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initialize_optional.m
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initialize_optional.m
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function [ iopt, fileid, final_opt ] = initialize_optional( iopt, id )
% This file is part of GPCCA.
%
% Copyright (c) 2018, 2017 Bernhard Reuter
%
% If you use this code or parts of it, cite the following reference:
%
% Reuter, B., Weber, M., Fackeldey, K., Röblitz, S., & Garcia, M. E. (2018). Generalized
% Markov State Modeling Method for Nonequilibrium Biomolecular Dynamics: Exemplified on
% Amyloid β Conformational Dynamics Driven by an Oscillating Electric Field. Journal of
% Chemical Theory and Computation, 14(7), 3579–3594. https://doi.org/10.1021/acs.jctc.8b00079
%
% GPCCA is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser 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 Lesser General Public License
% along with this program. If not, see <http://www.gnu.org/licenses/>.
% -------------------------------------------------------------------------
% initialize the workspace parameters for the optional final optimization
% procedure.
%
% [ iopt, fileid, final_opt ] = initialize_optional( iopt, id )
%
% Input:
% iopt structure of optional optimization parameters
% id input ID-string to construct the ID-string for naming
% of the output files
%
% Output:
% iopt (initialized) structure
% fileid ID-string for naming of the output files
% final_opt flag to indicate, if the optional final optimization
% shall be performed (1=yes, 0=no)
%
% Written by Bernhard Reuter, Theoretical Physics II,
% University of Kassel, 2017
if isfield(iopt,'solver')
solver = iopt.solver ;
final_opt = true ;
[init,iopt] = getopt(iopt,'init',1) ;
[parallel,iopt] = getopt(iopt,'parallel',0) ;
if (strcmpi(solver,'gauss-newton'))
[maxiter,iopt] = getopt(iopt,'maxiter',100) ;
% no Display currentlly implemented
[display,iopt] = getopt(iopt,'display',0) ;
% relative (!) tolerance in x (real tolerance related to
% XSCALE*XTOL)
[xtol,iopt] = getopt(iopt,'xtol',1e-4) ;
if xtol > 1e-2
xtol = 1.e-2 ;
iopt.xtol = xtol ;
end
% factor for the scaling vector
% xscale = xscale * ones(size(xguess))
[xscale,iopt] = getopt(iopt,'xscale',1e-6) ;
if xscale > xtol
xscale = xtol ;
iopt.xscale = xscale ;
end
fileid=strcat(id,'-',solver,'-','maxiter','_', ...
num2str(maxiter),'-','xscale','_',num2str(xscale), ...
'-','xtol','_',num2str(xtol),'-',numeric_t) ;
elseif (strcmpi(solver,'nelder-mead'))
% maxiter=-1 means off (internal maximum number of iterations
% of the algorithm is used);
% typically maxiter equals 2000-100000 for nelder-mead
[maxiter,iopt] = getopt(iopt,'maxiter',2000) ;
% if display=1, iterative output (and plot - in case of
% Nelder-Mead) is shown;
% if display=0, then not
[display,iopt] = getopt(iopt,'display',0) ;
% typically tolfun=1e-4 for nelder-mead
[tolfun,iopt] = getopt(iopt,'tolfun',1e-8) ;
% typically tolx=1e-4 for nelder-mead
[tolx,iopt] = getopt(iopt,'tolx',1e-8) ;
fileid=strcat(id,'-',solver,'-','maxiter','_', ...
num2str(maxiter),'-','tolfun','_',num2str(tolfun), ...
'-','tolx','_',num2str(tolx),'-',numeric_t) ;
elseif (strcmpi(solver,'levenberg-marquardt'))
% maxiter=-1 means off (internal maximum number of iterations
% of the algorithm is used);
% typically maxiter ~500 for levenberg-marquardt
[maxiter,iopt] = getopt(iopt,'maxiter',500) ;
% if display=1, iterative output (and plot - in case of
% Nelder-Mead) is shown;
% if display=0, then not
[display,iopt] = getopt(iopt,'display',0) ;
% typically tolfun=1e-8 for levenberg-marquardt
[tolfun,iopt] = getopt(iopt,'tolfun',1e-8) ;
% typically tolx=1e-10 for levenberg-marquardt
[tolx,iopt] = getopt(iopt,'tolx',1e-10) ;
fileid=strcat(id,'-',solver,'-','maxiter','_', ...
num2str(maxiter),'-','tolfun','_',num2str(tolfun), ...
'-','tolx','_',num2str(tolx),'-',numeric_t) ;
else
final_opt = 0 ;
error('initialize_optional:SolverError', ...
'Unknown solver for optimization problem.')
end
else
final_opt = false ;
fileid = '' ;
end
end