wolffd@0: function fh=hme_class_plot(net, nodes_info, train_data, test_data)
wolffd@0: % 
wolffd@0: % Use this function ONLY when the input dimension is 2
wolffd@0: % and the problem is a classification one.
wolffd@0: % We assume that each row of 'train_data' & 'test_data' is an example.
wolffd@0: %
wolffd@0: %------Line Spec------------------------------------------------------------------------
wolffd@0: %
wolffd@0: % LineWidth       - specifies the width (in points) of the line
wolffd@0: % MarkerEdgeColor - specifies the color of the marker or the edge color
wolffd@0: %                   forfilled markers (circle, square, diamond, pentagram, hexagram, and the
wolffd@0: %                   four triangles).
wolffd@0: % MarkerFaceColor - specifies the color of the face of filled markers.
wolffd@0: % MarkerSize      - specifies the size of the marker in points.
wolffd@0: %
wolffd@0: % Example
wolffd@0: % -------
wolffd@0: % plot(t,sin(2*t),'-mo',...
wolffd@0: %                'LineWidth',2,...
wolffd@0: %                'MarkerEdgeColor','k',...                          % 'k'=black
wolffd@0: %                'MarkerFaceColor',[.49 1 .63],...                  % RGB color
wolffd@0: %                'MarkerSize',12)
wolffd@0: %----------------------------------------------------------------------------------------
wolffd@0: 
wolffd@0: class_num=nodes_info(2,end);
wolffd@0: mn_x = round(min(train_data(:,1)));     mx_x = round(max(train_data(:,1)));
wolffd@0: mn_y = round(min(train_data(:,2)));     mx_y = round(max(train_data(:,2)));
wolffd@0: if nargin==4,
wolffd@0:     mn_x = round(min([train_data(:,1); test_data(:,1)]));     
wolffd@0:     mx_x = round(max([train_data(:,1); test_data(:,1)]));
wolffd@0:     mn_y = round(min([train_data(:,2); test_data(:,2)]));
wolffd@0:     mx_y = round(max([train_data(:,1); test_data(:,2)]));
wolffd@0: end
wolffd@0: x = mn_x(1)-1:0.2:mx_x(1)+1;
wolffd@0: y = mn_y(1)-1:0.2:mx_y(1)+1;
wolffd@0: [X, Y] = meshgrid(x,y);
wolffd@0: X = X(:); 
wolffd@0: Y = Y(:);
wolffd@0: num_g=size(X,1);
wolffd@0: griglia = [X Y];
wolffd@0: rand('state',1);
wolffd@0: if class_num<=6,
wolffd@0:     colors=['r'; 'g'; 'b'; 'c'; 'm'; 'y'];
wolffd@0: else
wolffd@0:     colors=rand(class_num, 3);  % each row is an RGB color
wolffd@0: end
wolffd@0: fh = figure('Name','Data & decision boundaries', 'MenuBar', 'none', 'NumberTitle', 'off');
wolffd@0: ms=5;           % Marker Size
wolffd@0: if nargin==4,
wolffd@0: %    ms=4;       % Marker Size
wolffd@0:     subplot(1,2,1);
wolffd@0: end
wolffd@0: % Plot of train_set -------------------------------------------------------------------------
wolffd@0: axis([mn_x-1 mx_x+1 mn_y-1 mx_y+1]);
wolffd@0: set(gca, 'Box', 'on');
wolffd@0: c_max_train = max(train_data(:,3));
wolffd@0: hold on
wolffd@0: for m=1:c_max_train,
wolffd@0:     app_x=train_data(:,1);
wolffd@0:     app_y=train_data(:,2);
wolffd@0:     thisX=app_x(train_data(:,3)==m);
wolffd@0:     thisY=app_y(train_data(:,3)==m);
wolffd@0:     if class_num<=6,
wolffd@0:        str_col=[];
wolffd@0:        str_col=['o', colors(m,:)];
wolffd@0:        plot(thisX, thisY, str_col, 'MarkerSize', ms);
wolffd@0:     else
wolffd@0:         plot(thisX, thisY, 'o',...
wolffd@0:             'LineWidth', 1,...            
wolffd@0:             'MarkerEdgeColor', colors(m,:), 'MarkerSize', ms)
wolffd@0:     end
wolffd@0: end
wolffd@0: %---hmefwd_generale(net,data,ndata)-----------------------------------------------------------
wolffd@0: Z=fhme(net, nodes_info, griglia, num_g);      % forward propagation trougth the HME
wolffd@0: %---------------------------------------------------------------------------------------------
wolffd@0: [foo , class] = max(Z'); % 0/1 loss function => we assume that the true class is the one with the
wolffd@0:                          % maximum posterior prob.
wolffd@0: class = class';
wolffd@0: for m = 1:class_num,
wolffd@0:   thisX=[]; thisY=[];
wolffd@0:   thisX = X(class == m);
wolffd@0:   thisY = Y(class == m);
wolffd@0:   if class_num<=6,
wolffd@0:       str_col=[];
wolffd@0:       str_col=['d', colors(m,:)];
wolffd@0:       h=plot(thisX, thisY, str_col);      
wolffd@0:   else
wolffd@0:       h = plot(thisX, thisY, 'd',...
wolffd@0:           'MarkerEdgeColor',colors(m,:),...
wolffd@0:           'MarkerFaceColor','w');
wolffd@0:   end
wolffd@0:   set(h, 'MarkerSize', 4);
wolffd@0: end
wolffd@0: title('Training set and Decision Boundaries (0/1 loss)')
wolffd@0: hold off
wolffd@0: 
wolffd@0: % Plot of test_set --------------------------------------------------------------------------
wolffd@0: if nargin==4,
wolffd@0:     subplot(1,2,2);
wolffd@0:     axis([mn_x-1 mx_x+1 mn_y-1 mx_y+1]);
wolffd@0:     set(gca, 'Box', 'on');
wolffd@0:     hold on     
wolffd@0:     if size(test_data,2)==3,  % we know the classification of the test set examples
wolffd@0:         c_max_test = max(test_data(:,3));
wolffd@0:         for m=1:c_max_test,
wolffd@0:             app_x=test_data(:,1);
wolffd@0:             app_y=test_data(:,2);
wolffd@0:             thisX=app_x(test_data(:,3)==m);
wolffd@0:             thisY=app_y(test_data(:,3)==m);
wolffd@0:             if class_num<=6,
wolffd@0:                 str_col=[];
wolffd@0:                 str_col=['o', colors(m,:)];
wolffd@0:                 plot(thisX, thisY, str_col, 'MarkerSize', ms);
wolffd@0:             else
wolffd@0:                 plot(thisX, thisY, 'o',...
wolffd@0:                      'LineWidth', 1,...
wolffd@0:                      'MarkerEdgeColor', colors(m,:),...
wolffd@0:                      'MarkerSize',ms);
wolffd@0:             end
wolffd@0:         end
wolffd@0:     else
wolffd@0:         plot(test_data(:,1), test_data(:,2), 'ko',...
wolffd@0:             'MarkerSize', ms);
wolffd@0:     end
wolffd@0:     for m = 1:class_num,
wolffd@0:         thisX=[]; thisY=[];
wolffd@0:         thisX = X(class == m);
wolffd@0:         thisY = Y(class == m);
wolffd@0:         if class_num<=6,
wolffd@0:           str_col=[];
wolffd@0:           str_col=['d', colors(m,:)];
wolffd@0:           h=plot(thisX, thisY, str_col);  
wolffd@0:         else
wolffd@0:            h = plot(thisX, thisY, 'd',...
wolffd@0:                     'MarkerEdgeColor', colors(m,:),...
wolffd@0:                     'MarkerFaceColor','w');
wolffd@0:         end
wolffd@0:         set(h, 'MarkerSize', 4);
wolffd@0:     end
wolffd@0:     title('Test set and Decision Boundaries (0/1 loss)')
wolffd@0:     hold off
wolffd@0: end