Commit 939c6c7d by Philipp Arras

### Some pep8

parent d5563c04
Pipeline #24109 failed with stage
in 4 minutes and 10 seconds
 ... ... @@ -22,9 +22,9 @@ from ..minimization.energy import Energy class NoiseEnergy(Energy): def __init__(self, position, d, m, D, t, HarmonicTransform, Instrument, nonlinearity, alpha, q, Projection, munit=1., sunit=1., dunit=1., samples=3, sample_list=None, inverter=None): def __init__(self, position, d, m, D, t, HarmonicTransform, Instrument, nonlinearity, alpha, q, Projection, munit=1., sunit=1., dunit=1., samples=3, sample_list=None, inverter=None): super(NoiseEnergy, self).__init__(position=position) self.m = m self.D = D ... ... @@ -53,14 +53,15 @@ class NoiseEnergy(Energy): self.sample_list = sample_list self.inverter = inverter A = Projection.adjoint_times(munit * exp(.5*self.t)) # unit: munit A = Projection.adjoint_times(munit * exp(.5 * self.t)) # unit: munit map_s = self.ht(A * m) self._gradient = None for sample in self.sample_list: map_s = self.ht(A * sample) residual = self.d - self.Instrument(sunit * self.nonlinearity(map_s)) residual = self.d - \ self.Instrument(sunit * self.nonlinearity(map_s)) lh = .5 * residual.vdot(self.N.inverse_times(residual)) grad = -.5 * self.N.inverse_times(residual.conjugate() * residual) ... ... @@ -71,11 +72,13 @@ class NoiseEnergy(Energy): self._value += lh self._gradient += grad self._value *= 1./len(self.sample_list) self._value += .5 * self.position.integrate() + (self.alpha - 1.).vdot(self.position) + self.q.vdot(exp(-self.position)) self._value *= 1. / len(self.sample_list) self._value += .5 * self.position.integrate() self._value += (self.alpha - 1.).vdot(self.position) + \ self.q.vdot(exp(-self.position)) self._gradient *= 1./len(self.sample_list) self._gradient += (self.alpha-0.5) - self.q * (exp(-self.position)) self._gradient *= 1. / len(self.sample_list) self._gradient += (self.alpha - 0.5) - self.q * (exp(-self.position)) def at(self, position): return self.__class__( ... ...
 ... ... @@ -20,12 +20,15 @@ from ..operators.inversion_enabler import InversionEnabler from .response_operators import LinearizedPowerResponse def NonlinearPowerCurvature(position, HarmonicTransform, Instrument, nonlinearity, Projection, N, T, sample_list, inverter, munit=1., sunit=1.): def NonlinearPowerCurvature(position, HarmonicTransform, Instrument, nonlinearity, Projection, N, T, sample_list, inverter, munit=1., sunit=1.): result = None for sample in sample_list: LinR = LinearizedPowerResponse(Instrument, nonlinearity, HarmonicTransform, Projection, position, sample, munit, sunit) op = LinR.adjoint*N.inverse*LinR LinR = LinearizedPowerResponse(Instrument, nonlinearity, HarmonicTransform, Projection, position, sample, munit, sunit) op = LinR.adjoint * N.inverse * LinR result = op if result is None else result + op result = result*(1./len(sample_list)) + T result = result * (1. / len(sample_list)) + T return InversionEnabler(result, inverter)
 ... ... @@ -51,7 +51,9 @@ class NonlinearPowerEnergy(Energy): default : 3 """ def __init__(self, position, d, N, m, D, HarmonicTransform, Instrument, nonlinearity, Projection, sigma=0., samples=3, sample_list=None, munit=1., sunit=1., inverter=None): def __init__(self, position, d, N, m, D, HarmonicTransform, Instrument, nonlinearity, Projection, sigma=0., samples=3, sample_list=None, munit=1., sunit=1., inverter=None): super(NonlinearPowerEnergy, self).__init__(position) self.d, self.N, self.m, self.D, self.ht = d, N, m, D, HarmonicTransform self.Instrument = Instrument ... ... @@ -72,16 +74,25 @@ class NonlinearPowerEnergy(Energy): self.T = SmoothnessOperator(domain=self.position.domain[0], strength=sigma, logarithmic=True) A = Projection.adjoint_times(munit * exp(.5*position)) # unit: munit A = Projection.adjoint_times(munit * exp(.5 * position)) # unit: munit map_s = self.ht(A * m) Tpos = self.T(position) self._gradient = None for sample in self.sample_list: map_s = self.ht(A * sample) LinR = LinearizedPowerResponse(Instrument, nonlinearity, self.ht, Projection, position, sample, munit, sunit) residual = self.d - self.Instrument(sunit * self.nonlinearity(map_s)) LinR = LinearizedPowerResponse( Instrument, nonlinearity, self.ht, Projection, position, sample, munit, sunit) residual = self.d - \ self.Instrument(sunit * self.nonlinearity(map_s)) lh = 0.5 * residual.vdot(self.N.inverse_times(residual)) grad = LinR.adjoint_times(self.N.inverse_times(residual)) ... ... @@ -92,9 +103,9 @@ class NonlinearPowerEnergy(Energy): self._value += lh self._gradient += grad self._value *= 1./len(self.sample_list) self._value += 0.5*self.position.vdot(Tpos) self._gradient *= -1./len(self.sample_list) self._value *= 1. / len(self.sample_list) self._value += 0.5 * self.position.vdot(Tpos) self._gradient *= -1. / len(self.sample_list) self._gradient += Tpos def at(self, position): ... ...
 ... ... @@ -23,8 +23,8 @@ from .response_operators import LinearizedSignalResponse class NonlinearWienerFilterEnergy(Energy): def __init__(self, position, d, Instrument, nonlinearity, HarmonicTransform, power, N, S, sunit=1., inverter=None): def __init__(self, position, d, Instrument, nonlinearity, HarmonicTransform, power, N, S, sunit=1., inverter=None): super(NonlinearWienerFilterEnergy, self).__init__(position=position) self.d = d self.sunit = sunit ... ...
 ... ... @@ -19,12 +19,15 @@ from ..field import exp def LinearizedSignalResponse(Instrument, nonlinearity, HarmonicTransform, power, s, sunit): return sunit * (Instrument * nonlinearity.derivative(s) * HarmonicTransform * power) def LinearizedSignalResponse(Instrument, nonlinearity, HarmonicTransform, power, s, sunit): return sunit * (Instrument * nonlinearity.derivative(s) * HarmonicTransform * power) def LinearizedPowerResponse(Instrument, nonlinearity, HarmonicTransform, Projection, t, m, munit, sunit): power = exp(0.5*t) * munit def LinearizedPowerResponse(Instrument, nonlinearity, HarmonicTransform, Projection, t, m, munit, sunit): power = exp(0.5 * t) * munit position = HarmonicTransform(Projection.adjoint_times(power) * m) linearization = nonlinearity.derivative(position) return sunit * (0.5 * Instrument * linearization * HarmonicTransform * m * ... ...
 ... ... @@ -45,7 +45,7 @@ class WienerFilterCurvature(EndomorphicOperator): self.R = R self.N = N self.S = S op = R.adjoint*N.inverse*R + S.inverse op = R.adjoint * N.inverse * R + S.inverse self._op = InversionEnabler(op, inverter, S.times) @property ... ... @@ -91,8 +91,10 @@ class WienerFilterCurvature(EndomorphicOperator): def generate_posterior_sample2(self): power = self.S.diagonal() mock_signal = Field.from_random(random_type="normal", domain=self.S.domain, dtype=power.dtype) mock_signal = Field.from_random( random_type="normal", domain=self.S.domain, dtype=power.dtype) mock_signal *= sqrt(power) noise = self.N.diagonal() ... ...
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!