66 lines
1.9 KiB
Prolog
66 lines
1.9 KiB
Prolog
%%% -*- Mode: Prolog; -*-
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% This file is part of YAP-LBFGS.
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% Copyright (C) 2009 Bernd Gutmann
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%
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% YAP-LBFGS is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% YAP-LBFGS is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with YAP-LBFGS. If not, see <http://www.gnu.org/licenses/>.
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:- use_module(library(lbfgs)).
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:- use_module(library(matrix)).
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% This is the call back function which evaluates F and the gradient of F
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evaluate(FX,X,G,_N,_Step) :-
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X0 <== X[0],
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X1 <== X[1],
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FX is (X0-2)*(X0-2) + (X1-1)*(X1-1),
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G0 is 2*(X0-2),
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G1 is 2*(X1-2),
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G[0] <== G0,
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G[1] <== G1.
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% This is the call back function which is invoked to report the progress
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% if the last argument is set to anything else than 0, the optimizer will
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% stop right now
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progress(FX,X,_G,X_Norm,G_Norm,Step,_N,Iteration,Ls,0) :-
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X0 <== X[0],
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X1 <== X[1],
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format('~d. Iteration : (x0,x1)=(~4f,~4f) f(X)=~4f |X|=~4f |X\'|=~4f Step=~4f Ls=~4f~n',[Iteration,X0,X1,FX,X_Norm,G_Norm,Step,Ls]).
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demo :-
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format('Optimizing the function f(x0,x1) = (x0-2)^2 + (x1-1)^2~n',[]),
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optimizer_initialize(2,X),
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StartX0 is random*1000-500,
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StartX1 is random*1000-500,
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format('We start the search at the random position (x0,x1)=(~5f,~5f)~2n',[StartX0,StartX1]),
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X[0] <== StartX0,
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X[1] <== StartX1,
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optimizer_run(BestF,Status),
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BestX0 <== X[0],
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BestX1 <== X[1],
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optimizer_finalize,
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format('~2nOptimization done~nWe found a minimum at f(~f,~f)=~f~2nLBFGS Status=~w~n',[BestX0,BestX1,BestF,Status]).
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