Commit cc38c3de authored by Philipp Arras's avatar Philipp Arras
Browse files

Cosmetics

parent 938935b9
......@@ -12,7 +12,7 @@
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# Copyright(C) 2013-2021 Max-Planck-Society
# Authors: Philipp Frank
# Authors: Philipp Frank, Philipp Arras
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
......
......@@ -235,14 +235,18 @@ class VariableCovarianceGaussianEnergy(LikelihoodOperator):
return None, res
def get_transformation(self):
"""Note that for the metric of a `VariableCovarianceGaussianEnergy` no
global transformation to Euclidean space exists. A local approximation
invoking the residual is used instead.
"""
Note
----
For `VariableCovarianceGaussianEnergy`, a global transformation to
Euclidean space does not exist. A local approximation invoking the
residual is used instead.
"""
r = FieldAdapter(self._domain[self._kr], self._kr)
ivar = FieldAdapter(self._domain[self._kr], self._ki).real
sc = 1. if self._cplx else 0.5
return self._dt, r.adjoint@(ivar.ptw('sqrt')*r) + ivar.adjoint@(sc*ivar.ptw('log'))
f = r.adjoint @ (ivar.sqrt()*r) + ivar.adjoint @ (sc*ivar.log())
return self._dt, f
class _SpecialGammaEnergy(LikelihoodOperator):
......@@ -267,6 +271,7 @@ class _SpecialGammaEnergy(LikelihoodOperator):
sc = 1. if self._cplx else np.sqrt(0.5)
return self._dt, sc*ScalingOperator(self._domain, 1.).ptw('log')
class GaussianEnergy(LikelihoodOperator):
"""Computes a negative-log Gaussian.
......@@ -400,7 +405,8 @@ class PoissonianEnergy(LikelihoodOperator):
return res.add_metric(self.get_metric_at(x.val))
def get_transformation(self):
return np.float64, 2.*ScalingOperator(self._domain,1.).sqrt()
return np.float64, 2.*ScalingOperator(self._domain, 1.).sqrt()
class InverseGammaLikelihood(LikelihoodOperator):
"""Computes the negative log-likelihood of the inverse gamma distribution.
......@@ -450,6 +456,7 @@ class InverseGammaLikelihood(LikelihoodOperator):
res = makeOp(fact)@ScalingOperator(self._domain,1.).ptw('log')
return self._sampling_dtype, res
class StudentTEnergy(LikelihoodOperator):
"""Computes likelihood energy corresponding to Student's t-distribution.
......@@ -487,6 +494,7 @@ class StudentTEnergy(LikelihoodOperator):
th = full(self._domain, self._theta)
return np.float64, makeOp(((th+1)/(th+3)).ptw('sqrt'))
class BernoulliEnergy(LikelihoodOperator):
"""Computes likelihood energy of expected event frequency constrained by
event data.
......@@ -525,6 +533,7 @@ class BernoulliEnergy(LikelihoodOperator):
res = res * ScalingOperator(self._domain,1).ptw('reciprocal')
return np.float64, -2.*res.ptw('sqrt').ptw('arctan')
class StandardHamiltonian(EnergyOperator):
"""Computes an information Hamiltonian in its standard form, i.e. with the
prior being a Gaussian with unit covariance.
......@@ -572,7 +581,8 @@ class StandardHamiltonian(EnergyOperator):
if not x.want_metric or self._ic_samp is None:
return (self._lh + self._prior)(x)
lhx, prx = self._lh(x), self._prior(x)
return (lhx+prx).add_metric(SamplingEnabler(lhx.metric, prx.metric, self._ic_samp))
met = SamplingEnabler(lhx.metric, prx.metric, self._ic_samp)
return (lhx+prx).add_metric(met)
def __repr__(self):
subs = 'Likelihood:\n{}'.format(utilities.indent(self._lh.__repr__()))
......
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