function Y = svmWrapper( trn_vects, trn_labels, trn_ids, ...
                         tst_vects, tst_labels, tst_ids, ...
                         flags, debugsvm )
%SVMWRAPPER   SVM light wrapper
%
%   Arguments:
%      trn_vects   x
%      trn_labels  x
%      trn_ids     x
%      tst_vects   x
%      tst_labels  x
%      K_file      x
%      flags       x
%      debugsvm    x
%
%   Returns:
%      Y           x
%
%   Authors:
%       Joshua V. Dillon; Feb. 21, 2007; jvdillon AAT purdue DDOT edu


% vectors never modified should automatically be passed by reference.
%  cf.:  http://www.mathworks.com/support/solutions/data/1-15SO4.html?1-15SO4 

% TODO: dimension checking here.  Ensure K has a compare-to-self column and
%       row!
% TODO: if we are doing a lot of CV, could just write the WHOLE kernel once,
%       and let SVM read the whole thing each time?

if nargin==6
	flags = '';
	debugsvm = 0;
elseif nargin==7
	debugsvm = 0;
elseif nargin==8
	% do nothing
else
	error('invalid args');
end

svmdir = '/noback/lowbow/translation/svm/helper/';


% --- Phase 0: Setup ----------------------------------------------------------
% create new temporary files and set some variables
tmpdir = '/noback/lowbow/translation/tmp/';
test_file   = mktemp([tmpdir 'testXXXXXX.dat']);
train_file  = mktemp([tmpdir 'trainXXXXXX.dat']);
model_file  = mktemp([tmpdir 'modelXXXXXX.dat']);	% designate a model file
output_file = mktemp([tmpdir 'outputXXXXXX.dat']);	% designate an output file
floatfmt = '%.16g';


% --- Phase 1: Training -------------------------------------------------------
% write training file
svmWriteDat(train_file, trn_vects, trn_labels, trn_ids, floatfmt);
%cmdlrn = [' ./svm_learn -c 1.0 -z c -t 4 -u "' K_file '" ' train_file ' ' model_file ];
cmdlrn = [svmdir 'svm_learn -z c ' flags ' ' train_file ' ' model_file ];
[status result] = system(cmdlrn);
if debugsvm, fprintf('%s\n%s\n',cmdlrn,result); end
system(['rm ' train_file]);


% --- Phase 2: Testing --------------------------------------------------------
% write testing file
svmWriteDat(test_file, tst_vects, tst_labels, tst_ids, floatfmt);

%cmdcls = ['./svm_classify -v 1 ' test_file ' ' model_file ' ' output_file];
cmdcls = [svmdir 'svm_classify -v 1 ' test_file ' ' model_file ' ' '/dev/null'];
%disp(cmdcls);
[status result] = system(cmdcls);
if debugsvm, fprintf('%s\n%s\n',cmdcls,result); end

% jvd: we could read the whole output file...
%system(['rm ' model_file ' ' test_file]);
%fd = fopen(output_file,'r');
%Y = textscan(fd,'%n');
%fclose(fd);
%Y = [Y{:}];
%system(['rm ' output_file]);

% jvd: ...or simply regex the svm output
ptrn = 'Accuracy .+? \((\d+) correct, \d+ incorrect, \d+ total)';
match = regexp(result,ptrn,'tokens');
Y = cellfun(@str2num,match{1});
system(['rm ' model_file ' ' test_file ' ' output_file]);



% --- Helper Functions --------------------------------------------------------
function svmWriteDat(filename,X,labels,ids,floatfmt)
	if     nargin==4, floatfmt = '%.16g';
	elseif nargin~=5, error('invalid arguments');
	else, end
	fd = fopen(filename,'w');
	for ii=1:size(X,2)
		[I J S] = find(X(:,ii));
		fprintf(fd,'%d',labels(ii));
		fprintf(fd,[' %d:' floatfmt],[I S]');
		fprintf(fd,' #%d\n',ids(ii));
	end 
	fclose(fd);