You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: triple.m
    path of file: ./repos/optimviz/utils/mcs/private
    
    the code of the file until where you have to start completion: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% triple.m %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% function [xtrip,ftrip,g,G,x1,x2,nf] = triple(fcn,data,x,f,x1,x2,u,v,G)
% finding a l
    
function [xtrip,ftrip,g,G,x1,x2,nf] = triple(fcn,data,x,f,x1,x2,u,v,G)
% finding a local quadratic model by triple search
% Input:
% fcn = 'fun'	name of function fun(data,x), x an n-vector
% x(1:n)	start vector
% f		its function value
% x1(1:n), x2(1:n)  'neighbors' of x with x(i), x1(i), x2(i) pairwise
%		distinct for i = 1,...,n
% [u,v]		original box
% G		Hessian of the quadratic model around xtrip
% Output:
% xtrip(1:n)	best point found 
% ftrip		its function value
% g, G		gradient and Hessian of the quadratic model around xtrip
% the quadratic model is given by
% q(x) = ftrip + g^T(x-xtrip) + 0.5(x-xtrip)G(x-xtrip)
% Uses the following m-files:
% hessian.m
% polint1.m

function [xtrip,ftrip,g,G,x1,x2,nf] = triple(fcn,data,x,f,x1,x2,u,v,hess,G)
nf = 0;
n = length(x);
g = zeros(n,1);
if nargin < 9
  hess = ones(n,n);
end