function Acc = svmCVOneVsRest( trn_samps, tst_samps, trn_zs, tst_zs,...
								tf, numFolds, svmflags, type, D, Dnull, gamma)
%SVMCVONEVSREST   Cross-validated binary "1 vs. Rest" classifcation using SVM light
%
%   Arguments:
%      trn_samps  randperms used to index into pool
%      tst_samps  randperms used to index into pool
%      trn_zs     corresponding (training) labels
%      tst_zs     corresponding (testing) labels
%      tf         term frequency matrix (cols are docs)
%      numFolds   Number of cross validations
%      svmflags   Flags passed to SVM light; if ED2 and A are specified,
%                    "-t 4 -u /path/to/K.eg.mtx" is appended to svmflags
%      type       either: 'stndrbf' 'stndlin' 'tranrbf' 'tranlin'
%
%   Potentially Ignored Arguments (based on 'type'):
%      D          either E{||a-b||^2} or E{a'*b}
%      Dnull      vector E{||a||^2} or Ignored
%      gamma      scalar as in exp(-gamma * D) or Ignored
%
%   Returns:
%      Acc        Number of correctly classified testing points at each fold
%
%   Authors:
%       Joshua V. Dillon; Feb. 21, 2007; jvdillon AAT purdue DDOT edu


if nargin<8
	error('must supply at least eight arguments (see help)');
end


% jvd: setup kernel
if strcmp(type,'stndrbf')
	% standard radial basis function: exp(-gamma ||a-b||^2)
	Kcache = [];
	svmflags = [svmflags ' -t 2 -g ' num2str(gamma) ' '];
	
elseif strcmp(type,'stndlin')
	% standard linear: a'*b
	Kcache = [];
	svmflags = [svmflags ' -t 0 '];
	
elseif strcmp(type,'tranrbf')
	% translated radial basis function: exp(-gamma E{||a-b||^2})
	if nargin<11
		error('translated rbf: must supply E{||a-b||^2}, E{||a||^2}, and gamma');
	end
	K_file = mktemp(['/noback/lowbow/translation/tmp/K.XXXXXX.mtx']);
	svmflags = [svmflags ' -t 4 -u "' K_file '" '];
	if size(Dnull,2)==1
		Kcache = exp(-gamma * [[0 Dnull'];[Dnull D]]);
	elseif size(Dnull,1)==1
		Kcache = exp(-gamma * [[0 Dnull];[Dnull' D]]);
	else
		error('Dnull must be a vector');
	end

elseif strcmp(type,'tranlin')
	% translated linear: E{a'*b}
	if nargin<9
		error('translated linear: must supply E{a''*b}');
	end
	K_file = mktemp(['/noback/lowbow/translation/tmp/K.XXXXXX.mtx']);
	svmflags = [svmflags ' -t 4 -u "' K_file '" '];
	Dnull = sparse(size(D,1),1);
	Kcache = [[0 Dnull'];[Dnull D]];

else
	error('unrecognized kernel type');
end


Acc = zeros(1,numFolds);

% cross validate
for ii=1:numFolds
	% convenience variables; these will index into the normal K, hence we need
	% to be cautious when working with the Kcache, as it contains the
	% additional nulldoc row,col
	trn_samp = trn_samps(:,ii);
	tst_samp = tst_samps(:,ii);
	trn_z = trn_zs(:,ii);
	tst_z = tst_zs(:,ii);

	% Kcache is same kernel for training and testing (tst_samp labels are offset)
	if ~isempty(Kcache)
		% always include the nulldoc, thus we use the first row and shift
		% everything accordingly
		I = [1;trn_samp+1;tst_samp+1];
		% can set precision here, default is '%.16f'
		jvdmatrixWrite( K_file, Kcache(I,I) );
	end

	% labels start at 1 because 0 row and col are reserved for nulldoc
	Acc(ii) = svmWrapper ( ...
					tf(:,trn_samp), trn_z,  1:length(trn_samp),...
					tf(:,tst_samp), tst_z, (1:length(tst_samp))+length(trn_samp),...
					svmflags, 0 );
end


if exist('K_file','var') & exist(K_file,'file')
	system(['rm ' K_file]);
end