plotc.m

模式识别工具箱。非常丰富的底层函数和常见的统计识别工具

%PLOTC Plot classifiers
% 
%   PLOTC(W,S,LINE_WIDTH)
%   PLOTC(W,LINE_WIDTH,S)
% 
% Plots the discriminant as given by the mapping W on predefined axis,
% typically set by scatterd. Discriminants are defined by the points
% where class differences for mapping values are zero. 
%
% S is the plot string, e.g. S = 'b--'. In case S = 'col' a color plot is
% produced filling the regions of different classes with different colors.
% Default S = 'k-';
%
% LINE_WIDTH sets the width of the lines and box. Default LINE_WIDTH = 1.5
%
% In W a cell array of classifiers may be given. In S a set of plot strings
% of appropriate size may be given. Automatically a legend is added to
% the plot.
% 
% The linear gridsize is read from the global parameter GRIDSIZE, 
% default GRIDSIZE = 30.
% 
% See also MAPPINGS, SCATTERD, PLOTM
% Examples in PREX_CONFMAT, PREX_PLOTC

% Copyright: R.P.W. Duin, [e-mail]
% Faculty of Applied Sciences, Delft University of Technology
% P.O. Box 5046, 2600 GA Delft, The Netherlands

% $Id: plotc.m,v 1.4 2008/03/06 05:08:43 duin Exp $


function handle = plotc(w,varargin)

	prtrace(mfilename);

	linew = 1.5;
	s = [];

	if nargin < 1 | isempty(w)
		handle = mapping(mfilename,'combiner',s);
		return
	end

	% Extract the plotwidth and linewidth:
	for j = 1:nargin-1
		if isstr(varargin{j})
			s = varargin{j}; 
		else
			linew = varargin{j}; 
		end
	end

	ss = char('k-','r-','b-','m-','k--','r--','b--','m--');
	ss = char(ss,'k-.','r-.','b-.','m-.','k:','r:','b:','m:');

	% When we want to plot a list of classifiers, we set up different
	% plot strings ss and call plotc several times.
	if iscell(w)
		w = w(:);
		n = length(w);
		names = [];
		% Check if sufficient plotstrings are available
		if ~isempty(s)
			if size(s,1) == 1
				s = repmat(s,n,1);
			elseif size(s,1) ~= n
				error('Wrong number of plot strings')
			end
		else
			s = ss(1:n,:);
		end
		% Plot the individual boundaries by calling 'mfilename' (i.e. this
		% function again)
		names = [];
		hh = [];
		for i=1:n
			h = feval(mfilename,w{i},deblank(s(i,:)),linew);
			hh = [hh h(1)];
			names = char(names,getname(w{i}));
		end
		% Finally fix the legend:
		names(1,:) = [];
		legend(hh,names,0);
		if nargout > 0
			handle = hh;
		end
		return
	end

	% Now the task is to plot a single boundary (multiple boundaries are
	% already covered above):
	if ~isa(w,'mapping') | ~istrained(w)
		error('Trained classifier expected')
	end

	[k,c] = size(w);
	c = max(c,2);
	if nargin < 2 | isempty(s)  % default plot string
		s = 1;
	end
	%DXD: Stop when the classifier is not in 2D:
	if (k~=2)
		error('Plotc can only plot classifiers operating in 2D.');
	end

	if ~isstr(s)
		if s > 16 | s < 1
			error('Plotstring undefined')
		else
			s = deblank(ss(s,:));
		end
	end
	% Get the figure size from the current figure:
	hold on
	V=axis;
	hh = [];
	set(gca,'linewidth',linew)

	% linear discriminant
	if isaffine(w) & c == 2 & ~strcmp(s,'col')	% plot as vector
		d = +w;
		n = size(d.rot,2);
		if n == 2, n = 1; end
		for i = 1:n
			w1 = d.rot(:,i); w0 = d.offset(i);
			J = find(w1==0);
			if ~isempty(J)
				w1(J) = repmat(realmin,size(J));
			end
			x = sort([V(1),V(2),(-w1(2)*V(3)-w0)/w1(1),(-w1(2)*V(4)-w0)/w1(1)]);
			x = x(2:3);
			y = (-w1(1)*x-w0)/w1(2);
			h = plot(x,y,s);
			set(h,'linewidth',linew)
			hh = [hh h];
		end
	else    % general case: find contour(0)
		% First define the mesh grid:
		n = gridsize;
		m = (n+1)*(n+1);
		dx = (V(2)-V(1))/n;
		dy = (V(4)-V(3))/n;
		[X Y] = meshgrid(V(1):dx:V(2),V(3):dy:V(4));
		D = double([X(:),Y(:),zeros(m,k-2)]*w);
		if min(D(:)) >=0, D = log(D+realmin); end  % avoid infinities

		% A two-class output can be given in one real number, avoid this
		% special case and fix it:
		if c == 2 & min(size(D)) == 1; D = [D -D]; end
		c = size(D,2); 

		if ~strcmp(s,'col')
		
			% Plot the contour lines
			if c < 3
				Z = reshape(D(:,1) - D(:,2),n+1,n+1);
				if ~isempty(contourc([V(1):dx:V(2)],[V(3):dy:V(4)],Z,[0 0]))
					[cc h] = contour([V(1):dx:V(2)],[V(3):dy:V(4)],Z,[0 0],s);
					set(h,'linewidth',linew)
					%DXD Matlab 7 has different handle definitions:
					if str2num(version('-release'))>13,
						h = get(h,'children');
					end
					hh = [hh;h];
				end
			else
				for j=1:c-1
					L = [1:c]; L(j) = [];
					Z = reshape( D(:,j) - max(D(:,L),[],2),n+1,n+1);
					if ~isempty(contourc([V(1):dx:V(2)],[V(3):dy:V(4)],Z,[0 0]))
						[cc h] = contour([V(1):dx:V(2)],[V(3):dy:V(4)],Z,[0 0],s);
						set(h,'linewidth',linew)
						%DXD Matlab 7 has different handle definitions:
						if str2num(version('-release'))>13,
							h = get(h,'children');
						end
						hh = [hh;h];
					end
				end
			end
		else
			% Fill the areas with some colour:
			col = 0; map = hsv(c+1); h = [];
			for j=1:c
				L = [1:c]; L(j) = [];
				Z = reshape( D(:,j) - max(D(:,L)',[],1)',n+1,n+1);
				Z = [-inf*ones(1,n+3);[-inf*ones(n+1,1),Z,-inf*ones(n+1,1)];-inf*ones(1,n+3)];
				col = col + 1;
				if ~isempty(contourc([V(1)-dx:dx:V(2)+dx],[V(3)-dy:dy:V(4)+dy],Z,[0 0]))
					[cc h] = contour([V(1)-dx:dx:V(2)+dx],[V(3)-dy:dy:V(4)+dy],Z,[0 0]);
					while ~isempty(cc)
						len = cc(2,1);
						fill(cc(1,2:len+1),cc(2,2:len+1),map(col,:),'FaceAlpha',0.5);
						cc(:,1:len+1) = [];
					end
					hh = [hh;h];
				end
			end
		end
	end
	axis(V);

	% Return the handles if they are requested:
	if nargout > 0, handle = hh; end
	hold off

	return