function [final_angles,final_tear] = fn_fold_relax_fmincon_springs(fold_angles,CP,thresh,springs)

theta_angles = CP.theta_angles ;
edges_at_vertex = CP.edges_at_vertex;

% Minimize tearing for simpe quads with fixed|rho| - using
% fmincon



% find null spaces
[C,~] = fnm_compute_CF(zeros(size(CP.alledges,1),1),CP.theta_angles,CP.edges_at_vertex,1e-12);
[u,s,v]=svd(C);

S = sign(fold_angles);

amp = norm(fold_angles); 
Rho = fold_angles; % Later, might want to project to null space of C



%history.x=[];
%history.fval=[];
%searchdir = [];

options=optimoptions('fmincon','Display','none','Algorithm','sqp','GradObj','off','MaxIter',thresh.fmin_relax_MaxIter,'MaxFunEvals',thresh.fmin_relax_evals*length(fold_angles),'TolFun',thresh.fmin_tolfun,'TolX',thresh.fmin_tolx);%,'OutputFcn',@outfun); %,'TypicalX',rem_fold_angles);
    %'GradConstr','on',
        
[final_angles,final_tear,exitflag]=fmincon(@(fa) mintear(fa),Rho,[],[],[],[],[],[],@(fa) mycon(fa),options);

%[~,final_tear_vec]=fnm_compute_CF_mex(final_angles,theta_angles,edges_at_vertex,1e-8);
%final_tear = norm(final_tear_vec);


if exitflag == 0
    disp('relax_fmincon ran out of iterations/evaluations');
else
    %disp(['relax_fminunc flag = ' num2str(exitflag)]);
end
% % % % Internal functions

    %function [tear,grad] = mintear(fa)
    function [tear] = mintear(fa)
        
        [C,Fvec]=fnm_compute_CF(fa,theta_angles,edges_at_vertex,1e-12);  
        
        %tear = norm(Fvec);
        %tear = sqrt(norm(Fvec)^2 + 0.5 * springs' * fa.^2) ; 
        tear0 = norm(Fvec)^2 + 0.5 * springs' * fa.^2 ;
        tear = log(tear0) ;  
        
        %force_int = +(C'*Fvec);  
        %force_spr = springs .* fa;
 
        %grad0 = force_int + force_spr;
        %grad0 = grad0 - (grad0'*fa)*fa/norm(fa)^2;
        %grad = (grad0) ;
        
        %disp(grad'*fa);
        %disp(tear)
       
    end

    function [p,Rho2,gp,gRho2] = mycon(fa)
         
        Rho2 = norm(fa)- amp; 
        gRho2 = fa/norm(Rho2);

        
        p=-1;
        gp=0;

    end

    function stop = outfun(x,optimValues,state)
     stop = false;
 
     switch state
         case 'init'
             hold on
         case 'iter'
         % Concatenate current point and objective function
         % value with history. x must be a row vector.
           history.fval = [history.fval; optimValues.fval];
           history.x = [history.x; x'];
         % Concatenate current search direction with 
         % searchdir.
           searchdir = [searchdir;... 
                        optimValues.searchdirection'];
         case 'done'
             hold off
         otherwise
     end
    end
end