73 lines
3.0 KiB
Matlab
73 lines
3.0 KiB
Matlab
function fjac = fjaco(f,x,varargin)
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% FJACO Computes two-sided finite difference Jacobian
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% USAGE
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% fjac = fjaco(f,x,P1,P2,...)
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% INPUTS
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% f : name of function of form fval = f(x)
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% x : evaluation point
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% P1,P2,... : additional arguments for f (optional)
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% OUTPUT
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% fjac : finite difference Jacobian
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%
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% Copyright (C) 2010-2017,2019-2020 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare 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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% Dynare 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 Dynare. If not, see <http://www.gnu.org/licenses/>.
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ff=feval(f,x,varargin{:});
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tol = eps.^(1/3); %some default value
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if strcmp(func2str(f),'get_perturbation_params_derivs_numerical_objective') || strcmp(func2str(f),'identification_numerical_objective')
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tol= varargin{5}.dynatol.x;
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end
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h = tol.*max(abs(x),1);
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xh1=x+h; xh0=x-h;
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h=xh1-xh0;
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fjac = NaN(length(ff),length(x));
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for j=1:length(x)
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xx = x;
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xx(j) = xh1(j); f1=feval(f,xx,varargin{:});
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if isempty(f1) && (strcmp(func2str(f),'get_perturbation_params_derivs_numerical_objective') || strcmp(func2str(f),'identification_numerical_objective') )
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[~,info]=feval(f,xx,varargin{:});
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disp_info_error_identification_perturbation(info,j);
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end
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xx(j) = xh0(j); f0=feval(f,xx,varargin{:});
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if isempty(f0) && (strcmp(func2str(f),'get_perturbation_params_derivs_numerical_objective') || strcmp(func2str(f),'identification_numerical_objective') )
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[~,info]=feval(f,xx,varargin{:});
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disp_info_error_identification_perturbation(info,j)
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end
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fjac(:,j) = (f1-f0)/h(j);
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end
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feval(f,x,varargin{:});
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%Auxiliary functions
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function disp_info_error_identification_perturbation(info,j)
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% there are errors in the solution algorithm
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probl_par = get_the_name(j,varargin{5}.TeX,varargin{3},varargin{2},varargin{5});
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skipline()
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message = get_error_message(info,varargin{5});
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fprintf('Parameter error in numerical two-sided difference method:\n')
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fprintf('Cannot solve the model for %s (info = %d, %s)\n', probl_par, info(1), message);
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fprintf('Possible solutions:\n')
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fprintf(' -- check your mod file, calibration and steady state computations carefully\n');
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fprintf(' -- use analytic derivatives, i.e. set analytic_derivation_mode=0\n');
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fprintf(' -- use an estimated_params block without %s or change its value\n', probl_par);
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fprintf(' -- change numerical tolerance level in fjaco.m (you can tune ''options_.dynatol.x'' or change fjaco.m function directly)\n');
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error('fjaco.m: numerical two-sided difference method yields errors in solution algorithm');
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end
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end %main function end |