relaxed_newton.py 1.59 KB
Newer Older
1
2
3
4
5
6
7
8
9
10
11
12
# 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/>.
Theo Steininger's avatar
Theo Steininger committed
13
#
Martin Reinecke's avatar
Martin Reinecke committed
14
# Copyright(C) 2013-2018 Max-Planck-Society
Theo Steininger's avatar
Theo Steininger committed
15
16
17
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
# and financially supported by the Studienstiftung des deutschen Volkes.
18

19
from .descent_minimizer import DescentMinimizer
Martin Reinecke's avatar
Martin Reinecke committed
20
from .line_search_strong_wolfe import LineSearchStrongWolfe
21
22


23
class RelaxedNewton(DescentMinimizer):
Martin Reinecke's avatar
Martin Reinecke committed
24
25
26
27
28
    """ Calculates the descent direction according to a Newton scheme.

    The descent direction is determined by weighting the gradient at the
    current parameter position with the inverse local curvature.
    """
Martin Reinecke's avatar
adjust    
Martin Reinecke committed
29
    def __init__(self, controller, line_searcher=LineSearchStrongWolfe()):
Martin Reinecke's avatar
tweaks    
Martin Reinecke committed
30
31
        super(RelaxedNewton, self).__init__(controller=controller,
                                            line_searcher=line_searcher)
Martin Reinecke's avatar
Martin Reinecke committed
32
        # FIXME: this does not look idiomatic
33
        self.line_searcher.preferred_initial_step_size = 1.
34

35
36
    def get_descent_direction(self, energy):
        return -energy.curvature.inverse_times(energy.gradient)