tweak and remove some code that would need more adjustments

nifty/library/nonlinear_signal_energy.py

@@ -45,9 +45,7 @@ class NonlinearWienerFilterEnergy(Energy):
     @property
     @memo
     def gradient(self):
-        gradient = self._t1.copy()
-        gradient -= self.LinearizedResponse.adjoint_times(self._t2)
-        return gradient
+        return self._t1 - self.LinearizedResponse.adjoint_times(self._t2)
 
     @property
     @memo

nifty/library/nonlinearities.py

-from numpy import logical_and, where
-from .. import Field, exp, tanh
+from ..field import Field, exp, tanh
 
 
-class Linear:
+class Linear(object):
     def __call__(self, x):
         return x
 
     def derivative(self, x):
-        return 1
+        return Field.ones_like(x)
 
 
 class Exponential(object):
@@ -26,55 +25,9 @@ class Tanh(object):
         return (1. - tanh(x)**2)
 
 
-class PositiveTanh:
+class PositiveTanh(object):
     def __call__(self, x):
         return 0.5 * tanh(x) + 0.5
 
     def derivative(self, x):
         return 0.5 * (1. - tanh(x)**2)
-
-
-class LinearThenQuadraticWithJump(object):
-    def __call__(self, x):
-        dom = x.domain
-        x = x.copy().val.get_full_data()
-        cond = where(x > 0.)
-        not_cond = where(x <= 0.)
-        x[cond] **= 2
-        x[not_cond] -= 1
-        return Field(domain=dom, val=x)
-
-    def derivative(self, x):
-        dom = x.domain
-        x = x.copy().val.get_full_data()
-        cond = where(x > 0.)
-        not_cond = where(x <= 0.)
-        x[cond] *= 2
-        x[not_cond] = 1
-        return Field(domain=dom, val=x)
-
-
-class ReallyStupidNonlinearity(object):
-    def __call__(self, x):
-        dom = x.domain
-        x = x.copy().val.get_full_data()
-        cond1 = where(logical_and(x > 0., x < .5))
-        cond2 = where(x >= .5)
-        not_cond = where(x <= 0.)
-        x[cond2] -= 0.5
-        x[cond2] **= 2
-        x[cond1] = 0.
-        x[not_cond] -= 1
-        return Field(domain=dom, val=x)
-
-    def derivative(self, x):
-        dom = x.domain
-        x = x.copy().val.get_full_data()
-        cond1 = where(logical_and(x > 0., x < 0.5))
-        cond2 = where(x > .5)
-        not_cond = where(x <= 0.)
-        x[cond2] -= 0.5
-        x[cond2] *= 2
-        x[cond1] = 0.
-        x[not_cond] = 1
-        return Field(domain=dom, val=x)

nifty/library/response_operators.py

-from .. import exp
+from ..field import exp
 from ..operators.linear_operator import LinearOperator
 
 
 class LinearizedSignalResponse(LinearOperator):
     def __init__(self, Instrument, nonlinearity, FFT, power, m):
         super(LinearizedSignalResponse, self).__init__()
-        self._target = Instrument.target
-        self._domain = FFT.target
         self.Instrument = Instrument
         self.FFT = FFT
         self.power = power
-        position = FFT.adjoint_times(self.power * m)
+        position = FFT.adjoint_times(self.power*m)
         self.linearization = nonlinearity.derivative(position)
 
     def _times(self, x):
-        return self.Instrument(self.linearization * self.FFT.adjoint_times(self.power * x))
+        tmp = self.FFT.adjoint_times(self.power*x)
+        tmp *= self.linearization
+        return self.Instrument(tmp)
 
     def _adjoint_times(self, x):
-        return self.power * self.FFT(self.linearization * self.Instrument.adjoint_times(x))
+        tmp = self.Instrument.adjoint_times(x)
+        tmp *= self.linearization
+        tmp = self.FFT(tmp)
+        tmp *= self.power
+        return tmp
 
     @property
     def domain(self):
-        return self._domain
+        return self.FFT.target
 
     @property
     def target(self):
-        return self._target
+        return self.Instrument.target
 
     @property
     def unitary(self):
@@ -35,8 +39,6 @@ class LinearizedSignalResponse(LinearOperator):
 class LinearizedPowerResponse(LinearOperator):
     def __init__(self, Instrument, nonlinearity, FFT, Projection, t, m):
         super(LinearizedPowerResponse, self).__init__()
-        self._target = Instrument.target
-        self._domain = t.domain
         self.Instrument = Instrument
         self.FFT = FFT
         self.Projection = Projection
@@ -47,22 +49,31 @@ class LinearizedPowerResponse(LinearOperator):
         self.linearization = nonlinearity.derivative(position)
 
     def _times(self, x):
-        return 0.5 * self.Instrument(self.linearization
-                                     * self.FFT.adjoint_times(self.m
-                                                              * self.Projection.adjoint_times(self.power * x)))
+        tmp = self.Projection.adjoint_times(self.power*x)
+        tmp *= self.m
+        tmp = self.FFT.adjoint_times(tmp)
+        tmp *= self.linearization
+        tmp = self.Instrument(tmp)
+        tmp *= 0.5
+        return tmp
 
     def _adjoint_times(self, x):
-        return 0.5 * self.power * self.Projection(self.m.conjugate()
-                                                  * self.FFT(self.linearization
-                                                             * self.Instrument.adjoint_times(x)))  # .weight(-1)
+        tmp = self.Instrument.adjoint_times(x)
+        tmp *= self.linearization
+        tmp = self.FFT(tmp)
+        tmp *= self.m.conjugate()
+        tmp = self.Projection(tmp)
+        tmp *= self.power
+        tmp *= 0.5
+        return tmp
 
     @property
     def domain(self):
-        return self._domain
+        return self.power.domain
 
     @property
     def target(self):
-        return self._target
+        return self.Instrument.target
 
     @property
     def unitary(self):