[p, q] = get_products();

% quantity sum over a day
%plot(sum(q'));

train_data = q( 1:28, :);
real_data  = q(29:42, :);

mean_data	= mean_pred(p, train_data);
regress_data	= regress_pred(p, train_data);
quad_data	= quad_regress_pred(p, train_data);
log_data	= log_regress_pred(p, train_data);
lq_data		= [log_data(:,1:334) quad_data(:,335) log_data(:,336:570)];
sevenday_data	= sevenday_pred(p, train_data);
random_data	= rand_pred(p, train_data);

[q2, removed] = remove_sevenday_frequency(q(1:14, :));
regress2_data = regress_pred(p([1:14 29:42],:), q2);
regress2_data = fft(regress2_data);
%regress2_data = (regress2_data .* (removed == 0)) + removed;
regress2_data = regress2_data + removed;
regress2_data = real(ifft(regress2_data));

pred_list = {mean_data regress_data quad_data log_data lq_data sevenday_data random_data regress2_data};

opt_data = opt_pred(real_data, pred_list);

% plot prediction quallity
[meqerr, meterr] = calc_error('mean',	  real_data, mean_data);
[reqerr, reterr] = calc_error('regress',  real_data, regress_data);
% quadratic just for reference, it sucks more than mean-predicition
[quqerr, quterr] = calc_error('quad reg.',real_data, quad_data);
[loqerr, loterr] = calc_error('log reg.', real_data, log_data);
[lqqerr, lqterr] = calc_error('l&q reg.', real_data, lq_data);
[seqerr, seterr] = calc_error('sevenday', real_data, sevenday_data);
[raqerr, raterr] = calc_error('random',	  real_data, random_data);
[opqerr, opterr] = calc_error('optimize', real_data, opt_data);
[re2qerr, re2terr] = calc_error('regress2', real_data, regress2_data);

qerr = [meqerr reqerr quqerr loqerr seqerr raqerr opqerr re2qerr];
terr = [meterr reterr quterr loterr seterr raterr opterr re2terr];
bar(qerr);
bar(terr);

mean_err	= sum(abs(real_data - mean_data));
regress_err	= sum(abs(real_data - regress_data));
quad_err	= sum(abs(real_data - quad_data));
log_err		= sum(abs(real_data - log_data));
lq_err		= sum(abs(real_data - lq_data));
sevenday_err	= sum(abs(real_data - sevenday_data));
random_err	= sum(abs(real_data - random_data));
opt_err		= sum(abs(real_data - opt_data));
regress2_err	= sum(abs(real_data - regress2_data));

err = [mean_err;regress_err;quad_err;log_err;sevenday_err;random_err;regress2_err];
[min_err, err_idx] = min(err);
printf('global min. error: %d\n', sum(min_err));
printf('local min count:');
local_min_count=[];
for i=1:size(err,1)
	local_min_count = [ local_min_count sum(sum(err_idx == i)) ];
	printf(' %d', local_min_count(i));
end
printf('\n');