print_all function removed, print m works as before.

GPy/core/model.py

@@ -31,8 +31,8 @@ class Model(Parameterized):
     def getstate(self):
         """
         Get the current state of the class.
-        
         Inherited from Parameterized, so add those parameters to the state
+
         :return: list of states from the model.
 
         """
@@ -46,7 +46,7 @@ class Model(Parameterized):
         call Parameterized with the rest of the state
 
         :param state: the state of the model.
-        :type state: list as returned from getstate.        
+        :type state: list as returned from getstate.
         """
         self.preferred_optimizer = state.pop()
         self.sampling_runs = state.pop()
@@ -397,17 +397,20 @@ class Model(Parameterized):
             return np.nan
         return 0.5 * self._get_params().size * np.log(2 * np.pi) + self.log_likelihood() - hld
 
-    def __str__(self, names=None):
-        if names is None:
-            names = self._get_print_names()
-        s = Parameterized.__str__(self, names=names).split('\n')
+    def __str__(self):
+        s = Parameterized.__str__(self).split('\n')
+        #def __str__(self, names=None):
+        #    if names is None:
+        #        names = self._get_print_names()
+        #s = Parameterized.__str__(self, names=names).split('\n')
         # add priors to the string
         if self.priors is not None:
             strs = [str(p) if p is not None else '' for p in self.priors]
         else:
-            strs = [''] * len(self._get_param_names())
-        name_indices = self.grep_param_names("|".join(names))
-        strs = np.array(strs)[name_indices]
+            strs = [''] * len(self._get_params())
+       #         strs = [''] * len(self._get_param_names())
+       #     name_indices = self.grep_param_names("|".join(names))
+       #     strs = np.array(strs)[name_indices]
         width = np.array(max([len(p) for p in strs] + [5])) + 4
 
         log_like = self.log_likelihood()

GPy/core/parameterized.py

@@ -27,9 +27,9 @@ class Parameterized(object):
 
     def _get_param_names(self):
         raise NotImplementedError, "this needs to be implemented to use the Parameterized class"
-    def _get_print_names(self):
-        """ Override for which names to print out, when using print m """
-        return self._get_param_names()
+    #def _get_print_names(self):
+    #    """ Override for which names to print out, when using print m """
+    #    return self._get_param_names()
 
     def pickle(self, filename, protocol=None):
         if protocol is None:
@@ -63,10 +63,10 @@ class Parameterized(object):
         """
         Get the current state of the class,
         here just all the indices, rest can get recomputed
-        
         For inheriting from Parameterized:
-        Allways append the state of the inherited object 
-        and call down to the inherited object in setstate!! 
+
+        Allways append the state of the inherited object
+        and call down to the inherited object in setstate!!
         """
         return [self.tied_indices,
                 self.fixed_indices,
@@ -336,26 +336,30 @@ class Parameterized(object):
         n = [nn for i, nn in enumerate(n) if not i in remove]
         return n
 
-    @property
-    def all(self):
-        return self.__str__(self._get_param_names())
+    #@property
+    #def all(self):
+    #    return self.__str__(self._get_param_names())
 
 
-    def __str__(self, names=None, nw=30):
+    #def __str__(self, names=None, nw=30):
+    def __str__(self, nw=30):
         """
         Return a string describing the parameter names and their ties and constraints
         """
-        if names is None:
-            names = self._get_print_names()
-        name_indices = self.grep_param_names("|".join(names))
+        names = self._get_param_names()
+        #if names is None:
+        #    names = self._get_print_names()
+        #name_indices = self.grep_param_names("|".join(names))
         N = len(names)
 
         if not N:
             return "This object has no free parameters."
         header = ['Name', 'Value', 'Constraints', 'Ties']
-        values = self._get_params()[name_indices] # map(str,self._get_params())
+        values = self._get_params() # map(str,self._get_params())
+        #values = self._get_params()[name_indices] # map(str,self._get_params())
         # sort out the constraints
-        constraints = [''] * len(self._get_param_names())
+        constraints = [''] * len(names)
+        #constraints = [''] * len(self._get_param_names())
         for i, t in zip(self.constrained_indices, self.constraints):
             for ii in i:
                 constraints[ii] = t.__str__()

GPy/core/sparse_gp.py

@@ -208,8 +208,8 @@ class SparseGP(GPBase):
         return sum([['iip_%i_%i' % (i, j) for j in range(self.Z.shape[1])] for i in range(self.Z.shape[0])], [])\
             + self.kern._get_param_names_transformed() + self.likelihood._get_param_names()
 
-    def _get_print_names(self):
-        return self.kern._get_param_names_transformed() + self.likelihood._get_param_names()
+    #def _get_print_names(self):
+    #    return self.kern._get_param_names_transformed() + self.likelihood._get_param_names()
 
     def update_likelihood_approximation(self):
         """