#include <eigen3/Eigen/Dense>
#include <vector>
#include <limits>
#include <algorithm>

using Eigen::Matrix;
using Eigen::Dynamic;
using std::numeric_limits;
using std::random_shuffle;
using std::vector;
using std::pair;

template<typename DataType, typename LabelType, class RandomAccessIterator,
         class DotCallback, class AddCallback>
int liblinear_cs_train(RandomAccessIterator first, RandomAccessIterator last)
{
	typedef Matrix<DataType,Dynamic,1> VectorXt;
	typedef vector<unsigned int> ActiveSet;

	unsigned int iteration = 0;
	unsigned int n_iteration = 10;
	unsigned int n_classes = 2;
	unsigned int n_vectors = 3;
	unsigned int n_features = 2;

	ActiveSet active_set;
	unsigned int active_set_size;

	VectorXt QD(last-first);
	for (unsigned int i=0; first!=last; ++first)
	{
		QD[i] = DotCallback(*first);
	}

	VectorXt G(n_classes);

	while (iteration < n_iteration)
	{
		double stopping = - numeric_limits<double>::min();

		random_shuffle(active_set.begin(),active_set.begin()+active_set_size);

		for (ActiveSet::const_iterator iterator=active_set.begin();
		     iterator!=active_set.end(); ++iterator)
		{
			unsigned int i = (*iterator);
			double Ai = QD[i];

			if (Ai > 0)
			{
			}
		}

		++iteration;
	}

}