fixed tests, now WienerFilterCUrvature automatically enables sampling

nifty4/library/nonlinear_wiener_filter_energy.py

@@ -24,7 +24,8 @@ from ..sugar import makeOp
 
 class NonlinearWienerFilterEnergy(Energy):
     def __init__(self, position, d, Instrument, nonlinearity, ht, power, N, S,
-                 inverter=None):
+                 inverter=None,
+                 sampling_inverter=None):
         super(NonlinearWienerFilterEnergy, self).__init__(position=position)
         self.d = d.lock()
         self.Instrument = Instrument
@@ -37,6 +38,9 @@ class NonlinearWienerFilterEnergy(Energy):
         self.N = N
         self.S = S
         self.inverter = inverter
+        if sampling_inverter==None:
+            sampling_inverter = inverter
+        self.sampling_inverter = sampling_inverter
         t1 = S.inverse_times(position)
         t2 = N.inverse_times(residual)
         self._value = 0.5 * (position.vdot(t1) + residual.vdot(t2)).real
@@ -60,4 +64,4 @@ class NonlinearWienerFilterEnergy(Energy):
     @property
     @memo
     def curvature(self):
-        return WienerFilterCurvature(self.R, self.N, self.S, self.inverter)
+        return WienerFilterCurvature(self.R, self.N, self.S, self.inverter, self.sampling_inverter)

nifty4/library/wiener_filter_curvature.py

@@ -18,9 +18,10 @@
 
 from ..operators.sandwich_operator import SandwichOperator
 from ..operators.inversion_enabler import InversionEnabler
+from ..operators.sampling_enabler import SamplingEnabler
 
 
-def WienerFilterCurvature(R, N, S, inverter):
+def WienerFilterCurvature(R, N, S, inverter, sampling_inverter=None):
     """The curvature of the WienerFilterEnergy.
 
     This operator implements the second derivative of the
@@ -38,6 +39,15 @@ def WienerFilterCurvature(R, N, S, inverter):
         The prior signal covariance
     inverter : Minimizer
         The minimizer to use during numerical inversion
+    sampling_inverter : Minimizer
+        The minimizer to use during numerical sampling
+        if None, it is not possible to draw inverse samples
+        default: None
     """
-    op = SandwichOperator.make(R, N.inverse) + S.inverse
+    M = SandwichOperator.make(R, N.inverse)
+    if sampling_inverter != None:
+        op = SamplingEnabler(M, S.inverse, sampling_inverter)
+    else:
+        op = M + S.inverse
     return InversionEnabler(op, inverter, S.inverse)
+

nifty4/library/wiener_filter_energy.py

@@ -20,7 +20,7 @@ from ..minimization.quadratic_energy import QuadraticEnergy
 from .wiener_filter_curvature import WienerFilterCurvature
 
 
-def WienerFilterEnergy(position, d, R, N, S, inverter=None):
+def WienerFilterEnergy(position, d, R, N, S, inverter=None, sampling_inverter=None):
     """The Energy for the Wiener filter.
 
     It covers the case of linear measurement with
@@ -42,7 +42,11 @@ def WienerFilterEnergy(position, d, R, N, S, inverter=None):
     inverter : Minimizer, optional
         the minimization strategy to use for operator inversion
         If None, the energy object will not support curvature computation.
+    sampling_inverter : Minimizer, optional
+        The minimizer to use during numerical sampling
+        if None, it is not possible to draw inverse samples
+        default: None
     """
-    op = WienerFilterCurvature(R, N, S, inverter)
+    op = WienerFilterCurvature(R, N, S, inverter, sampling_inverter)
     vec = R.adjoint_times(N.inverse_times(d))
     return QuadraticEnergy(position, op, vec)