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observer pattern has a handle to trigger only > min_priority observers

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Max Zwiessele 2014-02-28 11:33:31 +00:00
parent 058ab679e7
commit 2771e3f71f
8 changed files with 181 additions and 90 deletions
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39
GPy/core/parameterization/parameterized.py
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@ -58,6 +58,7 @@ class Parameterized(Parameterizable, Pickleable, Gradcheckable):
self._in_init_ = True
self._parameters_ = ParamList()
self.size = sum(p.size for p in self._parameters_)
self.add_observer(self, self._parameters_changed_notification, -100)
if not self._has_fixes():
self._fixes_ = None
self._param_slices_ = []
@ -65,7 +66,7 @@ class Parameterized(Parameterizable, Pickleable, Gradcheckable):
del self._in_init_
def build_pydot(self, G=None):
import pydot
import pydot # @UnresolvedImport
iamroot = False
if G is None:
G = pydot.Dot(graph_type='digraph')
@ -116,7 +117,7 @@ class Parameterized(Parameterizable, Pickleable, Gradcheckable):
self.constraints.update(param.constraints, start)
self.priors.update(param.priors, start)
self._parameters_.insert(index, param)
param.add_observer(self, self._pass_through_notify, -1)
param.add_observer(self, self._pass_through_notify_observers, -np.inf)
self.size += param.size
else:
raise RuntimeError, """Parameter exists already added and no copy made"""
@ -173,9 +174,10 @@ class Parameterized(Parameterizable, Pickleable, Gradcheckable):
#===========================================================================
# notification system
#===========================================================================
def _pass_through_notify(self, which):
def _parameters_changed_notification(self, which):
self.parameters_changed()
def _pass_through_notify_observers(self, which):
self._notify_observers(which)
#===========================================================================
# Pickling operations
#===========================================================================
@ -244,32 +246,7 @@ class Parameterized(Parameterizable, Pickleable, Gradcheckable):
g[self._offset_for(p) + numpy.array(list(i))] += g[self._raveled_index_for(t)]
if self._has_fixes(): return g[self._fixes_]
return g
#===========================================================================
# Optimization handles:
#===========================================================================
def _get_param_names(self):
n = numpy.array([p.hirarchy_name() + '[' + str(i) + ']' for p in self.flattened_parameters for i in p._indices()])
return n
def _get_param_names_transformed(self):
n = self._get_param_names()
if self._has_fixes():
return n[self._fixes_]
return n
def _get_params_transformed(self):
# transformed parameters (apply transformation rules)
p = self._get_params()
[numpy.put(p, ind, c.finv(p[ind])) for c, ind in self.constraints.iteritems() if c != __fixed__]
if self._has_fixes():
return p[self._fixes_]
return p
def _set_params_transformed(self, p):
# inverse apply transformations for parameters and set the resulting parameters
self._set_params(self._untransform_params(p))
def _untransform_params(self, p):
p = p.copy()
if self._has_fixes(): tmp = self._get_params(); tmp[self._fixes_] = p; p = tmp; del tmp
[numpy.put(p, ind, c.f(p[ind])) for c, ind in self.constraints.iteritems() if c != __fixed__]
return p
#===========================================================================
# Indexable Handling
#===========================================================================
@ -304,6 +281,7 @@ class Parameterized(Parameterizable, Pickleable, Gradcheckable):
this is not in the global view of things!
"""
return numpy.r_[:self.size]
#===========================================================================
# Fixing parameters:
#===========================================================================
@ -311,6 +289,7 @@ class Parameterized(Parameterizable, Pickleable, Gradcheckable):
if self._has_fixes():
return self._fixes_[self._raveled_index_for(param)]
return numpy.ones(self.size, dtype=bool)[self._raveled_index_for(param)]
#===========================================================================
# Convenience for fixed, tied checking of param:
#===========================================================================