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preconditioner.py
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preconditioner.py
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#!/usr/bin/env python3
## vi: tabstop=4 shiftwidth=4 softtabstop=4 expandtab
## ---------------------------------------------------------------------
##
## Copyright (C) 2018 by the adcc authors
##
## This file is part of adcc.
##
## adcc is free software: you can redistribute it and/or modify
## 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.
##
## adcc 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 adcc. If not, see <http://www.gnu.org/licenses/>.
##
## ---------------------------------------------------------------------
import numpy as np
from adcc.AdcMatrix import AdcMatrixlike
from adcc.functions import divide, empty_like, ones_like
from adcc.AmplitudeVector import AmplitudeVector
class PreconditionerIdentity:
"""
Preconditioner, which does absolutely nothing
"""
def apply(self, invecs, outvecs=None):
"""
Apply preconditioner to a bunch of input vectors
"""
if outvecs is not None:
invecs.copy_to(outvecs)
return invecs
def __matmul__(self, x):
return x
class JacobiPreconditioner:
"""
Jacobi-type preconditioner
Represents the application of (D - σ I)^{-1}, where
D is the diagonal of the adcmatrix.
"""
def __init__(self, adcmatrix, shifts=0.0):
if not isinstance(adcmatrix, AdcMatrixlike):
raise TypeError("Only an AdcMatrixlike may be used with this "
"preconditioner for now.")
self.diagonal = AmplitudeVector(*tuple(
adcmatrix.diagonal(block) for block in adcmatrix.blocks
))
self.shifts = shifts
def update_shifts(self, shifts):
"""
Update the shift value or values applied to the diagonal.
If this is a single value it will be applied to all
vectors simultaneously. If it is multiple values,
then each value will be applied only to one
of the passed vectors.
"""
self.shifts = shifts
# TODO: this seems to be implemented?
# if isinstance(shifts, (float, np.number)):
# raise NotImplementedError("Using only a single common shift is "
# "not implemented at the moment.")
def __compute_single_matvec(self, shift, invec, outvec):
eps = 1e-6 # Epsilon factor to make sure that 1 / (shift - diagonal)
# does not become ill-conditioned as soon as the shift
# approaches the actual diagonal values (which are the
# eigenvalues for the ADC(2) doubles part if the coupling
# block are absent)
shifted_diagonal = (self.diagonal
- (shift - eps) * ones_like(self.diagonal))
divide(invec, shifted_diagonal, outvec)
return outvec
def apply(self, invecs, outvecs=None):
if isinstance(invecs, AmplitudeVector):
if outvecs is None:
outvecs = empty_like(invecs)
if not isinstance(self.shifts, (float, np.number)):
raise TypeError("Can only apply JacobiPreconditioner "
"to a single vector if shifts is "
"only a single number.")
return self.__compute_single_matvec(self.shifts, invecs, outvecs)
elif isinstance(invecs, list):
if outvecs is None:
outvecs = [empty_like(v) for v in invecs]
if len(self.shifts) != len(invecs):
raise ValueError("Number of vectors passed does not agree "
"with number of shifts stored inside "
"precoditioner. Update using the "
"'update_shifts' method.")
for i in range(len(invecs)):
self.__compute_single_matvec(self.shifts[i],
invecs[i], outvecs[i])
return outvecs
else:
raise TypeError("Input type not understood: " + str(type(invecs)))
def __matmul__(self, invecs):
return self.apply(invecs)
# __matvec__