v4 csminwel.m: new version from Chris Sims
git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@654 ac1d8469-bf42-47a9-8791-bf33cf982152time-shift
michel
parent
50ab0c0473
commit
244d8775e3
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@ -1,274 +1,275 @@
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function [fh,xh,gh,H,itct,fcount,retcodeh] = csminwel(fcn,x0,H0,grad,crit,nit,varargin)
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%[fhat,xhat,ghat,Hhat,itct,fcount,retcodehat] = csminwel(fcn,x0,H0,grad,crit,nit,varargin)
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% fcn: string naming the objective function to be minimized
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% x0: initial value of the parameter vector
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% H0: initial value for the inverse Hessian. Must be positive definite.
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% grad: Either a string naming a function that calculates the gradient, or the null matrix.
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% If it's null, the program calculates a numerical gradient. In this case fcn must
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% be written so that it can take a matrix argument and produce a row vector of values.
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% crit: Convergence criterion. Iteration will cease when it proves impossible to improve the
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% function value by more than crit.
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% nit: Maximum number of iterations.
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% varargin: A list of optional length of additional parameters that get handed off to fcn each
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% time it is called.
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% Note that if the program ends abnormally, it is possible to retrieve the current x,
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% f, and H from the files g1.mat and H.mat that are written at each iteration and at each
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% hessian update, respectively. (When the routine hits certain kinds of difficulty, it
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% write g2.mat and g3.mat as well. If all were written at about the same time, any of them
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% may be a decent starting point. One can also start from the one with best function value.)
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global bayestopt_
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[nx,no]=size(x0);
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nx=max(nx,no);
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Verbose=1;
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NumGrad= isempty(grad);
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done=0;
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itct=0;
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fcount=0;
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snit=100;
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%tailstr = ')';
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%stailstr = [];
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% Lines below make the number of Pi's optional. This is inefficient, though, and precludes
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% use of the matlab compiler. Without them, we use feval and the number of Pi's must be
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% changed with the editor for each application. Places where this is required are marked
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% with ARGLIST comments
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%for i=nargin-6:-1:1
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% tailstr=[ ',P' num2str(i) tailstr];
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% stailstr=[' P' num2str(i) stailstr];
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%end
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f0 = feval(fcn,x0,varargin{:});
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%ARGLIST
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%f0 = feval(fcn,x0,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,P11,P12,P13);
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% disp('first fcn in csminwel.m ----------------') % Jinill on 9/5/95
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if f0 > 1e50, disp('Bad initial parameter.'), return, end
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if NumGrad
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if length(grad)==0
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[g badg] = numgrad(fcn,x0, varargin{:});
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%ARGLIST
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%[g badg] = numgrad(fcn,x0,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,P11,P12,P13);
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else
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badg=any(find(grad==0));
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g=grad;
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end
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%numgrad(fcn,x0,P1,P2,P3,P4);
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else
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[g badg] = feval(grad,x0,varargin{:});
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%ARGLIST
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%[g badg] = feval(grad,x0,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,P11,P12,P13);
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end
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retcode3=101;
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x=x0;
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f=f0;
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H=H0;
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cliff=0;
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while ~done
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bayestopt_.penalty = f;
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g1=[]; g2=[]; g3=[];
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%addition fj. 7/6/94 for control
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disp('-----------------')
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disp('-----------------')
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%disp('f and x at the beginning of new iteration')
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disp(sprintf('f at the beginning of new iteration, %20.10f',f))
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%-----------Comment out this line if the x vector is long----------------
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% disp([sprintf('x = ') sprintf('%15.8g %15.8g %15.8g %15.8g\n',x(1:12))]);
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%-------------------------
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itct=itct+1;
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[f1 x1 fc retcode1] = csminit(fcn,x,f,g,badg,H,varargin{:});
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%ARGLIST
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%[f1 x1 fc retcode1] = csminit(fcn,x,f,g,badg,H,P1,P2,P3,P4,P5,P6,P7,...
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% P8,P9,P10,P11,P12,P13);
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% itct=itct+1;
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fcount = fcount+fc;
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% erased on 8/4/94
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% if (retcode == 1) | (abs(f1-f) < crit)
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% done=1;
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% end
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% if itct > nit
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% done = 1;
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% retcode = -retcode;
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% end
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if retcode1 ~= 1
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if retcode1==2 | retcode1==4
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wall1=1; badg1=1;
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else
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if NumGrad
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[g1 badg1] = numgrad(fcn, x1,varargin{:});
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%ARGLIST
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%[g1 badg1] = numgrad(fcn, x1,P1,P2,P3,P4,P5,P6,P7,P8,P9,...
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% P10,P11,P12,P13);
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else
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[g1 badg1] = feval(grad,x1,varargin{:});
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%ARGLIST
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%[g1 badg1] = feval(grad, x1,P1,P2,P3,P4,P5,P6,P7,P8,P9,...
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% P10,P11,P12,P13);
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end
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wall1=badg1;
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% g1
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save g1 g1 x1 f1 varargin;
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%ARGLIST
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%save g1 g1 x1 f1 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13;
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end
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if wall1 % & (~done) by Jinill
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% Bad gradient or back and forth on step length. Possibly at
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% cliff edge. Try perturbing search direction.
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%
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%fcliff=fh;xcliff=xh;
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Hcliff=H+diag(diag(H).*rand(nx,1));
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disp('Cliff. Perturbing search direction.')
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[f2 x2 fc retcode2] = csminit(fcn,x,f,g,badg,Hcliff,varargin{:});
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%ARGLIST
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%[f2 x2 fc retcode2] = csminit(fcn,x,f,g,badg,Hcliff,P1,P2,P3,P4,...
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% P5,P6,P7,P8,P9,P10,P11,P12,P13);
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fcount = fcount+fc; % put by Jinill
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if f2 < f
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if retcode2==2 | retcode2==4
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wall2=1; badg2=1;
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else
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if NumGrad
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[g2 badg2] = numgrad(fcn, x2,varargin{:});
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%ARGLIST
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%[g2 badg2] = numgrad(fcn, x2,P1,P2,P3,P4,P5,P6,P7,P8,...
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% P9,P10,P11,P12,P13);
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else
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[g2 badg2] = feval(grad,x2,varargin{:});
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%ARGLIST
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%[g2 badg2] = feval(grad,x2,P1,P2,P3,P4,P5,P6,P7,P8,...
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% P9,P10,P11,P12,P13);
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end
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wall2=badg2;
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% g2
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badg2
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save g2 g2 x2 f2 varargin
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%ARGLIST
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%save g2 g2 x2 f2 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13;
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end
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if wall2
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disp('Cliff again. Try traversing')
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if norm(x2-x1) < 1e-13
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f3=f; x3=x; badg3=1;retcode3=101;
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else
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gcliff=((f2-f1)/((norm(x2-x1))^2))*(x2-x1);
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[f3 x3 fc retcode3] = csminit(fcn,x,f,gcliff,0,eye(nx),varargin{:});
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%ARGLIST
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%[f3 x3 fc retcode3] = csminit(fcn,x,f,gcliff,0,eye(nx),P1,P2,P3,...
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% P4,P5,P6,P7,P8,...
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% P9,P10,P11,P12,P13);
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fcount = fcount+fc; % put by Jinill
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if retcode3==2 | retcode3==4
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wall3=1; badg3=1;
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else
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if NumGrad
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[g3 badg3] = numgrad(fcn, x3,varargin{:});
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%ARGLIST
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%[g3 badg3] = numgrad(fcn, x3,P1,P2,P3,P4,P5,P6,P7,P8,...
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% P9,P10,P11,P12,P13);
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else
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[g3 badg3] = feval(grad,x3,varargin{:});
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%ARGLIST
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%[g3 badg3] = feval(grad,x3,P1,P2,P3,P4,P5,P6,P7,P8,...
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% P9,P10,P11,P12,P13);
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end
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wall3=badg3;
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% g3
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badg3
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save g3 g3 x3 f3 varargin;
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%ARGLIST
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%save g3 g3 x3 f3 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13;
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end
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end
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else
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f3=f; x3=x; badg3=1; retcode3=101;
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end
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else
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f3=f; x3=x; badg3=1;retcode3=101;
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end
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else
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% normal iteration, no walls, or else we're finished here.
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f2=f; f3=f; badg2=1; badg3=1; retcode2=101; retcode3=101;
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end
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else
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f2=f;f3=f;f1=f;retcode2=retcode1;retcode3=retcode1;
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end
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%how to pick gh and xh
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if f3<f & badg3==0
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ih=3
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fh=f3;xh=x3;gh=g3;badgh=badg3;retcodeh=retcode3;
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elseif f2<f & badg2==0
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ih=2
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fh=f2;xh=x2;gh=g2;badgh=badg2;retcodeh=retcode2;
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elseif f1<f & badg1==0
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ih=1
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fh=f1;xh=x1;gh=g1;badgh=badg1;retcodeh=retcode1;
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else
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[fh,ih] = min([f1,f2,f3]);
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disp(sprintf('ih = %d',ih))
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%eval(['xh=x' num2str(ih) ';'])
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switch ih
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case 1
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xh=x1;
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case 2
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xh=x2;
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case 3
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xh=x3;
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end %case
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%eval(['gh=g' num2str(ih) ';'])
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%eval(['retcodeh=retcode' num2str(ih) ';'])
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retcodei=[retcode1,retcode2,retcode3];
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retcodeh=retcodei(ih);
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if exist('gh')
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nogh=isempty(gh);
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else
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nogh=1;
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end
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if nogh
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if NumGrad
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[gh badgh] = numgrad(fcn,xh,varargin{:});
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else
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[gh badgh] = feval(grad, xh,varargin{:});
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end
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end
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badgh=1;
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end
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%end of picking
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%ih
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%fh
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%xh
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%gh
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%badgh
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stuck = (abs(fh-f) < crit);
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if (~badg)&(~badgh)&(~stuck)
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H = bfgsi(H,gh-g,xh-x);
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end
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if Verbose
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disp('----')
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disp(sprintf('Improvement on iteration %d = %18.9f',itct,f-fh))
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end
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if Verbose
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if itct > nit
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disp('iteration count termination')
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done = 1;
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elseif stuck
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disp('improvement < crit termination')
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done = 1;
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end
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rc=retcodeh;
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if rc == 1
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disp('zero gradient')
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elseif rc == 6
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disp('smallest step still improving too slow, reversed gradient')
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elseif rc == 5
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disp('largest step still improving too fast')
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elseif (rc == 4) | (rc==2)
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disp('back and forth on step length never finished')
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elseif rc == 3
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disp('smallest step still improving too slow')
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elseif rc == 7
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disp('warning: possible inaccuracy in H matrix')
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end
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end
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f=fh;
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x=xh;
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g=gh;
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badg=badgh;
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end
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% what about making an m-file of 10 lines including numgrad.m
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% since it appears three times in csminwel.m
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function [fh,xh,gh,H,itct,fcount,retcodeh] = csminwel(fcn,x0,H0,grad,crit,nit,varargin)
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%[fhat,xhat,ghat,Hhat,itct,fcount,retcodehat] = csminwel(fcn,x0,H0,grad,crit,nit,varargin)
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% fcn: string naming the objective function to be minimized
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% x0: initial value of the parameter vector
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% H0: initial value for the inverse Hessian. Must be positive definite.
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% grad: Either a string naming a function that calculates the gradient, or the null matrix.
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% If it's null, the program calculates a numerical gradient. In this case fcn must
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% be written so that it can take a matrix argument and produce a row vector of values.
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% crit: Convergence criterion. Iteration will cease when it proves impossible to improve the
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% function value by more than crit.
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% nit: Maximum number of iterations.
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% varargin: A list of optional length of additional parameters that get handed off to fcn each
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% time it is called.
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% Note that if the program ends abnormally, it is possible to retrieve the current x,
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% f, and H from the files g1.mat and H.mat that are written at each iteration and at each
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% hessian update, respectively. (When the routine hits certain kinds of difficulty, it
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% write g2.mat and g3.mat as well. If all were written at about the same time, any of them
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% may be a decent starting point. One can also start from the one with best function value.)
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global bayestopt_
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[nx,no]=size(x0);
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nx=max(nx,no);
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Verbose=1;
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NumGrad= isempty(grad);
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done=0;
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itct=0;
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fcount=0;
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snit=100;
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%tailstr = ')';
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%stailstr = [];
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% Lines below make the number of Pi's optional. This is inefficient, though, and precludes
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% use of the matlab compiler. Without them, we use feval and the number of Pi's must be
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% changed with the editor for each application. Places where this is required are marked
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% with ARGLIST comments
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%for i=nargin-6:-1:1
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% tailstr=[ ',P' num2str(i) tailstr];
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% stailstr=[' P' num2str(i) stailstr];
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%end
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f0 = feval(fcn,x0,varargin{:});
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%ARGLIST
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%f0 = feval(fcn,x0,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,P11,P12,P13);
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% disp('first fcn in csminwel.m ----------------') % Jinill on 9/5/95
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if f0 > 1e50, disp('Bad initial parameter.'), return, end
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if NumGrad
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if length(grad)==0
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[g badg] = numgrad(fcn,x0, varargin{:});
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%ARGLIST
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%[g badg] = numgrad(fcn,x0,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,P11,P12,P13);
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else
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badg=any(find(grad==0));
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g=grad;
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end
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%numgrad(fcn,x0,P1,P2,P3,P4);
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else
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[g badg] = feval(grad,x0,varargin{:});
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%ARGLIST
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%[g badg] = feval(grad,x0,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,P11,P12,P13);
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end
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retcode3=101;
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x=x0;
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f=f0;
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H=H0;
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cliff=0;
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while ~done
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bayestopt_.penalty = f;
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g1=[]; g2=[]; g3=[];
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%addition fj. 7/6/94 for control
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disp('-----------------')
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disp('-----------------')
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%disp('f and x at the beginning of new iteration')
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disp(sprintf('f at the beginning of new iteration, %20.10f',f))
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%-----------Comment out this line if the x vector is long----------------
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% disp([sprintf('x = ') sprintf('%15.8g %15.8g %15.8g %15.8g\n',x)]);
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%-------------------------
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itct=itct+1;
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[f1 x1 fc retcode1] = csminit(fcn,x,f,g,badg,H,varargin{:});
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%ARGLIST
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%[f1 x1 fc retcode1] = csminit(fcn,x,f,g,badg,H,P1,P2,P3,P4,P5,P6,P7,...
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% P8,P9,P10,P11,P12,P13);
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% itct=itct+1;
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fcount = fcount+fc;
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% erased on 8/4/94
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% if (retcode == 1) | (abs(f1-f) < crit)
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% done=1;
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% end
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% if itct > nit
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% done = 1;
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% retcode = -retcode;
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% end
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if retcode1 ~= 1
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if retcode1==2 | retcode1==4
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wall1=1; badg1=1;
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else
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if NumGrad
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[g1 badg1] = numgrad(fcn, x1,varargin{:});
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%ARGLIST
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%[g1 badg1] = numgrad(fcn, x1,P1,P2,P3,P4,P5,P6,P7,P8,P9,...
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% P10,P11,P12,P13);
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else
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[g1 badg1] = feval(grad,x1,varargin{:});
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%ARGLIST
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%[g1 badg1] = feval(grad, x1,P1,P2,P3,P4,P5,P6,P7,P8,P9,...
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% P10,P11,P12,P13);
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end
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wall1=badg1;
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% g1
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save g1 g1 x1 f1 varargin;
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%ARGLIST
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||||
%save g1 g1 x1 f1 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13;
|
||||
end
|
||||
if wall1 % & (~done) by Jinill
|
||||
% Bad gradient or back and forth on step length. Possibly at
|
||||
% cliff edge. Try perturbing search direction.
|
||||
%
|
||||
%fcliff=fh;xcliff=xh;
|
||||
Hcliff=H+diag(diag(H).*rand(nx,1));
|
||||
disp('Cliff. Perturbing search direction.')
|
||||
[f2 x2 fc retcode2] = csminit(fcn,x,f,g,badg,Hcliff,varargin{:});
|
||||
%ARGLIST
|
||||
%[f2 x2 fc retcode2] = csminit(fcn,x,f,g,badg,Hcliff,P1,P2,P3,P4,...
|
||||
% P5,P6,P7,P8,P9,P10,P11,P12,P13);
|
||||
fcount = fcount+fc; % put by Jinill
|
||||
if f2 < f
|
||||
if retcode2==2 | retcode2==4
|
||||
wall2=1; badg2=1;
|
||||
else
|
||||
if NumGrad
|
||||
[g2 badg2] = numgrad(fcn, x2,varargin{:});
|
||||
%ARGLIST
|
||||
%[g2 badg2] = numgrad(fcn, x2,P1,P2,P3,P4,P5,P6,P7,P8,...
|
||||
% P9,P10,P11,P12,P13);
|
||||
else
|
||||
[g2 badg2] = feval(grad,x2,varargin{:});
|
||||
%ARGLIST
|
||||
%[g2 badg2] = feval(grad,x2,P1,P2,P3,P4,P5,P6,P7,P8,...
|
||||
% P9,P10,P11,P12,P13);
|
||||
end
|
||||
wall2=badg2;
|
||||
% g2
|
||||
badg2
|
||||
save g2 g2 x2 f2 varargin
|
||||
%ARGLIST
|
||||
%save g2 g2 x2 f2 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13;
|
||||
end
|
||||
if wall2
|
||||
disp('Cliff again. Try traversing')
|
||||
if norm(x2-x1) < 1e-13
|
||||
f3=f; x3=x; badg3=1;retcode3=101;
|
||||
else
|
||||
gcliff=((f2-f1)/((norm(x2-x1))^2))*(x2-x1);
|
||||
if(size(x0,2)>1), gcliff=gcliff', end
|
||||
[f3 x3 fc retcode3] = csminit(fcn,x,f,gcliff,0,eye(nx),varargin{:});
|
||||
%ARGLIST
|
||||
%[f3 x3 fc retcode3] = csminit(fcn,x,f,gcliff,0,eye(nx),P1,P2,P3,...
|
||||
% P4,P5,P6,P7,P8,...
|
||||
% P9,P10,P11,P12,P13);
|
||||
fcount = fcount+fc; % put by Jinill
|
||||
if retcode3==2 | retcode3==4
|
||||
wall3=1; badg3=1;
|
||||
else
|
||||
if NumGrad
|
||||
[g3 badg3] = numgrad(fcn, x3,varargin{:});
|
||||
%ARGLIST
|
||||
%[g3 badg3] = numgrad(fcn, x3,P1,P2,P3,P4,P5,P6,P7,P8,...
|
||||
% P9,P10,P11,P12,P13);
|
||||
else
|
||||
[g3 badg3] = feval(grad,x3,varargin{:});
|
||||
%ARGLIST
|
||||
%[g3 badg3] = feval(grad,x3,P1,P2,P3,P4,P5,P6,P7,P8,...
|
||||
% P9,P10,P11,P12,P13);
|
||||
end
|
||||
wall3=badg3;
|
||||
% g3
|
||||
badg3
|
||||
save g3 g3 x3 f3 varargin;
|
||||
%ARGLIST
|
||||
%save g3 g3 x3 f3 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13;
|
||||
end
|
||||
end
|
||||
else
|
||||
f3=f; x3=x; badg3=1; retcode3=101;
|
||||
end
|
||||
else
|
||||
f3=f; x3=x; badg3=1;retcode3=101;
|
||||
end
|
||||
else
|
||||
% normal iteration, no walls, or else we're finished here.
|
||||
f2=f; f3=f; badg2=1; badg3=1; retcode2=101; retcode3=101;
|
||||
end
|
||||
else
|
||||
f2=f;f3=f;f1=f;retcode2=retcode1;retcode3=retcode1;
|
||||
end
|
||||
%how to pick gh and xh
|
||||
if f3 < f - crit & badg3==0
|
||||
ih=3
|
||||
fh=f3;xh=x3;gh=g3;badgh=badg3;retcodeh=retcode3;
|
||||
elseif f2 < f - crit & badg2==0
|
||||
ih=2
|
||||
fh=f2;xh=x2;gh=g2;badgh=badg2;retcodeh=retcode2;
|
||||
elseif f1 < f - crit & badg1==0
|
||||
ih=1
|
||||
fh=f1;xh=x1;gh=g1;badgh=badg1;retcodeh=retcode1;
|
||||
else
|
||||
[fh,ih] = min([f1,f2,f3]);
|
||||
disp(sprintf('ih = %d',ih))
|
||||
%eval(['xh=x' num2str(ih) ';'])
|
||||
switch ih
|
||||
case 1
|
||||
xh=x1;
|
||||
case 2
|
||||
xh=x2;
|
||||
case 3
|
||||
xh=x3;
|
||||
end %case
|
||||
%eval(['gh=g' num2str(ih) ';'])
|
||||
%eval(['retcodeh=retcode' num2str(ih) ';'])
|
||||
retcodei=[retcode1,retcode2,retcode3];
|
||||
retcodeh=retcodei(ih);
|
||||
if exist('gh')
|
||||
nogh=isempty(gh);
|
||||
else
|
||||
nogh=1;
|
||||
end
|
||||
if nogh
|
||||
if NumGrad
|
||||
[gh badgh] = numgrad(fcn,xh,varargin{:});
|
||||
else
|
||||
[gh badgh] = feval(grad, xh,varargin{:});
|
||||
end
|
||||
end
|
||||
badgh=1;
|
||||
end
|
||||
%end of picking
|
||||
%ih
|
||||
%fh
|
||||
%xh
|
||||
%gh
|
||||
%badgh
|
||||
stuck = (abs(fh-f) < crit);
|
||||
if (~badg)&(~badgh)&(~stuck)
|
||||
H = bfgsi(H,gh-g,xh-x);
|
||||
end
|
||||
if Verbose
|
||||
disp('----')
|
||||
disp(sprintf('Improvement on iteration %d = %18.9f',itct,f-fh))
|
||||
end
|
||||
% if Verbose
|
||||
if itct > nit
|
||||
disp('iteration count termination')
|
||||
done = 1;
|
||||
elseif stuck
|
||||
disp('improvement < crit termination')
|
||||
done = 1;
|
||||
end
|
||||
rc=retcodeh;
|
||||
if rc == 1
|
||||
disp('zero gradient')
|
||||
elseif rc == 6
|
||||
disp('smallest step still improving too slow, reversed gradient')
|
||||
elseif rc == 5
|
||||
disp('largest step still improving too fast')
|
||||
elseif (rc == 4) | (rc==2)
|
||||
disp('back and forth on step length never finished')
|
||||
elseif rc == 3
|
||||
disp('smallest step still improving too slow')
|
||||
elseif rc == 7
|
||||
disp('warning: possible inaccuracy in H matrix')
|
||||
end
|
||||
% end
|
||||
f=fh;
|
||||
x=xh;
|
||||
g=gh;
|
||||
badg=badgh;
|
||||
end
|
||||
% what about making an m-file of 10 lines including numgrad.m
|
||||
% since it appears three times in csminwel.m
|
||||
|
|
|
|||
Loading…
Reference in New Issue