rlsdualr.h

/*
 * The GURLS Package in C++
 *
 * Copyright (C) 2011-1013, IIT@MIT Lab
 * All rights reserved.
 *
 * authors:  M. Santoro
 * email:   msantoro@mit.edu
 * website: http://cbcl.mit.edu/IIT@MIT/IIT@MIT.html
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions
 * are met:
 *
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 *       copyright notice, this list of conditions and the following
 *       disclaimer.
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 *       copyright notice, this list of conditions and the following
 *       disclaimer in the documentation and/or other materials
 *       provided with the distribution.
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 *       of its contributors or of the Massacusetts Institute of
 *       Technology or of the Italian Institute of Technology may be
 *       used to endorse or promote products derived from this software
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#ifndef _GURLS_RLSDUALR_H_
#define _GURLS_RLSDUALR_H_

#include "gurls++/optimization.h"
#include "gurls++/utils.h"
#include "gurls++/gmath.h"

#include <set>

namespace gurls {

template <typename T>
class RLSDualr: public Optimizer<T>{

public:
   GurlsOptionsList* execute(const gMat2D<T>& X, const gMat2D<T>& Y, const GurlsOptionsList& opt);
};


template <typename T>
GurlsOptionsList* RLSDualr<T>::execute(const gMat2D<T>& X, const gMat2D<T>& Y, const GurlsOptionsList& opt)
{
//  lambda = opt.singlelambda(opt.paramsel.lambdas);
    const gMat2D<T> &ll = opt.getOptValue<OptMatrix<gMat2D<T> > >("paramsel.lambdas");
    T lambda = opt.getOptAs<OptFunction>("singlelambda")->getValue(ll.getData(), ll.getSize());

    const GurlsOptionsList* kernel = opt.getOptAs<GurlsOptionsList>("kernel");
    const gMat2D<T>& K_mat = kernel->getOptValue<OptMatrix<gMat2D<T> > >("K");

    T* K = new T[K_mat.getSize()];
    copy(K, K_mat.getData(), K_mat.getSize());

    //n = size(opt.kernel.K,1);
    const unsigned long n = K_mat.rows();

   //T = size(y,2);
    const unsigned long t = Y.cols();

    const T coeff = n*lambda;
    unsigned long i=0;
    for(T* it = K; i<n; ++i, it+=n+1)
        *it += coeff;


//       [Q,L,V] = tygert_svd(K,n);
//       Q = double(Q);
//       L = double(diag(L));
    T *Q = new T[n*n];
    T *L = new T[n];
    T *V = NULL;

//    k = round(opt.eig_percentage*n/100);
    unsigned long k = static_cast<unsigned long>(gurls::round((opt.getOptAsNumber("eig_percentage")*n)/100.0));
    random_svd(K, n, n, Q, L, V, k);


    gMat2D<T> *retC = new gMat2D<T>(n,t);
    T* work = new T[n*(n+1)];

    T* Qty = new T[n*Y.cols()];
    dot(Q, Y.getData(), Qty, n, n, Y.rows(), Y.cols(), n, Y.cols(), CblasTrans, CblasNoTrans, CblasColMajor);

    rls_eigen(Q, L, Qty, retC->getData(), lambda, n, n, n, n, n, t, work);

    delete [] Qty;
    delete [] work;
    delete [] Q;
    delete [] L;

    GurlsOptionsList* optimizer = new GurlsOptionsList("optimizer");


//       if strcmp(opt.kernel.type, 'linear')
   if(kernel->getOptAsString("type") == "linear")
   {
   //           cfr.W = X'*cfr.C;
        gMat2D<T>* W  = new gMat2D<T>(X.cols(), t);
        dot(X.getData(), retC->getData(), W->getData(), X.rows(), X.cols(), n, t, X.cols(), t, CblasTrans, CblasNoTrans, CblasColMajor);

        optimizer->addOpt("W", new OptMatrix<gMat2D<T> >(*W));

//           cfr.C = [];
        gMat2D<T>* emptyC = new gMat2D<T>();
        optimizer->addOpt("C", new OptMatrix<gMat2D<T> >(*emptyC));

//           cfr.X = [];
        gMat2D<T>* emptyX = new gMat2D<T>();
        optimizer->addOpt("X", new OptMatrix<gMat2D<T> >(*emptyX));

        delete retC;
    }
    else
    {
//           cfr.W = [];
        gMat2D<T>* emptyW = new gMat2D<T>();
        optimizer->addOpt("W", new OptMatrix<gMat2D<T> >(*emptyW));

//           cfr.C = retC;
        optimizer->addOpt("C", new OptMatrix<gMat2D<T> >(*retC));

//           cfr.X = X;
        gMat2D<T>* optX = new gMat2D<T>(X);
        optimizer->addOpt("X", new OptMatrix<gMat2D<T> >(*optX));
    }

    return optimizer;
}

}
#endif // _GURLS_RLSDUALR_H_