rename dK_dtheta > gradients_X

GPy/core/parameterization/array_core.py

@@ -27,6 +27,24 @@ class ParamList(list):
         return False
     
     pass
+class C(np.ndarray):
+    __array_priority__ = 1.
+    def __new__(cls, array):
+        obj = array.view(cls)
+        return obj
+    #def __array_finalize__(self, obj):
+    #    #print 'finalize'
+    #    return obj
+    def __array_prepare__(self, out_arr, context):
+        #print 'prepare'
+        while type(out_arr) is C:
+            out_arr = out_arr.base
+        return out_arr
+    def __array_wrap__(self, out_arr, context):
+        #print 'wrap', type(self), type(out_arr), context
+        while type(out_arr) is C:
+            out_arr = out_arr.base
+        return out_arr
 
 class ObservableArray(ListArray, Observable):
     """
@@ -35,7 +53,7 @@ class ObservableArray(ListArray, Observable):
     will be called every time this array changes. The callable
     takes exactly one argument, which is this array itself.
     """
-    __array_priority__ = 0 # Never give back Param
+    __array_priority__ = -1 # Never give back ObservableArray
     def __new__(cls, input_array):
         cls.__name__ = "ObservableArray\n     "
         obj = super(ObservableArray, cls).__new__(cls, input_array).view(cls)

GPy/core/parameterization/param.py

@@ -24,8 +24,11 @@ class Param(ObservableArray, Constrainable, Gradcheckable):
     """
     Parameter object for GPy models.
 
-    :param name:        name of the parameter to be printed
-    :param input_array: array which this parameter handles
+    :param str name:           name of the parameter to be printed
+    :param input_array:        array which this parameter handles
+    :type input_array:         numpy.ndarray
+    :param default_constraint: The default constraint for this parameter
+    :type default_constraint:  
 
     You can add/remove constraints by calling constrain on the parameter itself, e.g:
 
@@ -40,19 +43,10 @@ class Param(ObservableArray, Constrainable, Gradcheckable):
 
     See :py:class:`GPy.core.parameterized.Parameterized` for more details on constraining etc.
 
-    This ndarray can be stored in lists and checked if it is in.
-
-    >>> import numpy as np
-    >>> x = np.random.normal(size=(10,3))
-    >>> x in [[1], x, [3]]
-    True
-
-    WARNING: This overrides the functionality of x==y!!!
-    Use numpy.equal(x,y) for element-wise equality testing.
     """
-    __array_priority__ = 0 # Never give back Param
+    __array_priority__ = -1 # Never give back Param
     _fixes_ = None
-    def __new__(cls, name, input_array, *args, **kwargs):
+    def __new__(cls, name, input_array, default_constraint=None):
         obj = numpy.atleast_1d(super(Param, cls).__new__(cls, input_array=input_array))
         obj._current_slice_ = (slice(obj.shape[0]),)
         obj._realshape_ = obj.shape
@@ -66,8 +60,8 @@ class Param(ObservableArray, Constrainable, Gradcheckable):
         obj.gradient = None
         return obj
 
-    def __init__(self, name, input_array):
-        super(Param, self).__init__(name=name)
+    def __init__(self, name, input_array, default_constraint=None):
+        super(Param, self).__init__(name=name, default_constraint=default_constraint)
 
     def __array_finalize__(self, obj):
         # see InfoArray.__array_finalize__ for comments
@@ -75,6 +69,7 @@ class Param(ObservableArray, Constrainable, Gradcheckable):
         super(Param, self).__array_finalize__(obj)
         self._direct_parent_ = getattr(obj, '_direct_parent_', None)
         self._parent_index_ = getattr(obj, '_parent_index_', None)
+        self._default_constraint_ = getattr(obj, '_default_constraint_', None)
         self._current_slice_ = getattr(obj, '_current_slice_', None)
         self._tied_to_me_ = getattr(obj, '_tied_to_me_', None)
         self._tied_to_ = getattr(obj, '_tied_to_', None)
@@ -97,6 +92,7 @@ class Param(ObservableArray, Constrainable, Gradcheckable):
                             (self.name,
                              self._direct_parent_,
                              self._parent_index_,
+                             self._default_constraint_,
                              self._current_slice_,
                              self._realshape_,
                              self._realsize_,
@@ -117,6 +113,7 @@ class Param(ObservableArray, Constrainable, Gradcheckable):
         self._realsize_ = state.pop()
         self._realshape_ = state.pop()
         self._current_slice_ = state.pop()
+        self._default_constraint_ = state.pop()
         self._parent_index_ = state.pop()
         self._direct_parent_ = state.pop()
         self.name = state.pop()

GPy/core/parameterization/parameter_core.py

@@ -91,8 +91,9 @@ class Gradcheckable(Parentable):
 
 
 class Constrainable(Nameable):
-    def __init__(self, name):
+    def __init__(self, name, default_constraint=None):
         super(Constrainable,self).__init__(name)
+        self._default_constraint_ = default_constraint
     #===========================================================================
     # Fixing Parameters:
     #===========================================================================

GPy/core/parameterization/parameterized.py

@@ -171,6 +171,8 @@ class Parameterized(Constrainable, Pickleable, Observable, Gradcheckable):
             for t, ind in param._constraints_.iteritems():
                 self.constraints.add(t, ind+self._offset_for(param))
             param._constraints_.clear()
+        if param._default_constraint_ is not None:
+            self._add_constrain(param, param._default_constraint_, False)
         if self._has_fixes() and np.all(self._fixes_): # ==UNFIXED
             self._fixes_= None