--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/trajectorymanagement/src/LCSMetric.h	Mon Feb 22 22:09:35 2021 -0500
@@ -0,0 +1,130 @@
+#ifndef LCSMETRIC_H_
+#define LCSMETRIC_H_
+
+#include "Metric.h"
+
+/**
+ * LCSMetric class.
+ *
+ * The Longest Common Subsequence metric
+ * This class mesures :
+ * 1) the similarity (number of points in "common", ie relative to distance similarity threshold) ; 
+ * 2) the normalized distance between two trajectories
+ */
+
+template<typename Tr, typename To>
+class LCSMetric: public Metric<Tr, To>
+{
+public:
+	/**
+	 * Constructor.
+	 */
+ LCSMetric() : similarityThreshold(0.0), eps(1e-6)
+	{
+	}
+
+	/**
+	 * Set similarity threshold between two points.
+	 *
+	 * @param[in] similarityThreshold similarity threshold
+	 */
+	bool setSimilarityThreshold(double similarityThreshold)
+	{
+		if (similarityThreshold >= 0.0)
+		{
+			this->similarityThreshold = similarityThreshold;
+			return true;
+		}
+		return false;
+	}
+
+	/**
+	 * Set machine epsilon.
+	 *
+	 * @param[in] eps machine epsilon
+	 */
+	bool setEps(double eps)
+	{
+		if (eps >= 0.0)
+		{
+			this->eps = eps;
+			return true;
+		}
+		return false;
+	}
+
+	/**
+	 * Compute similarity between two trajectories.
+	 *
+	 * @param[in] a input trajectory
+	 * @param[in] b input trajectory
+	 * @param[out] result distance between two trajectories
+	 */
+	void distance(const Trajectory<Tr> *a, const Trajectory<Tr> *b, To &result, unsigned int nbOfPoints = std::numeric_limits<unsigned int>::max())
+	{
+	  result = To(0);	  
+	  unsigned int LCSS = 0;
+	  similarity(a,b, LCSS); 
+	  unsigned int min_size = min(a->size(),b->size());
+	  result = 1 - double(LCSS/min_size);
+	}
+
+	/**
+	 * Compute similarity between two trajectories.
+	 *
+	 * @param[in] a input trajectory
+	 * @param[in] b input trajectory
+	 * @param[out] result similarity between two trajectories
+	 */
+	void similarity(const Trajectory<Tr> *a, const Trajectory<Tr> *b, unsigned int &result)
+	{
+		unsigned int LCS[a->size() + 1][b->size() + 1];
+
+		{ //initialisation
+			for (unsigned int i = 0; i <= a->size(); ++i)
+			{
+				LCS[i][0] = 0;
+			}
+
+			for (unsigned int j = 0; j <= b->size(); ++j)
+			{
+				LCS[0][j] = 0;
+			}
+		}
+
+		{ //algorithm
+			for (unsigned int i = 1; i <= a->size(); ++i)
+			{
+				for (unsigned int j = 1; j <= b->size(); ++j)
+				{
+					cv::Point3_<typeof(static_cast<Tr>(a->getPoint(i-1)).x)> p(a->getPoint(i - 1) - b->getPoint(j - 1));
+					double distance = sqrt(pow(p.x, 2) + pow(p.y, 2) + pow(p.z, 2)); // il faudrait généraliser
+					if (distance <= similarityThreshold + eps)
+					{ //a[i] == b[j]
+						LCS[i][j] = LCS[i - 1][j - 1] + 1;
+					}
+					else
+					{
+					  LCS[i][j] = std::max(LCS[i - 1][j], LCS[i][j - 1]);
+					}
+				}
+			}
+		}
+
+		result = LCS[a->size()][b->size()];
+	}
+
+private:
+	/**
+	 * Similarity threshold between two points.
+	 */
+	double similarityThreshold;
+
+	/**
+	 * Machine epsilon.
+	 */
+	double eps;
+
+};
+
+#endif /* LCSMETRIC_H_ */