hypothesis2D.h

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#ifndef MMVL_HYPOTHESIS2D_HH
#define MMVL_HYPOTHESIS2D_HH

#ifndef NDEBUG
#include <iostream>
#endif

#include "hypothesis.h"
#include "dice.h"

using namespace mimas;

namespace mimas{
  namespace hf{
    
    class hypothesis2D: public hypothesis
      {
      public:
  float x;
  float y;
  static float sigmaSpan;
      
  // !! instead of using int(), use something to round to the nearest value 
  hypothesis2D drift(void) const
    {
      return hypothesis2D(int(x + Dice::gaussian_random() * sigmaSpan),
        int(y + Dice::gaussian_random() * sigmaSpan),
        weight);
    }

  //This is used by analyse_result_mean
  //when using this function make sure you are not dividing by 0 
  //bother about AnalyseResult won't have to implement it
  hypothesis2D mean(const hypothesis2D &h)
  {
    if(h.weight != 0)
      {
        float coord1 = (x * weight  + h.x * h.weight) /(weight + h.weight);
        float coord2 = (y * weight + h.y * h.weight) /(weight + h.weight);

        return hypothesis2D(coord1,
          coord2,
          weight + h.weight);
      }
    return *this;
  }

  float distance(const hypothesis2D &h)
  {
    return sqrt((h.x - x) * (h.x - x) + (h.y - y) * (h.y - y));
  }

  hypothesis2D(float x = 0, float y = 0, double weight = 0)
    :hypothesis(weight), x(x), y(y){}
      
      };
  }
} 
#endif

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