HardClusteringModel.h

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//===========================================================================
/*!
 * 
 *
 * \brief       Model for "hard" clustering.
 * 
 * 
 *
 * \author      T. Glasmachers
 * \date        2011
 *
 *
 * \par Copyright 1995-2017 Shark Development Team
 * 
 * <BR><HR>
 * This file is part of Shark.
 * <https://shark-ml.github.io/Shark/>
 * 
 * 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_CLUSTERING_HARDCLUSTERINGMODEL_H
#define SHARK_MODELS_CLUSTERING_HARDCLUSTERINGMODEL_H
 
#include <shark/Models/Clustering/ClusteringModel.h>
 
namespace shark {
 
 
///
/// \brief Model for "hard" clustering.
///
/// \par
/// The HardClusteringModel is based on an \ref clustering
/// object. Given an input, the model outputs the index of the
/// best matching cluster.
///
/// \par
/// See also SoftClusteringModel for general cluster membership.
/// \ingroup clustering
template <class InputT>
class HardClusteringModel : public ClusteringModel<InputT, unsigned int>
{
    typedef ClusteringModel<InputT, unsigned int> base_type;
    typedef AbstractClustering<InputT> ClusteringType;
public:
    typedef typename base_type::BatchInputType BatchInputType;
    typedef typename base_type::BatchOutputType BatchOutputType;
    typedef typename base_type::InputType InputType;
    typedef typename base_type::OutputType OutputType;
    
    
    /// Constructor
    HardClusteringModel(ClusteringType* clustering)
    : base_type(clustering){
    }
 
    /// \brief From INameable: return the class name.
    std::string name() const
    { return "HardClusteringModel"; }
    
    using ClusteringModel<InputT, unsigned int>::eval;
    
    Shape inputShape()const{
        return this->mep_clustering->inputShape();
    }
    Shape outputShape()const{
        return this->mep_clustering->numberOfClusters();
    }
    
    /// \brief Compute best matching cluster.
    ///
    /// \par
    /// The actual computation is redirected to the clustering object.
    void eval(InputType const & pattern, OutputType& output)const{
        output = this->mep_clustering->hardMembership(pattern);
    }
 
    /// \brief Compute best matching cluster for a batch of inputs.
    ///
    /// \par
    /// The actual computation is redirected to the clustering object.
    void eval(BatchInputType const & patterns, BatchOutputType& outputs)const{
        outputs = this->mep_clustering->hardMembership(patterns);
    }
};
 
 
}
#endif