diff toolboxes/FullBNT-1.0.7/netlab3.3/demtrain.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/netlab3.3/demtrain.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,362 @@
+function demtrain(action);
+%DEMTRAIN Demonstrate training of MLP network.
+%
+%	Description
+%	DEMTRAIN brings up a simple GUI to show the training of an MLP
+%	network on classification and regression problems.  The user should
+%	load in a dataset (which should be in Netlab format: see  DATREAD),
+%	select the output activation function, the  number of cycles and
+%	hidden units and then train the network. The scaled conjugate
+%	gradient algorithm is used. A graph shows the evolution of the error:
+%	the value is shown  MAX(CEIL(ITERATIONS / 50), 5) cycles.
+%
+%	Once the network is trained, it is saved to the file MLPTRAIN.NET.
+%	The results can then be viewed as a confusion matrix (for
+%	classification problems) or a plot of output versus target (for
+%	regression problems).
+%
+%	See also
+%	CONFMAT, DATREAD, MLP, NETOPT, SCG
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+% If run without parameters, initialise gui.
+if nargin<1,
+  action='initialise';
+end;
+
+% Global variable to reference GUI figure
+global DEMTRAIN_FIG
+% Global array to reference sub-figures for results plots
+global DEMTRAIN_RES_FIGS
+global NUM_DEMTRAIN_RES_FIGS
+
+if strcmp(action,'initialise'),
+
+  file = '';
+  path = '.';
+  
+  % Create FIGURE
+  fig = figure( ...
+	'Name', 'Netlab Demo', ...
+	'NumberTitle', 'off', ...
+	'Menubar', 'none', ...
+	'Color', [0.7529 0.7529 0.7529], ...
+	'Visible', 'on');
+  % Initialise the globals
+  DEMTRAIN_FIG = fig;
+  DEMTRAIN_RES_FIGS = 0;
+  NUM_DEMTRAIN_RES_FIGS = 0;
+
+  % Create GROUP for buttons
+  uicontrol(fig, ...
+	'Style', 'frame', ...
+	'Units', 'normalized', ...
+	'Position', [0.03 0.08 0.94 0.22], ...
+	'BackgroundColor', [0.5 0.5 0.5]);
+
+  % Create MAIN axis
+  hMain = axes( ...
+	'Units', 'normalized', ...
+	'Position', [0.10 0.5 0.80 0.40], ...
+	'XColor', [0 0 0], ...
+	'YColor', [0 0 0], ...
+	'Visible', 'on');
+
+  % Create static text for FILENAME and PATH
+  hFilename = uicontrol(fig, ...
+	'Style', 'text', ...
+	'Units', 'normalized', ...
+	'BackgroundColor', [0.7529 0.7529 0.7529], ...
+	'Position', [0.05 0.32 0.90 0.05], ...
+	'HorizontalAlignment', 'center', ...
+	'String', 'Please load data file.', ...
+	'Visible', 'on');
+  hPath = uicontrol(fig, ...
+	'Style', 'text', ...
+	'Units', 'normalized', ...
+	'BackgroundColor', [0.7529 0.7529 0.7529], ...
+	'Position', [0.05 0.37 0.90 0.05], ...
+	'HorizontalAlignment', 'center', ...
+	'String', '', ...
+	'Visible', 'on');
+
+  % Create NO OF HIDDEN UNITS slider and text
+  hSliderText = uicontrol(fig, ...
+	'Style', 'text', ...
+	'BackgroundColor', [0.5 0.5 0.5], ...
+	'Units', 'normalized', ...
+	'Position', [0.27 0.12 0.17 0.04], ...
+	'HorizontalAlignment', 'right', ...
+	'String', 'Hidden Units: 5');
+  hSlider = uicontrol(fig, ...
+	'Style', 'slider', ...
+	'Units', 'normalized', ...
+	'Position', [0.45 0.12 0.26 0.04], ...
+	'String', 'Slider', ...
+	'Min', 1, 'Max', 25, ...
+	'Value', 5, ...
+	'Callback', 'demtrain slider_moved');
+
+  % Create ITERATIONS slider and text
+  hIterationsText = uicontrol(fig, ...
+	'Style', 'text', ...
+	'BackgroundColor', [0.5 0.5 0.5], ...
+	'Units', 'normalized', ...
+	'Position', [0.27 0.21 0.17 0.04], ...
+	'HorizontalAlignment', 'right', ...
+	'String', 'Iterations: 50');
+  hIterations = uicontrol(fig, ...
+	'Style', 'slider', ...
+	'Units', 'normalized', ...
+	'Position', [0.45 0.21 0.26 0.04], ...
+	'String', 'Slider', ...
+	'Min', 10, 'Max', 500, ...
+	'Value', 50, ...
+	'Callback', 'demtrain iterations_moved');
+
+  % Create ACTIVATION FUNCTION popup and text
+  uicontrol(fig, ...
+	'Style', 'text', ...
+	'BackgroundColor', [0.5 0.5 0.5], ...
+	'Units', 'normalized', ...
+	'Position', [0.05 0.20 0.20 0.04], ...
+	'HorizontalAlignment', 'center', ...
+	'String', 'Activation Function:');
+  hPopup = uicontrol(fig, ...
+	'Style', 'popup', ...
+	'Units', 'normalized', ...
+	'Position' , [0.05 0.10 0.20 0.08], ...
+	'String', 'Linear|Logistic|Softmax', ...
+	'Callback', '');
+
+  % Create MENU
+  hMenu1 = uimenu('Label', 'Load Data file...', 'Callback', '');
+  uimenu(hMenu1, 'Label', 'Select training data file', ...
+	'Callback', 'demtrain get_ip_file');
+  hMenu2 = uimenu('Label', 'Show Results...', 'Callback', '');
+  uimenu(hMenu2, 'Label', 'Show classification results', ...
+	'Callback', 'demtrain classify');
+  uimenu(hMenu2, 'Label', 'Show regression results', ...
+	'Callback', 'demtrain predict');
+  
+  % Create START button
+  hStart = uicontrol(fig, ...
+	'Units', 'normalized', ...
+	'Position' , [0.75 0.2 0.20 0.08], ...
+	'String', 'Start Training', ...
+	'Enable', 'off',...
+	'Callback', 'demtrain start');
+
+  % Create CLOSE button
+  uicontrol(fig, ...
+	'Units', 'normalized', ...
+	'Position' , [0.75 0.1 0.20 0.08], ...
+	'String', 'Close', ...
+	'Callback', 'demtrain close');
+
+  % Save handles of important UI objects
+  hndlList = [hSlider hSliderText hFilename hPath hPopup ...
+      hIterations hIterationsText hStart];
+  set(fig, 'UserData', hndlList);
+  % Hide window from command line
+  set(fig, 'HandleVisibility', 'callback');
+
+  
+elseif strcmp(action, 'slider_moved'),
+
+  % Slider has been moved. 
+  
+  hndlList = get(gcf, 'UserData');
+  hSlider = hndlList(1);
+  hSliderText = hndlList(2);
+
+  val = get(hSlider, 'Value');
+  if rem(val, 1) < 0.5,  % Force up and down arrows to work!
+	val = ceil(val);
+  else
+	val = floor(val);
+  end;
+  set(hSlider, 'Value', val);
+  set(hSliderText, 'String', ['Hidden Units: ' int2str(val)]);
+
+  
+elseif strcmp(action, 'iterations_moved'),
+
+  % Slider has been moved. 
+  
+  hndlList = get(gcf, 'UserData');
+  hSlider = hndlList(6);
+  hSliderText = hndlList(7);
+
+  val = get(hSlider, 'Value');
+  set(hSliderText, 'String', ['Iterations: ' int2str(val)]);
+
+elseif strcmp(action, 'get_ip_file'),
+
+  % Get data file button pressed.
+  
+  hndlList = get(gcf, 'UserData');
+
+  [file, path] = uigetfile('*.dat', 'Get Data File', 50, 50);
+
+  if strcmp(file, '') | file == 0,
+    set(hndlList(3), 'String', 'No data file loaded.');
+    set(hndlList(4), 'String', '');
+  else
+    set(hndlList(3), 'String', file);
+    set(hndlList(4), 'String', path);
+  end;
+  
+  % Enable training button
+  set(hndlList(8), 'Enable', 'on');
+
+  set(gcf, 'UserData', hndlList);
+  
+elseif strcmp(action, 'start'),
+
+  % Start training
+  
+  % Get handles of and values from UI objects
+  hndlList = get(gcf, 'UserData');
+  hSlider = hndlList(1); % 				No of hidden units
+  hIterations = hndlList(6); 
+  iterations = get(hIterations, 'Value');
+  
+  hFilename = hndlList(3);	% 			Data file name
+  filename = get(hFilename, 'String');
+
+  hPath = hndlList(4);	% 				Data file path
+  path = get(hPath, 'String');
+
+  hPopup = hndlList(5);		% 			Activation function
+  if get(hPopup, 'Value') == 1,
+	act_fn = 'linear';
+  elseif get(hPopup, 'Value') == 2,
+	act_fn = 'logistic';
+  else
+	act_fn = 'softmax';
+  end;
+  nhidden = get(hSlider, 'Value');
+
+  % Check data file exists
+  if fopen([path '/' filename]) == -1,
+	errordlg('Training data file has not been selected.', 'Error');
+  else
+	% Load data file
+	[x,t,nin,nout,ndata] = datread([path filename]);
+	
+	% Call MLPTRAIN function repeatedly, while drawing training graph.
+	figure(DEMTRAIN_FIG);
+	hold on;
+	
+	title('Training - please wait.');
+	
+	% Create net and find initial error
+	net = mlp(size(x, 2), nhidden, size(t, 2), act_fn);
+	% Initialise network with inverse variance of 10
+	net = mlpinit(net, 10);
+	error = mlperr(net, x, t);
+	% Work out reporting step: should be sufficiently big to let training
+	% algorithm have a chance
+	step = max(ceil(iterations / 50), 5);
+
+	% Refresh and rescale axis.
+	cla;
+	max = error;
+	min = max/10;
+	set(gca, 'YScale', 'log');
+	ylabel('log Error');
+	xlabel('No. iterations');
+	axis([0 iterations min max+1]);
+	iold = 0;
+	errold = error;
+	% Plot circle to show error of last iteration
+	% Setting erase mode to none prevents screen flashing during 
+	% training
+	plot(0, error, 'ro', 'EraseMode', 'none');
+	hold on
+	drawnow; % Force redraw
+	for i = step-1:step:iterations,
+	  [net, error] = mlptrain(net, x, t, step);
+	  % Plot line from last point to new point.
+	  line([iold i], [errold error], 'Color', 'r', 'EraseMode', 'none');
+	  iold = i;
+	  errold = error;
+	  
+	  % If new point off scale, redraw axes.
+	  if error > max,
+	    max = error;
+	    axis([0 iterations min max+1]);
+	  end;
+	  if error < min
+	    min = error/10;
+	    axis([0 iterations min max+1]);
+	  end
+	  % Plot circle to show error of last iteration
+	  plot(i, error, 'ro', 'EraseMode', 'none');
+	  drawnow; % Force redraw
+	end;
+	save mlptrain.net net
+	zoom on;
+
+	title(['Training complete. Final error=', num2str(error)]);
+	
+  end;
+
+elseif strcmp(action, 'close'),
+  
+  % Close all the figures we have created
+  close(DEMTRAIN_FIG);
+  for n = 1:NUM_DEMTRAIN_RES_FIGS
+    if ishandle(DEMTRAIN_RES_FIGS(n))
+      close(DEMTRAIN_RES_FIGS(n));
+    end
+  end
+
+elseif strcmp(action, 'classify'),
+  
+  if fopen('mlptrain.net') == -1,
+	errordlg('You have not yet trained the network.', 'Error');
+  else
+  
+	hndlList = get(gcf, 'UserData');
+	filename = get(hndlList(3), 'String');
+	path = get(hndlList(4), 'String');
+	[x,t,nin,nout,ndata] = datread([path filename]);
+	load mlptrain.net net -mat
+	y = mlpfwd(net, x);
+	
+	% Save results figure so that it can be closed later
+	NUM_DEMTRAIN_RES_FIGS = NUM_DEMTRAIN_RES_FIGS + 1;
+	DEMTRAIN_RES_FIGS(NUM_DEMTRAIN_RES_FIGS)=conffig(y,t);
+	
+  end;
+
+elseif strcmp(action, 'predict'),
+  
+  if fopen('mlptrain.net') == -1,
+	errordlg('You have not yet trained the network.', 'Error');
+  else
+  
+	hndlList = get(gcf, 'UserData');
+	filename = get(hndlList(3), 'String');
+	path = get(hndlList(4), 'String');
+	[x,t,nin,nout,ndata] = datread([path filename]);
+	load mlptrain.net net -mat
+	y = mlpfwd(net, x);
+	
+	for i = 1:size(y,2),
+	  % Save results figure so that it can be closed later
+	  NUM_DEMTRAIN_RES_FIGS = NUM_DEMTRAIN_RES_FIGS + 1;
+	  DEMTRAIN_RES_FIGS(NUM_DEMTRAIN_RES_FIGS) = figure;
+	  hold on;
+	  title(['Output no ' num2str(i)]);
+	  plot([0 1], [0 1], 'r:');
+	  plot(y(:,i),t(:,i), 'o');
+	  hold off;
+	end;
+  end;
+	
+end;
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