AbstractMetric.h

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//===========================================================================
/*!
 * 
 *
 * \brief       abstract super class of all metrics
 * 
 * 
 *
 * \author      O. Krause
 * \date        2015
 *
 *
 * \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_MODELS_KERNELS_ABSTRACTMETRIC_H
#define SHARK_MODELS_KERNELS_ABSTRACTMETRIC_H

#include <shark/Data/BatchInterface.h>
#include <shark/Core/IParameterizable.h>
#include <shark/Core/ISerializable.h>
#include <shark/Core/INameable.h>
#include <shark/Core/Traits/ProxyReferenceTraits.h>
namespace shark {
    
    
template<class InputTypeT>
class AbstractMetric: public INameable, public IParameterizable<>, public ISerializable{
public:
    /// \brief  Input type of the Kernel.
    typedef InputTypeT InputType;
    /// \brief batch input type of the kernel
    typedef typename Batch<InputTypeT>::type BatchInputType;
    /// \brief Const references to InputType
    typedef typename ConstProxyReference<InputType const>::type ConstInputReference;
    /// \brief Const references to BatchInputType
    typedef typename ConstProxyReference<BatchInputType const>::type ConstBatchInputReference;

    AbstractMetric() { }
    virtual ~AbstractMetric() { }
        
    /// \brief From ISerializable, reads a metric from an archive.
    virtual void read( InArchive & archive ){
        RealVector p;
        archive & p;
        setParameterVector(p);
    }

    /// \brief From ISerializable, writes a metric to an archive.
    ///
    /// The default implementation just saves the parameters.
    virtual void write( OutArchive & archive ) const{
        RealVector p = parameterVector();
        archive & p;
    }
    
    /// Computes the squared distance in the kernel induced feature space.
    virtual double featureDistanceSqr(ConstInputReference x1, ConstInputReference x2) const=0;
    
    virtual RealMatrix featureDistanceSqr(
        ConstBatchInputReference batchX1,
        ConstBatchInputReference batchX2
    ) const = 0;
    

    /// \brief Computes the distance in the kernel induced feature space.
    double featureDistance(ConstInputReference x1, ConstInputReference x2) const {
        return std::sqrt(featureDistanceSqr(x1, x2));
    }
};
}
#endif