nnd12rp.m

matlab在神经网络中的一些界面函数

function nnd12rp(cmd,arg1)
%NND12RP Resilient backpropagation demonstration.
%
%       This demonstration requires the Neural Network Toolbox.

% First Version, 7-25-96.

%==================================================================

% Constants for RPROP
delt0 = 1; % Initial step size;
deltmax = 50; % Maximum step size;
etapos = 1.1; % factor for increasing step size;
etaneg = 0.8; % factor for decreasing step size;

% CONSTANTS
me = 'nnd12rp';
max_epoch = 50;
max_t = 0.5;
w_max = 10;
p_max = 2;
circle_size = 6;

% FLAGS
change_func = 0;

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

% FIND WINDOW IF IT EXISTS
fig = nnfgflag(me);
if length(get(fig,'children')) == 0, fig = 0; end

% GET WINDOW DATA IF IT EXISTS
if fig
  H = get(fig,'userdata');
  fig_axis = H(1);            % window axis
  desc_text = H(2);           % handle to first line of text sequence
  cont_axis = H(3);           % error contour axis
  cont_ptr = H(4);            % pointer to error contour handles
  radios = H(5:7);          % radio buttons
  option_ptr = H(8);         % index of active radio
  path_ptr = H(9);           % pointer to training path handles
end

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

if strcmp(cmd,'')
  if fig
    figure(fig)
    set(fig,'visible','on')
  else
    feval(me,'init')
  end

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

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

%==================================================================
% Initialize the window.
%
% ME('init')
%==================================================================

elseif strcmp(cmd,'init') & (~fig)

  % CHECK FOR NNT
  if ~nntexist(me), return, end

  % CONSTANTS
  W1 = [10; 10];
  b1 = [-5;5];
  W2 = [1 1];
  b2 = [-1];
  P = -2:0.1:2;
  T = logsig(W2*logsig(W1*P,b1),b2);

  % NEW DEMO FIGURE
  fig = nndemof2(me,'DESIGN','Resilient Backpropagation','','Chapter 12');
  set(fig, ...
    'windowbuttondownfcn',nncallbk(me,'down'), ...
    'BackingStore','off',...
    'nextplot','add');
  H = get(fig,'userdata');
  fig_axis = H(1);
  desc_text = H(2);

  % ICON
  nndicon(12,458,363,'shadow')

  % RADIO BUTTONS
  option = 1;
  radio1 = uicontrol(...
    'units','points',...
    'position',[20 335 130 20],...
    'style','radio',...
    'string','W1(1,1), W2(1,1)',...
    'back',nnltgray,...
    'callback',[me '(''radio'',1)'],...
    'value',1);
  radio2 = uicontrol(...
    'units','points',...
    'position',[155 335 115 20],...
    'style','radio',...
    'string','W1(1,1), b1(1)',...
    'back',nnltgray,...
    'callback',[me '(''radio'',2)']);
  radio3 = uicontrol(...
    'units','points',...
    'position',[270 335 105 20],...
    'style','radio',...
    'string','b1(1), b1(2)',...
    'back',nnltgray,...
    'callback',[me '(''radio'',3)']);

  % ERROR SURFACE
  load nndbp1

  cont_axis = nnsfo('a2','',v1,v2,'');
  set(cont_axis, ...
    'units','points',...
    'position',[50 40 280 280],...
    'color',nnltyell,...
    'xlim',range1,...
    'ylim',range2,...
    'colororder',[0 0 0])
  [dummy,cont_h] = contour(x2,y2,E2,levels);
  set(cont_h,'erasemode','none');
  plot3(range1([1 2 2 1 1]),range2([1 1 2 2 1]),1000*ones(1,5),...
    'color',nndkblue);
  cont_h2 = plot(optx,opty,'+','color',nnred);
  cont_h = [cont_h; cont_h2];
  view(2)

  % BUTTONS
  uicontrol(...
    'units','points',...
    'position',[400 110 60 20],...
    'string','Contents',...
    'callback','nndtoc')
  uicontrol(...
    'units','points',...
    'position',[400 75 60 20],...
    'string','Close',...
    'callback',[me '(''close'')'])

  % DATA POINTERS
  cont_ptr = uicontrol('visible','off','userdata',cont_h);
  option_ptr = uicontrol('visible','off','userdata',option);
  path_ptr = uicontrol('visible','off','userdata',[]);

  % SAVE WINDOW DATA AND LOCK
  H = [fig_axis desc_text cont_axis cont_ptr ...
       radio1 radio2 radio3 option_ptr path_ptr];
  set(fig,'userdata',H,'nextplot','new')

  % INSTRUCTION TEXT
  feval(me,'instr');

  % LOCK WINDOW
  set(fig,'nextplot','new','color',nnltgray);

  nnchkfs;

%==================================================================
% Display the instructions.
%
% ME('instr')
%==================================================================

elseif strcmp(cmd,'instr') & (fig)
  nnsettxt(desc_text,...
    'Use the radio buttons',...
    'to select the network',...
    'parameters to train',...
    'with backpropagation.',...
    '',...
    'The corresponding',...
    'contour plot is',...
    'shown to the left.',...
    '',...
    'Click in the contour',...
    'graph to start the',...
    'conjugate gradient',...
    'learning algorithm.')

%==================================================================
% Respond to radio buttons.
%
% ME('radio',i)
%==================================================================

elseif strcmp(cmd,'radio') & (fig) & (nargin == 2)

  % GET DATA
  option = get(option_ptr,'userdata');

  % ALTER TRAINABLE PARAMETERS
  if (arg1 ~= option)

    % HIGHLIGHT NEW RADIO BUTTON
    set(radios(option),'value',0)
    set(radios(arg1),'value',1)
    option = arg1;

    % CLEAR AXES
    delete(get(cont_axis,'children'))

    % CONSTANTS
    W1 = [10; 10];
    b1 = [-5;5];
    W2 = [1 1];
    b2 = [-1];
    P = -2:0.1:2;
    T = logsig(W2*logsig(W1*P,b1),b2);

    % ERROR SURFACE & VARIABLE NAMES
    if option == 1
      load nndbp1
    elseif option == 2
      load nndbp2
    else
      load nndbp3
    end

    set(fig,'nextplot','add')
    axes(cont_axis)
    set(get(cont_axis,'xlabel'),'string',v1)
    set(get(cont_axis,'ylabel'),'string',v2)
    set(cont_axis,'xlim',range1,'ylim',range2)
    [dummy,cont_h] = contour(x2,y2,E2,levels);
    set(cont_h,'erasemode','none');
    plot3(range1([1 2 2 1 1]),range2([1 1 2 2 1]),1000*ones(1,5),...
      'color',nndkblue);
    cont_h2 = plot(optx,opty,'+','color',nnred);
    cont_h = [cont_h; cont_h2];
    view(2)

    % STORE DATA
    set(cont_ptr,'userdata',cont_h);
    set(path_ptr,'userdata',[]);
    set(option_ptr,'userdata',option);
  end

%==================================================================
% Respond to mouse down.
%
% ME('down')
%==================================================================

elseif strcmp(cmd,'down') & (fig) & (nargin == 1)

  pt = get(cont_axis,'currentpoint');

  x = pt(1);
  y = pt(3);
  xlim = get(cont_axis,'xlim');
  ylim = get(cont_axis,'ylim');

  if (x > xlim(1) & x < xlim(2) & y > ylim(1) & y < ylim(2))

    % GET DATA
    option = get(option_ptr,'userdata');
    path = get(path_ptr,'userdata');
    cont_h = get(cont_ptr,'userdata');

    % REMOVE PREVIOUS PATH
    set(fig,'nextplot','add')
    set(path,'erasemode','normal');
    delete(path);

    % INITIAL VALUES
    W1 = [10; 10];
    b1 = [-5;5];
    W2 = [1 1];
    b2 = [-1];
    P = -2:0.1:2;
    T = logsig(W2*logsig(W1*P,b1),b2);

    % PLOT START POINT
    dkblue = nndkblue;
    red = nnred;
    axes(cont_axis);
    path = [...
      plot(x,y,'o','color',dkblue,'markersize',8,'erasemode','none');
      plot(x,y,'o','color',[1 1 1],'markersize',10,'erasemode','none');
      plot(x,y,'o','color',dkblue,'markersize',12,'erasemode','none')];
    drawnow

    % PLOT PATH
    set(fig,'pointer','watch')

    % INITIALIZE TRAINING
    Lx = x;
    Ly = y;
    if option == 1
      W1(1,1) = x;
      W2(1,1) = y;
    elseif option == 2
      W1(1,1) = x;
      b1(1) = y;
    else
      b1(1) = x;
      b1(2) = y;
    end
%--
deltW = [0;0];
W = [x;y];
deltMAX = [deltmax;deltmax];


    % MAIN LOOP
    xx = [x zeros(1,max_epoch)];
    yy = [y zeros(1,max_epoch)];
    for i=2:(max_epoch+1)

      % CALCULATE GRADIENT
      A1 = logsig(W1*P,b1);
      A2 = logsig(W2*A1,b2);
      E = T-A2;
      D2 = feval('deltalog',A2,E);
      D1 = feval('deltalog',A1,D2,W2);
      [gW1,gb1] = feval('learnbp',P,D1,1);
      [gW2,gb2] = feval('learnbp',A1,D2,1);

      if (option == 1)
        dW = [gW1(1,1);gW2(1,1)];
      elseif(option == 2)
        dW = [gW1(1,1);gb1(1)];
      else
        dW = [gb1(1);gb1(2)];
      end

        % RPROP calculation of changes to W and B
        sig = sign(dW.*deltW);
        delt = ((sig>0).*etapos + (sig<0).*etaneg + (sig==0)).*abs(deltW);
        delt = min(delt,deltMAX) + delt0.*(deltW==0);
        deltW = delt.*(sign(dW));

        % Update weights and biases
        W = W + deltW;

      % UPDATE VARIABLES
      if (option == 1)
        W1(1,1) = W(1);
        W2(1,1) = W(2);
      elseif(option == 2)
        W1(1,1) = W(1);
        b1(1)   = W(2);
      else
        b1(1) = W(1);
        b1(2) = W(2);
      end
      xx(i) = W(1);
      yy(i) = W(2);

     end

    % CONTOUR PLOT
    path = [path; plot(xx,yy,'color',nnred);
plot(xx,yy,'o','color',nnred,'markersize',6)];
    set(fig,'nextplot','new')

    % SAVE DATA
    set(path_ptr,'userdata',path);
    set(fig,'pointer','arrow')

  end
end