diff --git a/nifty/library/critical_filter/critical_power_curvature.py b/nifty/library/critical_filter/critical_power_curvature.py
index a401ef2fecc61b518ea13b2f4e256032e5608d0d..1b26256e9c37e62ad6bd70d8e775a266ce6bf8a2 100644
--- a/nifty/library/critical_filter/critical_power_curvature.py
+++ b/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):
diff --git a/nifty/library/log_normal_wiener_filter/log_normal_wiener_filter_curvature.py b/nifty/library/log_normal_wiener_filter/log_normal_wiener_filter_curvature.py
index d877f9125d0e40ca1cd25ed64614c7f6eecbee8d..887d0ae9d07500bedb3ba9c893a638655e7ca45a 100644
--- a/nifty/library/log_normal_wiener_filter/log_normal_wiener_filter_curvature.py
+++ b/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
diff --git a/nifty/library/log_normal_wiener_filter/log_normal_wiener_filter_energy.py b/nifty/library/log_normal_wiener_filter/log_normal_wiener_filter_energy.py
index 3a63a0803fdf2991510fa7a79fe9825c7c8d6c22..836516d4678281cd84116ba97444bf29a9c7bca6 100644
--- a/nifty/library/log_normal_wiener_filter/log_normal_wiener_filter_energy.py
+++ b/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):
diff --git a/nifty/library/wiener_filter/wiener_filter_curvature.py b/nifty/library/wiener_filter/wiener_filter_curvature.py
index 5edcd3fa2fd2eecdce086b06e5dfc6d1650d7a04..e4e1a1a871a37001115de0fbcee21a66292bff0b 100644
--- a/nifty/library/wiener_filter/wiener_filter_curvature.py
+++ b/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)
diff --git a/nifty/library/wiener_filter/wiener_filter_energy.py b/nifty/library/wiener_filter/wiener_filter_energy.py
index e8be5fe88ea4a037dfc84690071305674a2a9fef..05a36ef256f2e13687b50c8ec4b70d7f285c98a5 100644
--- a/nifty/library/wiener_filter/wiener_filter_energy.py
+++ b/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):
diff --git a/nifty/probing/prober.py b/nifty/probing/prober.py
index f9b01fb01529110600c2df253154a7de10e467cc..cc9207d5da359b47f50606b58910a512a753e58d 100644
--- a/nifty/probing/prober.py
+++ b/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,