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roots_and_optimization/goldmin.m
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function [x,fx,ea,iter]=goldmin(f,xl,xu,es,maxit,varargin) | |
% goldmin: minimization golden section search | |
% [x,fx,ea,iter]=goldmin(f,xl,xu,es,maxit,p1,p2,...): | |
% uses golden section search to find the minimum of f | |
% input: | |
% f = name of function | |
% xl, xu = lower and upper guesses | |
% es = desired relative error (default = 0.0001%) | |
% maxit = maximum allowable iterations (default = 50) | |
% p1,p2,... = additional parameters used by f | |
% output: | |
% x = location of minimum | |
% fx = minimum function value | |
% ea = approximate relative error (%) | |
% iter = number of iterations | |
if nargin<3,error('at least 3 input arguments required'),end | |
if nargin<4|isempty(es), es=0.0001;end | |
if nargin<5|isempty(maxit), maxit=50;end | |
phi=(1+sqrt(5))/2; | |
iter=0; | |
while(1) | |
d = (phi-1)*(xu - xl); | |
x1 = xl + d; | |
x2 = xu - d; | |
if f(x1,varargin{:}) < f(x2,varargin{:}) | |
xopt = x1; | |
xl = x2; | |
else | |
xopt = x2; | |
xu = x1; | |
end | |
iter=iter+1; | |
if xopt~=0, ea = (2 - phi) * abs((xu - xl) / xopt) * 100;end | |
if ea <= es | iter >= maxit,break,end | |
end | |
x=xopt;fx=f(xopt,varargin{:}); |