gaussian_vector.h

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/* Author: Wim Meeussen */

#ifndef PEOPLE_TRACKING_FILTER_GAUSSIAN_VECTOR_H
#define PEOPLE_TRACKING_FILTER_GAUSSIAN_VECTOR_H

#include <bfl/pdf/pdf.h>
#include <tf/tf.h>
#include <vector>

namespace BFL
{
class GaussianVector: public Pdf<tf::Vector3>
{
private:
  tf::Vector3 mu_, sigma_;
  mutable double sqrt_;
  mutable tf::Vector3 sigma_sq_;
  mutable bool sigma_changed_;

public:
  GaussianVector(const tf::Vector3& mu, const tf::Vector3& sigma);

  virtual ~GaussianVector();

  friend std::ostream& operator<< (std::ostream& os, const GaussianVector& g);

  void sigmaSet(const tf::Vector3& sigma);

  // Redefinition of pure virtuals
  virtual Probability ProbabilityGet(const tf::Vector3& input) const;
  bool SampleFrom(vector<Sample<tf::Vector3> >& list_samples, const int num_samples, int method = DEFAULT,
                  void * args = NULL) const;
  virtual bool SampleFrom(Sample<tf::Vector3>& one_sample, int method = DEFAULT, void * args = NULL) const;

  virtual tf::Vector3 ExpectedValueGet() const;
  virtual MatrixWrapper::SymmetricMatrix CovarianceGet() const;

  virtual GaussianVector* Clone() const;
};
}  // end namespace BFL
#endif  // PEOPLE_TRACKING_FILTER_GAUSSIAN_VECTOR_H