%PLOTF Plot feature distribution% %   h = PLOTF(A)% % Produces 1-D density plots for all the features in dataset A. The % densities are estimated using PARZENML.% % See also DATASETS, PARZENML% Copyright: R.P.W. Duin, duin@ph.tn.tudelft.nl% Faculty of Applied Sciences, Delft University of Technology% P.O. Box 5046, 2600 GA Delft, The Netherlands% $Id: plotf.m,v 1.5 2004/10/21 15:47:18 duin Exp $function h_out = plotf(a)	prtrace(mfilename);		[m,k,c] = getsize(a);	% Define the color for each of the classes:	if c == 2		map = [0 0 1; 1 0 0];	else		map = hsv(c);	end	% Make subplots for each feature, so a grid of p x q subplots is	% defined	h = [];	if k > 3		p = ceil(k/2); q = 2;	else		p = k; q = 1;	end	% Get the feature names	feats = getfeatlab(a,'string');	if size(feats,2) == 1		feats = [repmat('Feature ',size(feats,1),1) feats];	end	% Make the plot for each of the features:	for j = 1:k		b = a(:,j);		s = zeros(1,c);		d = zeros(121,c);		bb = [-0.10:0.01:1.10]' * (max(b)-min(b)) + min(b);		ex = 0;		% Make a density estimate of each of the classes:		for i = 1:c			I = findnlab(a,i);			D = +distm(bb,b(I));			s(i) = parzenml(b(I));			% Compute the density function			d(:,i) = sum(exp(-D/(s(i).^2)),2)./(length(I)*s(i));;		end		% Create the subplots with the correct sizes:		subplot(p,q,j)		plot(bb,zeros(size(bb)),'w.');		hold on		h = [];		% Scatter the data and plot the density functions for each of the		% classes:		for i = 1:c			I = findnlab(a,i);			hh = plot(b(I),zeros(size(b(I))),'x',bb,+d(:,i));			set(hh,'color',map(i,:));			h = [h;hh];		end		%legend(h,getlablist(a)); does not work properly		title([getname(a) ': ' feats(j,:)]);		hold off	end	% The last details to take care of:	if k == 1, title(''); end	if nargout > 0		h_out = h;	end	return