(self, state)
 
 #     def _get_param_names(self):
 #         return sum([['X_%i_%i' % (n, q) for q in range(self.input_dim)] for n in range(self.num_data)], []) + GP._get_param_names(self)

GPy/models/mrd.py

@@ -79,8 +79,8 @@ class MRD(Model):
         Model.__init__(self)
         self.ensure_default_constraints()
 
-    def getstate(self):
-        return Model.getstate(self) + [self.names,
+    def _getstate(self):
+        return Model._getstate(self) + [self.names,
                 self.bgplvms,
                 self.gref,
                 self.nparams,
@@ -90,7 +90,7 @@ class MRD(Model):
                 self.NQ,
                 self.MQ]
 
-    def setstate(self, state):
+    def _setstate(self, state):
         self.MQ = state.pop()
         self.NQ = state.pop()
         self.num_data = state.pop()
@@ -100,7 +100,7 @@ class MRD(Model):
         self.gref = state.pop()
         self.bgplvms = state.pop()
         self.names = state.pop()
-        Model.setstate(self, state)
+        Model._setstate(self, state)
 
     @property
     def X(self):

GPy/models/sparse_gp_classification.py

@@ -46,11 +46,11 @@ class SparseGPClassification(SparseGP):
         SparseGP.__init__(self, X, likelihood, kernel, Z=Z, normalize_X=normalize_X)
         self.ensure_default_constraints()
 
-    def getstate(self):
-        return SparseGP.getstate(self)
+    def _getstate(self):
+        return SparseGP._getstate(self)
 
 
-    def setstate(self, state):
-        return SparseGP.setstate(self, state)
+    def _setstate(self, state):
+        return SparseGP._setstate(self, state)
 
     pass

GPy/models/sparse_gp_regression.py

@@ -49,11 +49,11 @@ class SparseGPRegression(SparseGP):
         self.ensure_default_constraints()
         pass
 
-    def getstate(self):
-        return SparseGP.getstate(self)
+    def _getstate(self):
+        return SparseGP._getstate(self)
 
 
-    def setstate(self, state):
-        return SparseGP.setstate(self, state)
+    def _setstate(self, state):
+        return SparseGP._setstate(self, state)
 
     pass

GPy/models/sparse_gplvm.py

@@ -28,12 +28,12 @@ class SparseGPLVM(SparseGPRegression, GPLVM):
         SparseGPRegression.__init__(self, X, Y, kernel=kernel, num_inducing=num_inducing)
         self.ensure_default_constraints()
 
-    def getstate(self):
-        return SparseGPRegression.getstate(self)
+    def _getstate(self):
+        return SparseGPRegression._getstate(self)
 
 
-    def setstate(self, state):
-        return SparseGPRegression.setstate(self, state)
+    def _setstate(self, state):
+        return SparseGPRegression._setstate(self, state)
 
 
     def _get_param_names(self):

GPy/models/svigp_regression.py

@@ -43,10 +43,10 @@ class SVIGPRegression(SVIGP):
         SVIGP.__init__(self, X, likelihood, kernel, Z, q_u=q_u, batchsize=batchsize)
         self.load_batch()
 
-    def getstate(self):
-        return GPBase.getstate(self)
+    def _getstate(self):
+        return GPBase._getstate(self)
 
 
-    def setstate(self, state):
-        return GPBase.setstate(self, state)
+    def _setstate(self, state):
+        return GPBase._setstate(self, state)
 

GPy/models/warped_gp.py

@@ -30,12 +30,12 @@ class WarpedGP(GP):
         GP.__init__(self, X, likelihood, kernel, normalize_X=normalize_X)
         self._set_params(self._get_params())
 
-    def getstate(self):
-        return GP.getstate(self)
+    def _getstate(self):
+        return GP._getstate(self)
 
 
-    def setstate(self, state):
-        return GP.setstate(self, state)
+    def _setstate(self, state):
+        return GP._setstate(self, state)
 
 
     def _scale_data(self, Y):