function nnmodref(cmd,arg1,arg2,arg3)
%NNMODREF Neural Network Model Reference Controller GUI for Neural Network Controller Toolbox.
%
%  Synopsis
%
%    nnmodref(cmd,arg1,arg2,arg3)
%
%  Warning!!
%
%    This function may be altered or removed in future
%    releases of the Neural Network Toolbox. We recommend
%    you do not write code which calls this function.
%    This function is generally being called from a Simulink block.

% Orlando De Jesus, Martin Hagan, 1-25-00
% Copyright 1992-2004 The MathWorks, Inc.
% $Revision: 1.7.2.1 $ $Date: 2004/03/24 20:42:49 $


% CONSTANTS
me = 'Model Reference Control';

% DEFAULTS
if nargin == 0, cmd = ''; else cmd = lower(cmd); end

% FIND WINDOW IF IT EXISTS
fig = 0;

% 9/3/99 We alow the program to see hidden handles
fig=findall(0,'type','figure','name',me);
if (size(fig,1)==0), fig=0; end

if length(get(fig,'children')) == 0, fig = 0; end

% GET WINDOW DATA IF IT EXISTS
if fig
  H = get(fig,'userdata');
  
  if strcmp(cmd,'')
    if get(H.gcbh_ptr,'userdata')~=arg1
      delete(fig);
      fig=0;
    end
  else
    if strcmp(cmd,'close')
       delete(fig)
       return;
    end
    % ODJ 1-13-00 We check if the field SimulationStatus exist before reading that field
    if isfield(get(H.gcbh_ptr,'userdata'))
       if isfield(get_param(get_param(get(H.gcbh_ptr,'userdata'),'parent'),'objectparameters'),'SimulationStatus')
          SimulationStatus=get_param(get_param(get(H.gcbh_ptr,'userdata'),'parent'),'simulationstatus');
       else
          SimulationStatus='none';
       end
    else
       SimulationStatus='none';
    end
    if (strcmp(SimulationStatus,'running') | strcmp(SimulationStatus,'paused')) & ~strcmp(cmd,'close')
      set(H.error_messages,'string','You must stop the simulation to change NN configuration parameters.');
      return;
    end
  end
end

%==================================================================
% Activate the window.
%
% ME() or ME('')
%==================================================================

if strcmp(cmd,'')
  if fig
    figure(fig)
    if strcmp(arg3,'nnident')
      set(H.error_messages,'string',sprintf('Generate or import data before training the neural network controller.'));
    else
      set(H.error_messages,'string',sprintf('Perform plant identification before controller training.'));
    end
    set(fig,'visible','on')
  else
    nncontrolutil('nnmodref','init',arg1,arg2,arg3)
  end

%==================================================================
% Close the window.
%
% ME() or ME('')
%==================================================================

elseif strcmp(cmd,'close') & (fig)
   delete(fig)
   return;

elseif strcmp(cmd,'stop_sim')
  fig2=findall(0,'type','figure','tag','ind_adap_data');
  if (size(fig2,1)==0), fig2=0; end
  f2=get(fig2,'userdata');
  f2.stop=1;
  set(fig2,'UserData',f2);
  return;
       
elseif (strcmp(cmd,'apply') | strcmp(cmd,'ok')) & (fig)
  arg1=get(H.gcbh_ptr,'userdata');
  
  epochs_c = get(H.epochs_c_ptr,'userdata');
  set_param(arg1,'epochs_c',num2str(epochs_c));
    
  retraining_c = get(H.retraining_c_ptr,'userdata');
  set_param(arg1,'retraining_c',num2str(retraining_c));
  
  max_r = get(H.max_r_ptr,'userdata');
  set_param(arg1,'max_r',num2str(max_r));
    
  min_r = get(H.min_r_ptr,'userdata');
  set_param(arg1,'min_r',num2str(min_r));
    
  max_r_int = get(H.max_r_int_ptr,'userdata');
  set_param(arg1,'max_r_int',num2str(max_r_int));
    
  min_r_int = get(H.min_r_int_ptr,'userdata');
  set_param(arg1,'min_r_int',num2str(min_r_int));
    
  sam_training_c = get(H.sam_training_c_ptr,'userdata');
  set_param(arg1,'sam_training_c',num2str(sam_training_c));
    
  S1c = get(H.S1c_ptr,'userdata');
  set_param(arg1,'S1c',num2str(S1c));
    
  Ref_file = get(H.Ref_file_ptr,'userdata');
  set_param(arg1,'Ref_file',Ref_file);
  
  Nrc = get(H.Nrc_ptr,'userdata');
  set_param(arg1,'Nrc',num2str(Nrc));
  
  Nic = get(H.Nic_ptr,'userdata');
  set_param(arg1,'Nic',num2str(Nic));
  
  Njc = get(H.Njc_ptr,'userdata');
  set_param(arg1,'Njc',num2str(Njc));
    
  Use_Inc_training = get(H.Use_Inc_training_ptr,'userdata');
  set_param(arg1,'Use_Inc_training',num2str(Use_Inc_training)); 
    
  Use_Previous_Weights = get(H.Use_Previous_Weights_ptr,'userdata');
  set_param(arg1,'Use_Previous_Weights',num2str(Use_Previous_Weights)); 
    
  IW_r = get(H.IW_r_ptr,'userdata');
  IW_u = get(H.IW_u_ptr,'userdata');
  IW_y = get(H.IW_y_ptr,'userdata');
  LW_c = get(H.LW_c_ptr,'userdata');
  B1_c = get(H.B1_c_ptr,'userdata');
  B2_c = get(H.B2_c_ptr,'userdata');
    
  set_param(arg1,'IW_y',mat2str(IW_y,20));  
  set_param(arg1,'IW_u',mat2str(IW_u,20));  
  set_param(arg1,'IW_r',mat2str(IW_r,20));  
  set_param(arg1,'LW_c',mat2str(LW_c,20));  
  set_param(arg1,'B1_c',mat2str(B1_c,20));  
  set_param(arg1,'B2_c',mat2str(B2_c,20));  
  
  if strcmp(cmd,'ok')
     delete(fig)
  end
  
%==================================================================
% Execute Identification Training.
%
% ME('training')
%==================================================================

elseif strcmp(cmd,'training') & (fig)
  arg1=get(H.gcbh_ptr,'userdata');
  arg2=get(H.gcb_ptr,'userdata');
  nnident('',arg1,arg2,'nnmodref');
  
%==================================================================
% Execute Controller Training.
%
% ME('training')
%==================================================================

elseif (strcmp(cmd,'training_con') | strcmp(cmd,'cont_training_con') | strcmp(cmd,'data_ok') | ...
      strcmp(cmd,'gen_data') | strcmp(cmd,'have_file')) & (fig)
  if strcmp(cmd,'gen_data') & (fig)
    H.Data_Imported=0;
    set(fig,'UserData',H);

  elseif strcmp(cmd,'have_file') & (fig)
    ImportStr=arg1;
    H.Data_Imported=1;
    if nargin==3
       Data_Name=arg2;
    else
       U_Name=arg2;
       Y_Name=arg3;
    end
  end
  
  set(H.Train_con,'enable','off')
  set(H.Cancel_but,'enable','off')
  set(H.OK_but,'enable','off')
  set(H.Apply_but,'enable','off')
  set(H.Handles.Menus.File.Save_NN,'enable','off')
  set(H.Handles.Menus.File.Save_Exit_NN,'enable','off')
  
  if (strcmp(cmd,'gen_data') | strcmp(cmd,'have_file'))%strcmp(cmd,'start_training')
    arg1=get(H.gcbh_ptr,'userdata');
  
    a1 = str2num(get(H.max_r_edit,'string'));
    if length(a1) == 0, 
      max_r=get_param(arg1,'max_r'); 
      present_error(fig,H,H.max_r_edit,max_r,1, ...
        'Please correct the maximum reference value');  
      return
    else max_r=a1; set(H.max_r_ptr,'userdata',a1); end
    
    a1 = str2num(get(H.min_r_edit,'string'));
    min_r=get_param(arg1,'min_r'); 
    if length(a1) == 0, 
      present_error(fig,H,H.min_r_edit,min_r,1, ...
        'Please correct the minimum reference value.');  
      return
    elseif a1>=max_r
      present_error(fig,H,H.min_r_edit,min_r,1, ...
        'Please correct the maximum and minimum reference values.');  
      return
    else min_r=a1; set(H.min_r_ptr,'userdata',a1); end
    
    a1 = str2num(get(H.max_r_int_edit,'string'));
    if (length(a1) == 0) | a1<=0, 
      max_r_int=get_param(arg1,'max_r_int'); 
      present_error(fig,H,H.max_r_int_edit,max_r_int,1, ...
        'You must enter a valid number for the maximum interval value over which the random input is constant.');  
      return
    else max_r_int=a1; set(H.max_r_int_ptr,'userdata',a1); end
    
    a1 = str2num(get(H.min_r_int_edit,'string'));
    min_r_int=get_param(arg1,'min_r_int'); 
    if (length(a1) == 0) | a1<=0, 
      present_error(fig,H,H.min_r_int_edit,min_r_int,1, ...
        'You must enter a valid number for the minimum interval value over which the random input is constant.');  
      return
    elseif a1>=max_r_int
      present_error(fig,H,H.min_r_int_edit,min_r_int,1, ...
        'You must enter valid maximum and minimum interval values for constant reference input.');  
      return
    else min_r_int=a1; set(H.min_r_int_ptr,'userdata',a1); end
    
    a1 = str2num(get(H.sam_training_c_edit,'string'));
    if length(a1) == 0, a1=0; end
    if a1<1 | ceil(a1)~=a1, 
      sam_training_c=get_param(arg1,'sam_training_c'); 
      present_error(fig,H,H.sam_training_c_edit,sam_training_c,1, ...
        'Please correct the number of controller training samples.');  
      return
    else sam_training_c=a1; set(H.sam_training_c_ptr,'userdata',a1); end
    
    Ts=get_param(arg1,'Ts'); 
    set(H.Sampling_time,'string',Ts);
    Ts=str2num(Ts);
  
    fig2=findall(0,'type','figure','tag','ind_adap_data');
    if (size(fig2,1)==0), fig2=0; end
    
    if strcmp(cmd,'have_file')
      if nargin==3
        if isempty(ImportStr)   % Workspace
          tr_dat=evalin('base',Data_Name);
          if ~isfield(tr_dat,'.flag')
             tr_dat.flag=ones(size(tr_dat.Y));
          end
          if ~isfield(tr_dat,'.Ts')
             tr_dat.Ts=Ts;
          end
        else
          a1 = ImportStr; 
          a2 = which(cat(2,a1,'.mat'));
          if (length(a1) == 0 | length(a2) == 0), 
             present_error(fig,H,0,0,0, ...
                'You must enter a valid filename for your training data, or the file directory must be defined in the MATLAB Path.'); 
             return
          else file_data=a1; end
          temp=load (file_data,Data_Name);
          tr_dat.U=getfield(temp,Data_Name,'U');
          tr_dat.Y=getfield(temp,Data_Name,'Y');
          if isfield(eval(cat(2,'temp.',Data_Name)),'flag')
             tr_dat.flag=getfield(temp,Data_Name,'flag');
          else
             tr_dat.flag=ones(size(tr_dat.Y));
          end
          if isfield(eval(cat(2,'temp.',Data_Name)),'Ts')
             tr_dat.Ts=getfield(temp,Data_Name,'Ts');
          else
             tr_dat.Ts=Ts;
          end
        end
      else
        if isempty(ImportStr)   % Workspace
          tr_dat=struct('U',evalin('base',U_Name),'Y',evalin('base',Y_Name));
          tr_dat.flag=ones(size(tr_dat.Y));
          tr_dat.Ts=Ts;
        else
          a1 = ImportStr; 
          a2 = which(cat(2,a1,'.mat'));
          if (length(a1) == 0 | length(a2) == 0), 
             present_error(fig,H,0,0,0, ...
                'You must enter a valid filename for your training data, or the file directory must be defined in the MATLAB Path.'); 
             return
          else file_data=a1; end
          temp=load (file_data,U_Name,Y_Name);
          tr_dat.U=getfield(temp,U_Name);
          tr_dat.Y=getfield(temp,Y_Name);
          tr_dat.flag=ones(size(tr_dat.Y));
          tr_dat.Ts=Ts;
        end
      end
      
      % We verify direction of the input vectors.
      if size(tr_dat.U,1)<=1
         tr_dat.U=tr_dat.U';
      end
      if size(tr_dat.Y,1)<=1
         tr_dat.Y=tr_dat.Y';
      end
      if size(tr_dat.flag,1)<=1
         tr_dat.flag=tr_dat.flag';
      end
      sam_training_c=size(tr_dat.Y,1)-1;
      
      if fig2==0
        pos_fig2=get(fig,'Position');
        fig2 = figure('Units',          'points',...
                 'Interruptible','off', ...
                 'BusyAction','cancel', ...
                 'HandleVis','Callback', ...
                 'Name',           'Input-Output Data for NN Model Reference Control',...
                 'Tag',            'ind_adap_data',...
                 'NumberTitle',    'off',...
                 'Position',       pos_fig2, ...
                 'IntegerHandle',  'off',...
                 'Toolbar',        'none', ...
                'WindowStyle','modal');
        f2.h1=axes('Position',[0.13 0.60 0.74 0.32],'Parent',fig2);
        f2.h2=axes('Position',[0.13 0.15 0.74 0.32],'Parent',fig2);
        f2.message= uicontrol('Parent',fig2, ...
                                 'Units','points', ...
                                 'BackgroundColor',[0.752941176470588 0.752941176470588 0.752941176470588], ...
                                 'FontWeight','bold', ...