Serialization: Add docstrings

GPy/likelihoods/bernoulli.py

@@ -30,7 +30,15 @@ class Bernoulli(Likelihood):
             self.log_concave = True
 
     def to_dict(self):
-        input_dict = super(Bernoulli, self)._to_dict()
+        """
+        Convert the object into a json serializable dictionary.
+
+        Note: It uses the private method _save_to_input_dict of the parent.
+
+        :return dict: json serializable dictionary containing the needed information to instantiate the object
+        """
+
+        input_dict = super(Bernoulli, self)._save_to_input_dict()
         input_dict["class"] = "GPy.likelihoods.Bernoulli"
         return input_dict
 

GPy/likelihoods/gaussian.py

@@ -47,7 +47,15 @@ class Gaussian(Likelihood):
             self.log_concave = True
 
     def to_dict(self):
-        input_dict = super(Gaussian, self)._to_dict()
+        """
+        Convert the object into a json serializable dictionary.
+
+        Note: It uses the private method _save_to_input_dict of the parent.
+
+        :return dict: json serializable dictionary containing the needed information to instantiate the object
+        """
+
+        input_dict = super(Gaussian, self)._save_to_input_dict()
         input_dict["class"] = "GPy.likelihoods.Gaussian"
         input_dict["variance"] = self.variance.values.tolist()
         return input_dict

GPy/likelihoods/likelihood.py

@@ -49,7 +49,7 @@ class Likelihood(Parameterized):
     def to_dict(self):
         raise NotImplementedError
 
-    def _to_dict(self):
+    def _save_to_input_dict(self):
         input_dict = {}
         input_dict["name"] = self.name
         input_dict["gp_link_dict"] = self.gp_link.to_dict()
@@ -57,6 +57,18 @@ class Likelihood(Parameterized):
 
     @staticmethod
     def from_dict(input_dict):
+        """
+        Instantiate an object of a derived class using the information
+        in input_dict (built by the to_dict method of the derived class).
+        More specifically, after reading the derived class from input_dict,
+        it calls the method _build_from_input_dict of the derived class.
+        Note: This method should not be overrided in the derived class. In case
+        it is needed, please override _build_from_input_dict instate.
+
+        :param dict input_dict: Dictionary with all the information needed to
+           instantiate the object.
+        """
+
         import copy
         input_dict = copy.deepcopy(input_dict)
         likelihood_class = input_dict.pop('class')
@@ -64,10 +76,10 @@ class Likelihood(Parameterized):
         name = input_dict.pop('name')
         import GPy
         likelihood_class = eval(likelihood_class)
-        return likelihood_class._from_dict(likelihood_class, input_dict)
+        return likelihood_class._build_from_input_dict(likelihood_class, input_dict)
 
     @staticmethod
-    def _from_dict(likelihood_class, input_dict):
+    def _build_from_input_dict(likelihood_class, input_dict):
         import copy
         input_dict = copy.deepcopy(input_dict)
         gp_link_dict = input_dict.pop('gp_link_dict')

GPy/likelihoods/link_functions.py

@@ -46,20 +46,32 @@ class GPTransformation(object):
     def to_dict(self):
         raise NotImplementedError
 
-    def _to_dict(self):
+    def _save_to_input_dict(self):
         return {}
 
     @staticmethod
     def from_dict(input_dict):
+        """
+        Instantiate an object of a derived class using the information
+        in input_dict (built by the to_dict method of the derived class).
+        More specifically, after reading the derived class from input_dict,
+        it calls the method _build_from_input_dict of the derived class.
+        Note: This method should not be overrided in the derived class. In case
+        it is needed, please override _build_from_input_dict instate.
+
+        :param dict input_dict: Dictionary with all the information needed to
+           instantiate the object.
+        """
+
         import copy
         input_dict = copy.deepcopy(input_dict)
         link_class = input_dict.pop('class')
         import GPy
         link_class = eval(link_class)
-        return link_class._from_dict(link_class, input_dict)
+        return link_class._build_from_input_dict(link_class, input_dict)
 
     @staticmethod
-    def _from_dict(link_class, input_dict):
+    def _build_from_input_dict(link_class, input_dict):
         return link_class(**input_dict)
 
 class Identity(GPTransformation):
@@ -82,7 +94,15 @@ class Identity(GPTransformation):
         return np.zeros_like(f)
 
     def to_dict(self):
-        input_dict = super(Identity, self)._to_dict()
+        """
+        Convert the object into a json serializable dictionary.
+
+        Note: It uses the private method _save_to_input_dict of the parent.
+
+        :return dict: json serializable dictionary containing the needed information to instantiate the object
+        """
+
+        input_dict = super(Identity, self)._save_to_input_dict()
         input_dict["class"] = "GPy.likelihoods.link_functions.Identity"
         return input_dict
 
@@ -106,7 +126,15 @@ class Probit(GPTransformation):
         return (safe_square(f)-1.)*std_norm_pdf(f)
 
     def to_dict(self):
-        input_dict = super(Probit, self)._to_dict()
+        """
+        Convert the object into a json serializable dictionary.
+
+        Note: It uses the private method _save_to_input_dict of the parent.
+
+        :return dict: json serializable dictionary containing the needed information to instantiate the object
+        """
+
+        input_dict = super(Probit, self)._save_to_input_dict()
         input_dict["class"] = "GPy.likelihoods.link_functions.Probit"
         return input_dict