default_iteration_controller.py 3.21 KB
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# This program 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.
#
# 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 <http://www.gnu.org/licenses/>.
#
# Copyright(C) 2013-2017 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
# and financially supported by the Studienstiftung des deutschen Volkes.

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from __future__ import print_function
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from .iteration_controller import IterationController

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class DefaultIterationController(IterationController):
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    def __init__(self, tol_abs_gradnorm=None, tol_rel_gradnorm=None,
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                 tol_custom=None, convergence_level=1, iteration_limit=None,
                 name=None, verbose=None):
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        super(DefaultIterationController, self).__init__()
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        self._tol_abs_gradnorm = tol_abs_gradnorm
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        self._tol_rel_gradnorm = tol_rel_gradnorm
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        self._tol_custom = tol_custom
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        self._convergence_level = convergence_level
        self._iteration_limit = iteration_limit
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        self._name = name
        self._verbose = verbose
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    def start(self, energy, custom_measure=None):
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        self._itcount = -1
        self._ccount = 0
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        if self._tol_rel_gradnorm is not None:
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            self._tol_rel_gradnorm_now = self._tol_rel_gradnorm \
                                       * energy.gradient_norm
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        return self.check(energy, custom_measure)
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    def check(self, energy, custom_measure=None):
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        self._itcount += 1
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        inclvl = False
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        if self._tol_abs_gradnorm is not None:
            if energy.gradient_norm <= self._tol_abs_gradnorm:
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                inclvl = True
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        if self._tol_rel_gradnorm is not None:
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            if energy.gradient_norm <= self._tol_rel_gradnorm_now:
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                inclvl = True
        if self._tol_custom is not None and custom_measure is not None:
            if custom_measure <= self._tol_custom:
                inclvl = True
        if inclvl:
            self._ccount += 1
        else:
            self._ccount = max(0, self._ccount-1)
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        # report
        if self._verbose:
            msg = ""
            if self._name is not None:
                msg += self._name+":"
            msg += " Iteration #" + str(self._itcount)
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            msg += " energy=" + str(energy.value)
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            msg += " gradnorm=" + str(energy.gradient_norm)
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            if custom_measure is not None:
                msg += " custom=" + str(custom_measure)
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            msg += " clvl=" + str(self._ccount)
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            print(msg)
            # self.logger.info(msg)
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        # Are we done?
        if self._iteration_limit is not None:
            if self._itcount >= self._iteration_limit:
                return self.CONVERGED
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        if self._ccount >= self._convergence_level:
            return self.CONVERGED
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        return self.CONTINUE