//===========================================================================
/*!
 * 
 *
 * \brief       Interface for nearest Neighbor queries
 * 
 * 
 *
 * \author      O.Krause
 * \date        2012-2014
 *
 *
 * \par Copyright 1995-2017 Shark Development Team
 * 
 * <BR><HR>
 * This file is part of Shark.
 * <http://shark-ml.org/>
 * 
 * Shark is free software: you can redistribute it and/or modify
 * it under the terms of the GNU Lesser General Public License as published 
 * by the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 * 
 * Shark is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU Lesser General Public License for more details.
 * 
 * You should have received a copy of the GNU Lesser General Public License
 * along with Shark.  If not, see <http://www.gnu.org/licenses/>.
 *
 */
//===========================================================================

#ifndef SHARK_ALGORITHMS_NEARESTNEIGHBORS_ABSTRACTNEARESTNEIGHBORS_H
#define SHARK_ALGORITHMS_NEARESTNEIGHBORS_ABSTRACTNEARESTNEIGHBORS_H

#include <shark/Core/utility/KeyValuePair.h>
#include <shark/Data/Dataset.h>
namespace shark{

	
/// \brief Interface for Nearest Neighbor queries.
///
/// Defines the abstract interface for query of nearest neighbors. This is used to generalize over the different algorithms
/// to query for nearest neighbors.
template<class InputType,class LabelType>
class AbstractNearestNeighbors{
public:
	typedef KeyValuePair<double,LabelType> DistancePair;
	typedef typename Batch<InputType>::type BatchInputType;

	///\brief Returns the k-nearest neighbors of a batch of points and returns them as linearized array.
	///
	///Given a batch of size n, a array with nxk values is returned where each entry is a key-value pair of distance and label.
	///the first k entries are the neighbors of point 1, the next k of point 2 and so on.
	virtual std::vector<DistancePair> getNeighbors(BatchInputType const& batch, std::size_t k) const = 0;

	/// \brief Returns the expected shape of the inputs
	Shape const& inputShape() const{
		return m_inputShape;
	}
	
	///\brief returns a const reference to the dataset used by the algorithm
	virtual LabeledData<InputType,LabelType>const& dataset()const = 0;

	virtual ~AbstractNearestNeighbors() {}
protected:
	Shape m_inputShape;
};

	
}

#endif
