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# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
# Copyright(C) 2013-2018 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
# and financially supported by the Studienstiftung des deutschen Volkes.
from ..operators.sandwich_operator import SandwichOperator
from ..operators.inversion_enabler import InversionEnabler
from ..operators.sampling_enabler import SamplingEnabler
def WienerFilterCurvature(R, N, S, inverter, sampling_inverter=None):
"""The curvature of the WienerFilterEnergy.
This operator implements the second derivative of the
WienerFilterEnergy used in some minimization algorithms or
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.
S : DiagonalOperator
The prior signal covariance
inverter : Minimizer
The minimizer to use during numerical inversion
sampling_inverter : Minimizer
The minimizer to use during numerical sampling
if None, it is not possible to draw inverse samples
default: None
"""
M = SandwichOperator.make(R, N.inverse)
if sampling_inverter is not None:
op = SamplingEnabler(M, S.inverse, sampling_inverter, S.inverse)
else:
op = M + S.inverse
return InversionEnabler(op, inverter, S.inverse)