diracmixturepdf.hpp

dysii是一款非常出色的滤波函数库

#ifndef INDII_ML_AUX_DIRACMIXTUREPDF_HPP
#define INDII_ML_AUX_DIRACMIXTUREPDF_HPP

#include "MixturePdf.hpp"
#include "DiracPdf.hpp"

namespace indii {
  namespace ml {
    namespace aux {
/**
 * Dirac mixture probability density.
 *
 * @author Lawrence Murray <[e-mail]>
 * @version $Rev: 348 $
 * @date $Date: 2007-11-16 18:28:44 +0000 (Fri, 16 Nov 2007) $
 *
 * @see MixturePdf for more information regarding the serialization
 * and parallelisation features of this class.
 */
class DiracMixturePdf : public MixturePdf<DiracPdf> {
public:
  /**
   * Default constructor.
   *
   * Initialises the mixture with zero dimensions. This should
   * generally only be used when the object is to be restored from a
   * serialization. Indeed, there is no other way to resize the
   * mixture to nonzero dimensionality except by subsequently
   * restoring from a serialization.
   */
  DiracMixturePdf();

  /**
   * Sampling constructor.
   *
   * @param o Distribution to approximate.
   * @param P Number of samples with which to approximate the
   * distribution.
   * 
   * Initialises the mixture by drawing @c P equally weighted samples
   * from the distribution @c o.
   */
  DiracMixturePdf(Pdf& o, const unsigned int P);

  /**
   * Constructor. One or more components should be added with
   * addComponent() after construction.
   *
   * @param N Dimensionality of the distribution.
   */
  DiracMixturePdf(const unsigned int N);

  /**
   * Destructor.
   */
  virtual ~DiracMixturePdf();

  virtual void setDimensions(const unsigned int N,
      const bool preserve = false);

  virtual const symmetric_matrix& getCovariance();

  /**
   * Get the covariance of the full distribution.
   *
   * @return \f$\Sigma\f$; covariance of the full distribution.
   */
  symmetric_matrix getDistributedCovariance();

protected:
  virtual void dirty();

private:
  /**
   * Last calculated covariance.
   */
  symmetric_matrix sigma;

  /**
   * Last calculated unnormalized covariance.
   */
  symmetric_matrix Zsigma;

  /**
   * Is the last calculated covariance up to date?
   */
  bool haveSigma;

  /**
   * Calculate covariance from current components.
   */
  void calculateCovariance();

  /**
   * Serialize.
   */
  template<class Archive>
  void save(Archive& ar, const unsigned int version) const;

  /**
   * Restore from serialization.
   */
  template<class Archive>
  void load(Archive& ar, const unsigned int version);

  /*
   * Boost.Serialization requirements.
   */
  BOOST_SERIALIZATION_SPLIT_MEMBER()
  friend class boost::serialization::access;

};

    }
  }
}

#include "boost/serialization/base_object.hpp"

template <class Archive>
void indii::ml::aux::DiracMixturePdf::save(Archive& ar,
    const unsigned int version) const {
  ar & boost::serialization::base_object<MixturePdf<DiracPdf> >(*this);
}

template <class Archive>
void indii::ml::aux::DiracMixturePdf::load(Archive& ar,
    const unsigned int version) {
  ar & boost::serialization::base_object<MixturePdf<DiracPdf> >(*this);

  sigma.resize(getDimensions(), false);
  Zsigma.resize(getDimensions(), false);
  haveSigma = false;
}

#endif