cleanups

nifty/library/critical_filter/critical_power_curvature.py

@@ -26,7 +26,6 @@ class CriticalPowerCurvature(InvertibleOperatorMixin, EndomorphicOperator):
         self.T = T
         if preconditioner is None:
             preconditioner = self.theta.inverse_times
-        self._domain = self.theta.domain
         super(CriticalPowerCurvature, self).__init__(
                                                  inverter=inverter,
                                                  preconditioner=preconditioner,
@@ -39,7 +38,7 @@ class CriticalPowerCurvature(InvertibleOperatorMixin, EndomorphicOperator):
 
     @property
     def domain(self):
-        return self._domain
+        return self.theta.domain
 
     @property
     def self_adjoint(self):

nifty/library/log_normal_wiener_filter/log_normal_wiener_filter_curvature.py

@@ -17,12 +17,11 @@ class LogNormalWienerFilterCurvature(InvertibleOperatorMixin,
     Parameters
     ----------
     R: LinearOperator,
-        The response operator of the Wiener filter measurement.
-    N : EndomorphicOperator
-        The noise covariance.
+       The response operator of the Wiener filter measurement.
+    N: EndomorphicOperator
+       The noise covariance.
     S: DiagonalOperator,
-        The prior signal covariance
-
+       The prior signal covariance
     """
 
     def __init__(self, R, N, S, d, position, inverter, fft4exp=None, **kwargs):
@@ -31,7 +30,6 @@ class LogNormalWienerFilterCurvature(InvertibleOperatorMixin,
         self.S = S
         self.d = d
         self.position = position
-        self._domain = self.S.domain
 
         if fft4exp is None:
             self._fft = create_composed_fft_operator(self.domain,
@@ -45,7 +43,7 @@ class LogNormalWienerFilterCurvature(InvertibleOperatorMixin,
 
     @property
     def domain(self):
-        return self._domain
+        return self.S.domain
 
     @property
     def self_adjoint(self):
@@ -55,8 +53,6 @@ class LogNormalWienerFilterCurvature(InvertibleOperatorMixin,
     def unitary(self):
         return False
 
-    # ---Added properties and methods---
-
     def _times(self, x):
         part1 = self.S.inverse_times(x)
         # part2 = self._exppRNRexppd * x
@@ -72,15 +68,11 @@ class LogNormalWienerFilterCurvature(InvertibleOperatorMixin,
     def _expp_sspace(self):
         return exp(self._fft(self.position))
 
-    @property
-    @memo
-    def _expp(self):
-        return self._fft.adjoint_times(self._expp_sspace)
-
     @property
     @memo
     def _Rexppd(self):
-        return self.R(self._expp) - self.d
+        expp = self._fft.adjoint_times(self._expp_sspace)
+        return self.R(expp) - self.d
 
     @property
     @memo

nifty/library/log_normal_wiener_filter/log_normal_wiener_filter_energy.py

@@ -13,15 +13,15 @@ class LogNormalWienerFilterEnergy(Energy):
     Parameters
     ----------
     position: Field,
-        The current position.
-    d : Field,
-        the data.
-    R : Operator,
-        The response operator, describtion of the measurement process.
-    N : EndomorphicOperator,
-        The noise covariance in data space.
-    S : EndomorphicOperator,
-        The prior signal covariance in harmonic space.
+       The current position.
+    d: Field,
+       the data.
+    R: Operator,
+       The response operator, describtion of the measurement process.
+    N: EndomorphicOperator,
+       The noise covariance in data space.
+    S: EndomorphicOperator,
+       The prior signal covariance in harmonic space.
     """
 
     def __init__(self, position, d, R, N, S, inverter, fft4exp=None):
@@ -47,12 +47,12 @@ class LogNormalWienerFilterEnergy(Energy):
     @memo
     def value(self):
         return 0.5*(self.position.vdot(self._Sp) +
-                    self._Rexppd.vdot(self._NRexppd))
+                    self.curvature._Rexppd.vdot(self.curvature._NRexppd))
 
     @property
     @memo
     def gradient(self):
-        return self._Sp + self._exppRNRexppd
+        return self._Sp + self.curvature._exppRNRexppd
 
     @property
     @memo
@@ -62,22 +62,6 @@ class LogNormalWienerFilterEnergy(Energy):
                                               fft4exp=self._fft,
                                               inverter=self._inverter)
 
-    @property
-    def _expp(self):
-        return self.curvature._expp
-
-    @property
-    def _Rexppd(self):
-        return self.curvature._Rexppd
-
-    @property
-    def _NRexppd(self):
-        return self.curvature._NRexppd
-
-    @property
-    def _exppRNRexppd(self):
-        return self.curvature._exppRNRexppd
-
     @property
     @memo
     def _Sp(self):

nifty/library/wiener_filter/wiener_filter_curvature.py

@@ -10,16 +10,14 @@ class WienerFilterCurvature(InvertibleOperatorMixin, EndomorphicOperator):
     for error estimates of the posterior maps. It is the
     inverse of the propagator operator.
 
-
     Parameters
     ----------
     R: LinearOperator,
-        The response operator of the Wiener filter measurement.
-    N : EndomorphicOperator
-        The noise covariance.
+       The response operator of the Wiener filter measurement.
+    N: EndomorphicOperator
+       The noise covariance.
     S: DiagonalOperator,
-        The prior signal covariance
-
+       The prior signal covariance
     """
 
     def __init__(self, R, N, S, inverter, preconditioner=None, **kwargs):
@@ -28,7 +26,6 @@ class WienerFilterCurvature(InvertibleOperatorMixin, EndomorphicOperator):
         self.S = S
         if preconditioner is None:
             preconditioner = self.S.times
-        self._domain = self.S.domain
         super(WienerFilterCurvature, self).__init__(
                                                  inverter=inverter,
                                                  preconditioner=preconditioner,
@@ -36,7 +33,7 @@ class WienerFilterCurvature(InvertibleOperatorMixin, EndomorphicOperator):
 
     @property
     def domain(self):
-        return self._domain
+        return self.S.domain
 
     @property
     def self_adjoint(self):
@@ -46,8 +43,6 @@ class WienerFilterCurvature(InvertibleOperatorMixin, EndomorphicOperator):
     def unitary(self):
         return False
 
-    # ---Added properties and methods---
-
     def _times(self, x):
         res = self.R.adjoint_times(self.N.inverse_times(self.R(x)))
         res += self.S.inverse_times(x)

nifty/library/wiener_filter/wiener_filter_energy.py

@@ -13,14 +13,14 @@ class WienerFilterEnergy(Energy):
     ----------
     position: Field,
         The current position.
-    d : Field,
-        the data.
-    R : Operator,
-        The response operator, description of the measurement process.
-    N : EndomorphicOperator,
-        The noise covariance in data space.
-    S : EndomorphicOperator,
-        The prior signal covariance in harmonic space.
+    d: Field,
+       the data
+    R: LinearOperator,
+       The response operator, description of the measurement process.
+    N: EndomorphicOperator,
+       The noise covariance in data space.
+    S: EndomorphicOperator,
+       The prior signal covariance in harmonic space.
     """
 
     def __init__(self, position, d, R, N, S, inverter, _j=None):

nifty/probing/prober.py

@@ -31,7 +31,6 @@ class Prober(object):
 
     https://www.python.org/download/releases/2.2.3/descrintro/#cooperation
     https://rhettinger.wordpress.com/2011/05/26/super-considered-super/
-
     """
 
     def __init__(self, domain=None, probe_count=8,