Chris@26: /* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
Chris@26: 
Chris@26: /*
Chris@26:     Vamp feature extraction plugin using the MATCH audio alignment
Chris@26:     algorithm.
Chris@26: 
Chris@26:     Centre for Digital Music, Queen Mary, University of London.
Chris@26:     This file copyright 2007 Simon Dixon, Chris Cannam and QMUL.
Chris@26:     
Chris@26:     This program is free software; you can redistribute it and/or
Chris@26:     modify it under the terms of the GNU General Public License as
Chris@26:     published by the Free Software Foundation; either version 2 of the
Chris@26:     License, or (at your option) any later version.  See the file
Chris@26:     COPYING included with this distribution for more information.
Chris@26: */
Chris@26: 
Chris@26: #ifndef DISTANCE_METRIC_H
Chris@26: #define DISTANCE_METRIC_H
Chris@26: 
Chris@26: #include <vector>
Chris@26: 
Chris@26: class DistanceMetric
Chris@26: {
Chris@26: public:
Chris@26:     enum DistanceNormalisation {
Chris@26:             
Chris@26:         /** Do not normalise distance metrics */
Chris@26:         NoDistanceNormalisation,
Chris@26: 
Chris@26:         /** Normalise distance metric for pairs of frames by the sum
Chris@26:          *  of the two frames. */
Chris@26:         NormaliseDistanceToSum,
Chris@26: 
Chris@26:         /** Normalise distance metric for pairs of frames by the log
Chris@26:          *  of the sum of the frames. */
Chris@26:         NormaliseDistanceToLogSum,
Chris@26:     };
Chris@26: 
Chris@143:     struct Parameters {
Chris@143: 
Chris@143:         Parameters() :
Chris@144:             norm(NormaliseDistanceToLogSum)
Chris@143:         {}
Chris@143: 
Chris@143:         /** Normalisation for distance metrics. */
Chris@143:         DistanceNormalisation norm;
Chris@143:     };
Chris@143:     
Chris@143:     DistanceMetric(Parameters params);
Chris@26:     
Chris@26:     /** Calculates the Manhattan distance between two vectors, with an
Chris@26:      *  optional normalisation by the combined values in the
Chris@26:      *  vectors. Since the vectors contain energy, this could be
Chris@26:      *  considered as a squared Euclidean distance metric. Note that
Chris@26:      *  normalisation assumes the values are all non-negative.
Chris@26:      *
Chris@26:      *  @param f1 one of the vectors involved in the distance calculation
Chris@26:      *  @param f2 one of the vectors involved in the distance calculation
Chris@26:      *  @return the distance
Chris@26:      */
Chris@26:     double calcDistance(const std::vector<double> &f1,
Chris@26: 			const std::vector<double> &f2);
Chris@26:     
Chris@26: private:
Chris@143:     Parameters m_params;
Chris@26: };
Chris@26: 
Chris@26: #endif