%%%  File Name        : rnn_gen_test_exact.m                    %%%
%%%  Outputs                                                        %%%
%%%     qqq_out       : The vector resulted from the test           %%%
%%%     i_out         : Number of iterations needed for convergence %%%  
%%%     qqq_array_out : Matrix that contains the intermediate resulted vectors
%%%  Inputs                                                         %%%
%%%      Probe_in     : The the input probe vector                  %%%
%%%      Display_in   : = 1 for displaying intermediate results     %%%
%%%      dis          :     convergence stopping crieteria          %%% 
%%%  Date             :     September, 1, 1999                      %%%
%%%  Author           :     Hossam Eldin Mostafa Abdelbaki          %%%
%%%  Address          :     University of Central Florida,          %%%
%%%                   :     School of Computer Science              %%%
%%%  Email            :     ahossam@cs.ucf.edu                      %%% 
%%%  Home Page        :     http://www.cs.ucf.edu/~ahossam/         %%% 
%%%  Help             :     read the manual file (rnnsimv2.pdf)     %%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

function [qqq_out,i_out,qqq_out_array_out] = rnn_gen_test_exact(Probe_in,Num_Iter_in,Display_in,dis)

global wplus wminus r
global LAMBDA lambda;
global N_Total qqq_out;
global Res distance;

distance = dis;
Res = .0001;

i_out = 0;
LAMBDA = []; lambda = [];
prepare_test_patterns(Probe_in);
for i = 1:Num_Iter_in
   qqq_out = solve_nonlinear_equations;
   
   if(nargout == 3)
      qqq_out_array_out(i,:) = qqq_out;
   end

   if(nargout >= 2)   
      flag1 = check_equal;
      if(flag1 == 0)
         i_out = i;
         return
      end
   end
   
   if(Display_in == 1)
      show_output(i);
   end
   LAMBDA = qqq_out;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%% Begin calculate_exact_output  %%%%%%%%%%%%%%%%%%%%%%
function q_result = solve_nonlinear_equations

global wplus wminus;
global r;
global N_Total;
global LAMBDA lambda Res;

lambda_minus = .5*ones(size(LAMBDA));
%lambda_minus = [.1 .1 .1 .1 .1];
for i = 1:N_Total
   for j = 1:N_Total
      Pplus(i,j) = wplus(i,j)/r(i);
      Pminus(i,j) = wminus(i,j)/r(i);
   end
end

for llll = 1:200
   for i = 1:N_Total
      for j = 1:N_Total
         if(i == j)
            F(i,j) = r(i)/(r(i) + lambda_minus(i));
         else
            F(i,j)=0;
         end
      end
   end
   lambda_plus = LAMBDA*inv(eye(N_Total,N_Total)-F*Pplus);
   G = lambda_plus*F*Pminus + lambda;
   %  abs(lambda_minus - G)
   %  llll
   %  pause
   iii = 0;
   for ll = 1:length(lambda_minus)
      if(abs(lambda_minus(i) - G(i)) > .001 | lambda_minus(i) < 0)
         iii = iii + 1;
      end
   end
   if(iii > 0)
      lambda_minus = G;
   else 
      break;
   end
end

for i = 1:N_Total
   for j = 1:N_Total
      if(i == j)
         F(i,j) = r(i)/(r(i) + lambda_minus(i));
      end
      if(i ~= j)
         F(i,j)=0;
      end
   end
end

lambda_plus = LAMBDA*inv(eye(N_Total,N_Total)-F*Pplus);
for i = 1:N_Total
   q(i) = lambda_plus(i)/(r(i)+lambda_minus(i));
   if q(i) > 1
      q(i) = 1;
   end
   if(q(i) < 0)
      q(i) = 0;
   end
   
%   D(i) = lambda_minus(i)+r(i);   
end
q_result = q;     
%%%%%%%%%%%%%%%%%%%%% end solve_nonlinear_equations %%%%%%%%%%%%%%%%%%%%%%%%   

%%%%%  Begin Function prepare_test_patterns %%%%%%%%%%%%%%%%%%%%%%%%
function prepare_test_patterns(W)

global LAMBDA lambda N_Total 

sz = size(W);
N_Test_Patterns = sz(1);
N_Total = sz(2);
N_Input = N_Total ;

Applied_lambda = zeros(N_Test_Patterns ,N_Input);             
Applied_LAMBDA = zeros(N_Test_Patterns ,N_Input);

   for j = 1:N_Input
      if (W(j) >= 0)
         Applied_LAMBDA(j) = W(j);
%         Applied_lambda(j)= .1;   
      elseif(W(j) <0)
        Applied_lambda(j)= -W(j);
%        Applied_LAMBDA(j) = .1;
      end
   end

   for i = 1:N_Input
      LAMBDA(i) = Applied_LAMBDA(i) ;
      lambda(i) = Applied_lambda(i) ;
   end
%%%%%%%%  End Function prepare_test_patterns %%%%%%%%%%%%%%

%%%%%%% Function  show_output  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function show_output(pp)

global qqq_out;

mess1 = sprintf('   Iteration No. %d\n',pp);
disp(mess1);
disp(qqq_out)
pause
%%%%%%%%  end show_output %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function aa = check_equal

global LAMBDA qqq_out distance
aa = 0;
%for kk=1:length(qqq_out)
%   if(abs(qqq_out(kk) - LAMBDA(kk)) > 0.0001)
%      aa = aa + 1;
%      return   
%   end
%end
if(norm(qqq_out - LAMBDA) > distance)
   aa = aa +1;
end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%