skinymultinormal.h

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/*

Copyright (c) 2003, Cornell University
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   - Redistributions of source code must retain the above copyright notice,
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   - Neither the name of Cornell University nor the names of its
       contributors may be used to endorse or promote products derived from
       this software without specific prior written permission.

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AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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*/

// -*- C++ -*-

#if !defined _CLUS_SKINYMULTINORMAL_H_
#define _CLUS_SKINYMULTINORMAL_H_

#include "general.h"
#include "distribution.h"
#include "emhipclus.h"
#include "vec.h"
#include "cholesky.h"
#include <math.h>
#include "linearregressor.h"
#include "misc.h"
#include "trislv.h"

using namespace TNT;

namespace CLUS
{

/** For now make EMHiperPlanCluster look like a Distribution */
class SkinyMultiDimNormal: public Distribution, public EMHiperPlan
{
public:
    SkinyMultiDimNormal(int InDim=0):Distribution(InDim), EMHiperPlan(InDim,1)
    { }
    
    SkinyMultiDimNormal(int InDim, int):Distribution(InDim), EMHiperPlan(InDim-1,1,0)
    { }

    Regressor* CreateRegressor(void)
    {
        EMHiperPlan::ComputeCCoef();
        return new LinearRegressor(EMHiperPlan::C);
    }

    void DenormalizeParameters(SkinyMultiDimNormal* pD)
    {}

    void NormalizeData(const double* DataCache, double* X)
    {
        // Just do the copying
        for (int i=0; i<=EMHiperPlan::inDim; i++)
            X[i]=DataCache[i];
    }

    double LearnProbability(const double* DataCache)
    {
        double aux=EMHiperPlan::ClusDistance(DataCache);
        probabilityLearn = 1.0/aux;
        return probabilityLearn;
    }

    double InferProbability(const double* DataCache)
    {
        probabilityInfer = 1.0/EMHiperPlan::InferDistance(DataCache);
        return probabilityInfer;
    }

    double NormalizeLearnProbability(double Coef, int nrClus=1)
    {
        return CorrectApartGrade(Coef);
    }

    double UpdateParameters(void)
    {
        return AdjustPrototypes();
    }

    void AdjustYwithYoverD(double& y)
    {
        Vector<double> Y(1);
        Y[0]=y;
        EMHiperPlan::AdjustYwithYoverD(Y);
        y=Y[0];
    }

    static string TypeName(void)
    {
        return string("SkinyMultiDimNormal");
    }

    void RandomDistribution(int NrClusters)
    {
        EMHiperPlan::RandomCluster();
    }

    void SaveToStream(ostream& out)
    {
        EMHiperPlan::SaveToStream(out);
    }

    void LoadFromStream(istream& in)
    {
        EMHiperPlan::LoadFromStream(in);
    }
};

}


#endif /* _CLUS_SKINYMULTINORMAL_H_ */

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