Merge branch 'working_on_demos' of gitlab.mpcdf.mpg.de:ift/NIFTy into working_on_demos

demos/critical_filtering.py

 
 from nifty import *
-
+from nifty.library.wiener_filter import WienerFilterEnergy
+from nifty.library.critical_filter import CriticalPowerEnergy
 import plotly.offline as pl
 import plotly.graph_objs as go
 

nifty/library/critical_filter/critical_power_energy.py

 from nifty.energies.energy import Energy
 from nifty.operators.smoothness_operator import SmoothnessOperator
 from nifty.library.critical_filter import CriticalPowerCurvature
-
+from nifty.energies.memoization import memo
 
 from nifty.sugar import generate_posterior_sample
 from nifty import Field, exp
@@ -77,22 +77,23 @@ class CriticalPowerEnergy(Energy):
 
     @property
     def value(self):
-        energy = exp(-self.position).vdot(self.q + self.w / 2., bare= True)
-        energy += self.position.vdot(self.alpha - 1. + self.rho / 2., bare=True)
-        energy += 0.5 * self.position.vdot(self.T(self.position))
+        energy = self._theta.vdot(Field(self.position.domain,val=1.), bare= True)
+        energy += self.position.vdot(self._rho_prime, bare=True)
+        energy += 0.5 * self.position.vdot(self._Tt)
         return energy.real
 
     @property
     def gradient(self):
-        gradient = - self.theta.weight(-1)
-        gradient += (self.alpha - 1. + self.rho / 2.).weight(-1)
-        gradient +=  self.T(self.position)
+        gradient = - self._theta.weight(-1)
+        gradient += (self._rho_prime).weight(-1)
+        gradient +=  self._Tt
         gradient.val = gradient.val.real
         return gradient
 
     @property
     def curvature(self):
-        curvature = CriticalPowerCurvature(theta=self.theta.weight(-1), T=self.T, inverter=self.inverter)
+        curvature = CriticalPowerCurvature(theta=self._theta.weight(-1), T=self.T,
+                                           inverter=self.inverter)
         return curvature
 
     def _calculate_w(self, m, D, samples):
@@ -114,4 +115,18 @@ class CriticalPowerEnergy(Energy):
         return w
 
 
+    @property
+    @memo
+    def _theta(self):
+        return (exp(-self.position) * (self.q + self.w / 2.))
+
+    @property
+    @memo
+    def _rho_prime(self):
+        return self.alpha - 1. + self.rho / 2.
+
+    @property
+    @memo
+    def _Tt(self):
+        return self.T(self.position)