function [perf, elapsedTime]=stDsPerfEval(ds, opt, showPlot)
% Performance evaluation of ST (singing transcription) on a given dataset
%
%	Usage:
%		perf=stDsPerfEval(ds, opt)
%
%	Example:
%		load mir-st010.mat	% load dataset
%		opt=stDsPredict('defaultOpt');
%		[ds2, time]=stDsPredict(ds, opt, 1);
%		opt2=stDsPerfEval('defaultOpt');
%		perf=stDsPerfEval(ds2, opt2, 1)
%		fprintf('Elapsed time = %g sec\n', time);

if nargin<1, selfdemo; return; end
if ischar(ds) && strcmpi(ds, 'defaultOpt')    % Set the default options
	perf=pv2note('defaultOpt');
	return
end
if nargin<2||isempty(opt), opt=feval(mfilename, 'defaultOpt'); end
if nargin<3, showPlot=0; end

myTic=tic;
dsCount=length(ds);
for i=1:dsCount
	ds(i).fMeasure=noteVecSim(ds(i).notePredicted, ds(i).noteGt);	% Compute the performance in F-measure
%	fprintf('%d/%d: file=%s, f-measure=%g\n', i, dsCount, ds(i).gtFile, ds(i).fMeasure);
end
perf=mean([ds.fMeasure]);	% Average of F-measure
elapsedTime=toc(myTic);		% Elapsed time

if showPlot
	bar([ds.songId], [ds.fMeasure]);
	xlabel('Song ID'); ylabel('f-measure'); title(sprintf('Average f-measure=%g', perf));
end
% ====== Self demo
function selfdemo
mObj=mFileParse(which(mfilename));
strEval(mObj.example);