%%%******************  test_rnn_gen.m   *********************%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%  Info  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%   File Name       :     test_rnn_gen.m                          %%%
%%%   Type            :     m function file                         %%%
%%%   Parent          :     use_rnn_gen.m                           %%%
%%%   External Calls  :     vardef.m                                %%%  
%%%   Internal Calls  :     Prepare_Tst_Patterns                    %%%
%%%                         calculate_rate                          %%%
%%%                         calculate_ffm_output                    %%%
%%%                         save_response_txt                       %%%
%%%                         save_response_m                         %%%
%%%   Date            :     September, 1, 1999                      %%%
%%%   Author          :     Hossam Eldin Mostafa Abdelbaki          %%%
%%%   Address         :     University of Centeral 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 q_cal_1 = test_rnn_gen(kind,TEST_INPUT_1,r_1,Weights_File_Name_1,Log_File_Name_1, ...
                       Temp_Log_File_Name_1)

vardef;                    

if(nargin > 2)
   r = r_1;   
end

if(nargin > 3)
   Weights_File_Name = Weights_File_Name_1;
   mess = sprintf('load %s',Weights_File_Name);
   disp(mess)
   eval(mess);
end

SAVE_TEXT_LOG = 0;
SAVE_MFILE_LOG = 0; 

if(nargin > 4)
   Log_File_Name = Log_File_Name_1;
   SAVE_TEXT_LOG = 1;   
end

if(nargin > 5)
    Temp_Log_File_Name = Temp_Log_File_Name_1;   
    SAVE_MFILE_LOG = 1; 
end


TEST_INPUT = TEST_INPUT_1;
start = last_iter;
sz = size(TEST_INPUT);
N_Test_Patterns = sz(1);
prepare_tst_patterns;
%%%%%%%%%%%%%%%%%%%   BEGIN  TESTING MODE %%%%%%%%%%%%%%%%%%%%%%%%%%%%
%if(nargin == 1)
r = calculate_rate;
%end
q_cal =[];
for k = 1:N_Test_Patterns   
   if(kind == '1')
      q = calculate_ffm_output(k);
   end
   if(kind == '2')
      q = solve_nonlinear_equations_1(k);   %Solve for q      
   end
   
   for i = 1:N_Output
      q_cal(k,i) = q(output_index(i));
   end
end %for
%%%%%%%%%%%%%%%%%%%   END  TESTING MODE %%%%%%%%%%%%%%%%%%%%%%%%%%%%

if(SAVE_TEXT_LOG == 1)
   save_response_txt;
end

if(SAVE_MFILE_LOG == 1)
   save_response_m;
end

q_cal_1 = q_cal;
%%%%%%%%%%%%%%%%%%%   END  TESTING MODE %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


%%%%%%%%%%%%%%%%%%%% FUNCTIONS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%% Prepare_Tst_Patterns  %%%%%%%%%%%%%%%%%%%%%%%%%
function prepare_tst_patterns()

global   N_Test_Patterns TEST_INPUT N_Input LAMBDA lambda N_Total

%disp('  Preparing Test Patterns ....');
%%%%%%%%%%%%Function: Preparing Inputs for Testing %%%%%%%%%%%%%%%
%####### Setting the Excitatory and Inhibitatory Training Patterns ########
%N_Test_Patterns = N_Patterns;
Applied_lambda = zeros(N_Test_Patterns,N_Input);             
Applied_LAMBDA = zeros(N_Test_Patterns,N_Input);
%yyy = size(TEST_INPUT);
%N_Test_Patterns = yyy(1);
for i = 1:N_Test_Patterns
   for j = 1:N_Input
      if (TEST_INPUT(i,j) >= 0)
         Applied_LAMBDA(i,j) = TEST_INPUT(i,j);
      elseif(TEST_INPUT(i,j) <0)
         Applied_lambda(i,j)= -TEST_INPUT(i,j);
      end
   end
end  

%##### Preparing LAMBDA #################
%fill = zeros(N_Test_Patterns , N_Total - N_Input);
%LAMBDA=[Applied_LAMBDA fill];
for k = 1:N_Test_Patterns
   for i = 1:N_Input
      LAMBDA(k,i) = Applied_LAMBDA(k,i) ;
   end
   for i = (N_Input+1):N_Total
      LAMBDA(k,i) = 0.0;
   end
end

%##### Preparing lambda #################
%Applied_lambda=zeros(N_Test_Patterns,N_Input);
%fill = zeros(N_Test_Patterns , N_Total - N_Input);
%lambda=[Applied_lambda fill];
for k = 1:N_Test_Patterns
   for i = 1:N_Input
      lambda(k,i) = Applied_lambda(k,i) ;
   end
   for i = (N_Input+1):N_Total
      lambda(k,i) = 0.0;
   end
end
%%%%%%%%%%%%%%%%%%%%% end Prepare_Tst_Patterns  %%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%  calculate_rate  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%      
function r_result = calculate_rate()     

global N_Total wplus wminus R_IN R_Out FIX_RIN N_Output output_index AUTO_MAPPING N_Input;

for i = 1:N_Total
   r_result(i) = 0.0;
end
if(FIX_RIN == 1 )
   for i = 1:N_Input
      r_result(i) = R_IN;
   end
   
   for i = (N_Input+1):N_Total
      for j = 1:N_Total
         r_result(i) = r_result(i) + wplus(i,j) + wminus(i,j);
      end
   end
end

if(FIX_RIN == 0 )
   for i = 1:N_Total
      for j = 1:N_Total
         r_result(i) = r_result(i) + wplus(i,j) + wminus(i,j);
      end
   end
end

if(AUTO_MAPPING == 0)
   for i = 1:N_Output
      r_result(output_index(i)) = R_Out;   
   end
end

%%%%%%%%%%%%%%%%%%%%  end calculate_rate  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%  

%%%%%%%%%%%%%%%%%%%%  calculate_ffm_output  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function q_result = calculate_ffm_output(k)

global wplus wminus;
global r;
global N_Total N_Input;
global R_Out;
global output_index LAMBDA lambda y D  Res;

q = zeros(1,N_Total);      

     for i = 1:N_Total      
        N(i) = 0.0;
        D(i) = 0.0;
        for j = 1:N_Total
          N(i) = N(i) + q(j) * wplus(j,i);
          D(i) = D(i) + q(j) * wminus(j,i);
        end
        N(i) = N(i) + LAMBDA(k,i);
        D(i) = D(i) + r(i) + lambda(k,i);
        q(i) = N(i)/D(i);
        if(D(i) ~= 0)
           q(i) = N(i)/D(i);
        end
        if(D(i) == 0)
           q(i) = 1.0;
        end
        if(q(i) > 1.0) 
           q(i) = 1.0;
        end
        if(q(i) < 0.0) 
           q(i) = 0.0;
        end
     end
q_result = q;     
%%%%%%%%%%%%%%%%%%%%  end calculate_ffm_output  %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%  solve_nonlinear_equations_1 %%%%%%%%%%%%%%%%%%%%%%%%%%%
function q_result = solve_nonlinear_equations_1(k)

global wplus wminus;
global r;
global N_Total;
global R_Out;
global output_index LAMBDA lambda y D  Res;

lambda_minus = .2*rand(1,N_Total);
for i = 1:N_Total
   for j = 1:N_Total
      if(r(i) ~= 0)
         Pplus(i,j) = wplus(i,j)/r(i);
         Pminus(i,j) = wminus(i,j)/r(i);
      else
         Pplus(i,j) = 0;
         Pminus(i,j) = 0;
      end
   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(k,:)*inv(eye(N_Total,N_Total)-F*Pplus);
   G = lambda_plus*F*Pminus + lambda(k,:);
   %  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(k,:)*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 %%%%%%%%%%%%%%%%%%%%%%%%  

%%%%%%%%%%%%%%%%%%%%% save_response_txt  %%%%%%%%%%%%%%%%%%%%%%%%%%%
function save_response_txt()

global N_Test_Patterns Log_File_Name last_iter  MSEaveg q_cal N_Output N_Input TEST_INPUT

   mess = sprintf('  Saving to log text file ....( %s )',Log_File_Name);
   disp(mess);
   fid = fopen(Log_File_Name,'w');
   fprintf(fid,'Iteration No.  %d      MSE = %12.9f \n',last_iter, MSEaveg);
   fprintf(fid,'--------------------------------------------\n');
   
for k = 1:N_Test_Patterns
   fprintf(fid,'pattern No. %d: \n',k);
   for i=1:N_Input
      fprintf(fid,'%12.9f ',TEST_INPUT(k,i));
   end
   fprintf(fid,'\n Response: \n');
   for i = 1:N_Output
      fprintf(fid,'%12.9f ',q_cal(k,i));
   end
   fprintf(fid,'\n');       
end
fclose(fid);
%%%%%%%%%%%%%%%%%%%%% end save_response_txt  %%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%% save_response_m  %%%%%%%%%%%%%%%%%%%%%%%%%%%
function save_response_m()

global N_Test_Patterns Temp_Log_File_Name last_iter  MSEaveg q_cal N_Output  

   mess = sprintf('  Saving to log m file ....( %s )',Temp_Log_File_Name);
   disp(mess);
   fid = fopen(Temp_Log_File_Name,'w');
   fprintf(fid,'%%Iteration No.  %d      MSE = %12.9f \n',last_iter, MSEaveg);
   fprintf(fid,'RESPONSE = [\n');
   
for k = 1:N_Test_Patterns
   for i = 1:N_Output
      fprintf(fid,'%12.9f ',q_cal(k,i));
   end
   fprintf(fid,'\n');    
end
fprintf(fid,'];\n');
fclose(fid);
%%%%%%%%%%%%%%%%%%%%% end save_response_m  %%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%************************   end test_rnn_gen.m   ************************%%%