text: /*
   * This program is free software; you can redistribute it and/or modify
   * it under the terms of the GNU General Public License as published by
   * the Free Software Foundation; either version 3 of the License, or
   * (at your option) any later version.
   *
   * Written (W) 2007-2009 Soeren Sonnenburg
   * Copyright (C) 2007-2009 Fraunhofer Institute FIRST and Max-Planck-Society
   */
  
  #ifndef _EUCLIDEANDISTANCE_H__
  #define _EUCLIDEANDISTANCE_H__
  
  #include <shogun/lib/config.h>
  
  #include <shogun/lib/common.h>
  #include <shogun/distance/RealDistance.h>
  #include <shogun/features/DenseFeatures.h>
  
  namespace shogun
  {
  /** @brief class EuclideanDistance
   *
   * The familiar Euclidean distance for real valued features computes
   * the square root of the sum of squared disparity between the
   * corresponding feature dimensions of two data points.
   *
   * \f[\displaystyle
   *  d({\bf x},{\bf x'})= \sqrt{\sum_{i=0}^{n}|{\bf x_i}-{\bf x'_i}|^2}
   * \f]
   *
   * This special case of Minkowski metric is invariant to an arbitrary
   * translation or rotation in feature space.
   *
   * The Euclidean Squared distance does not take the square root:
   *
   * \f[\displaystyle
   *  d({\bf x},{\bf x'})= \sum_{i=0}^{n}|{\bf x_i}-{\bf x'_i}|^2
   * \f]
   *
   * @see CMinkowskiMetric
   * @see <a href="http://en.wikipedia.org/wiki/Distance#Distance_in_Euclidean_space">
   * Wikipedia: Distance in Euclidean space</a>
   */
  class CEuclideanDistance: public CRealDistance
  {
  	public:
  		/** default constructor */
  		CEuclideanDistance();
  
  		/** constructor
  		 *
  		 * @param l features of left-hand side
  		 * @param r features of right-hand side
  		 */
  		CEuclideanDistance(CDenseFeatures<float64_t>* l, CDenseFeatures<float64_t>* r);
  		virtual ~CEuclideanDistance();
  
  		/** init distance
  		 *
  		 * @param l features of left-hand side
  		 * @param r features of right-hand side
  		 * @return if init was successful
  		 */
  		virtual bool init(CFeatures* l, CFeatures* r);
  
  		/** cleanup distance */
  		virtual void cleanup();
  
  		/** get distance type we are
  		 *
  		 * @return distance type EUCLIDEAN
  		 */
  		virtual EDistanceType get_distance_type() { return D_EUCLIDEAN; }
  
  		/** get feature type the distance can deal with
  		 *
  		 * @return feature type DREAL
  		 */
  		virtual EFeatureType get_feature_type() { return F_DREAL; }
  
  		/** get name of the distance
  		 *
  		 * @return name Euclidean
  		 */
  		virtual const char* get_name() const { return "EuclideanDistance"; }
  
  		/** disable application of sqrt on matrix computation
  		 * the matrix can then also be named norm squared
  		 *
  		 * @return if application of sqrt is disabled
  		 */
  		virtual bool get_disable_sqrt() { return disable_sqrt; };
  
  		/** disable application of sqrt on matrix computation
  		 * the matrix can then also be named norm squared
  		 *
  		 * @param state new disable_sqrt
  		 */
  		virtual void set_disable_sqrt(bool state) { disable_sqrt=state; };
  
  		/** compute the distance between lhs feature vector a
  		 *  and rhs feature vector b. The computation of the
  		 *  distance stops if the intermediate result is
  		 *  larger than upper_bound. This is useful to use
  		 *  with John Langford's Cover Tree
  		 *
  		 *  @param idx_a feature vector a at idx_a
  		 *  @param idx_b feature vector b at idx_b
  		 *  @param upper_bound value above which the computation
  		 *  halts
  		 *  @return distance value or upper_bound
  		 */
  		virtual float64_t distance_upper_bounded(int32_t idx_a, int32_t idx_b, float64_t upper_bound);
  
  	protected:
  		/// compute kernel function for features a and b
  		/// idx_{a,b} denote the index of the feature vectors
  		/// in the corresponding feature object
  		virtual float64_t compute(int32_t idx_a, int32_t idx_b);
  
  	private:
  		void init();
  
  	protected:
  		/** if application of sqrt on matrix computation is disabled */
  		bool disable_sqrt;
  };
  
  } // namespace shogun
  #endif /* _EUCLIDEANDISTANCE_H__ */
  