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/* Author: Ioan Sucan */

#ifndef FCL_KNN_NEAREST_NEIGHBORS_LINEAR_H
#define FCL_KNN_NEAREST_NEIGHBORS_LINEAR_H

#include "fcl/knn/nearest_neighbors.h"
#include "fcl/exception.h"
#include <algorithm>

namespace fcl
{
/** \brief A nearest neighbors datastructure that uses linear
    search.

    \li Search for nearest neighbor is O(n).
    \li Search for k-nearest neighbors is  O(n log(k)).
    \li Search for neighbors within a range is O(n log(n)).
    \li Adding an element to the datastructure is O(1).
    \li Removing an element from the datastructure O(n).
*/
template<typename _T>
class NearestNeighborsLinear : public NearestNeighbors<_T>
{
public:
  NearestNeighborsLinear(void) : NearestNeighbors<_T>()
  {
  }

  virtual ~NearestNeighborsLinear(void)
  {
  }

  virtual void clear(void)
  {
    data_.clear();
  }

  virtual void add(const _T &data)
  {
    data_.push_back(data);
  }

  virtual void add(const std::vector<_T> &data)
  {
    data_.reserve(data_.size() + data.size());
    data_.insert(data_.end(), data.begin(), data.end());
  }

  virtual bool remove(const _T &data)
  {
    if (!data_.empty())
      for (int i = data_.size() - 1 ; i >= 0 ; --i)
        if (data_[i] == data)
        {
          data_.erase(data_.begin() + i);
          return true;
        }
    return false;
  }

  virtual _T nearest(const _T &data) const
  {
    const std::size_t sz = data_.size();
    std::size_t pos = sz;
    double dmin = 0.0;
    for (std::size_t i = 0 ; i < sz ; ++i)
    {
      double distance = NearestNeighbors<_T>::distFun_(data_[i], data);
      if (pos == sz || dmin > distance)
      {
        pos = i;
        dmin = distance;
      }
    }
    if (pos != sz)
      return data_[pos];

    throw Exception("No elements found in nearest neighbors data structure");
  }

  virtual void nearestK(const _T &data, std::size_t k, std::vector<_T> &nbh) const
  {
    nbh = data_;
    if (nbh.size() > k)
    {
      std::partial_sort(nbh.begin(), nbh.begin() + k, nbh.end(),
                        ElemSort(data, NearestNeighbors<_T>::distFun_));
      nbh.resize(k);
    }
    else
    {
      std::sort(nbh.begin(), nbh.end(), ElemSort(data, NearestNeighbors<_T>::distFun_));
    }
  }

  virtual void nearestR(const _T &data, double radius, std::vector<_T> &nbh) const
  {
    nbh.clear();
    for (std::size_t i = 0 ; i < data_.size() ; ++i)
      if (NearestNeighbors<_T>::distFun_(data_[i], data) <= radius)
        nbh.push_back(data_[i]);
    std::sort(nbh.begin(), nbh.end(), ElemSort(data, NearestNeighbors<_T>::distFun_));
  }

  virtual std::size_t size(void) const
  {
    return data_.size();
  }

  virtual void list(std::vector<_T> &data) const
  {
    data = data_;
  }

protected:

  /** \brief The data elements stored in this structure */
  std::vector<_T>   data_;

private:

  struct ElemSort
  {
    ElemSort(const _T &e, const typename NearestNeighbors<_T>::DistanceFunction &df) : e_(e), df_(df)
    {
    }

    bool operator()(const _T &a, const _T &b) const
    {
      return df_(a, e_) < df_(b, e_);
    }

    const _T                                              &e_;
    const typename NearestNeighbors<_T>::DistanceFunction &df_;
  };

};

}

#endif
