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// $Id: DynamicNearestNeighbours.hh 2687 2011-11-14 11:17:51Z soyez $
//
// Copyright (c) 2005-2011, Matteo Cacciari, Gavin P. Salam and Gregory Soyez
//
//----------------------------------------------------------------------
// This file is part of FastJet.
//
// FastJet 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 2 of the License, or
// (at your option) any later version.
//
// The algorithms that underlie FastJet have required considerable
// development and are described in hep-ph/0512210. If you use
// FastJet as part of work towards a scientific publication, please
// include a citation to the FastJet paper.
//
// FastJet is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with FastJet. If not, see .
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#ifndef __FASTJET_DYNAMICNEARESTNEIGHBOURS_HH__
#define __FASTJET_DYNAMICNEARESTNEIGHBOURS_HH__
#include
#include
#include
#include
#include
#include "fastjet/internal/numconsts.hh"
FASTJET_BEGIN_NAMESPACE // defined in fastjet/internal/base.hh
/// Shortcut for dealing with eta-phi coordinates.
//typedef std::pair EtaPhi;
/// \if internal_doc
/// @ingroup internal
/// \class EtaPhi
/// use a class instead of a pair so that phi can be sanitized
/// and put into proper range on initialization.
/// \endif
class EtaPhi {
public:
double first, second;
EtaPhi() {}
EtaPhi(double a, double b) {first = a; second = b;}
/// put things into the desired range.
void sanitize() {
if (second < 0) second += twopi;
if (second >= twopi) second -= twopi;
}
};
/// \if internal_doc
/// @ingroup internal
/// \class DnnError
/// class corresponding to errors that will be thrown by Dynamic
/// Nearest Neighbours code
/// \endif
class DnnError {
public:
// constructors
DnnError() {;};
DnnError(const std::string & message_in) {
_message = message_in; std::cerr << message_in << std::endl;};
std::string message() const {return _message;};
private:
std::string _message;
};
/// \if internal_doc
/// @ingroup internal
/// \class DynamicNearestNeighbours
/// Abstract base class for quick location of nearest neighbours in a set of
/// points.
///
/// Abstract base class for quick location of nearest neighbours in a set of
/// points, with facilities for adding and removing points from the
/// set after initialisation. Derived classes will be
/// named according to the convention DnnSomeName (e.g. DnnPlane).
///
/// The main purpose of this abstract base class is to define the
/// general interface of a whole set of classes that deal with
/// nearest-neighbour location on different 2-d geometries and with
/// various underlying data structures and algorithms.
///
/// \endif
class DynamicNearestNeighbours {
public:
/// Dummy initialiser --- does nothing!
//virtual DynamicNearestNeighbours() {};
/// Initialiser --- sets up the necessary structures to allow efficient
/// nearest-neighbour finding on the std::vector of input points
//virtual DynamicNearestNeighbours(const std::vector &,
// const bool & verbose = false ) = 0;
/// Returns the index of the nearest neighbour of point labelled
/// by ii (assumes ii is valid)
virtual int NearestNeighbourIndex(const int & ii) const = 0;
/// Returns the distance to the nearest neighbour of point labelled
/// by index ii (assumes ii is valid)
virtual double NearestNeighbourDistance(const int & ii) const = 0;
/// Returns true iff the given index corresponds to a point that
/// exists in the DNN structure (meaning that it has been added, and
/// not removed in the meantime)
virtual bool Valid(const int & index) const = 0;
/// remove the points labelled by the std::vector indices_to_remove, and
/// add the points specified by the std::vector points_to_add
/// (corresponding indices will be calculated automatically); the
/// idea behind this routine is that the points to be added will
/// somehow be close to the one or other of the points being removed
/// and this can be used by the implementation to provide hints for
/// inserting the new points in whatever structure it is using. In a
/// kt-algorithm the points being added will be a result of a
/// combination of the points to be removed -- hence the proximity
/// is (more or less) guaranteed.
virtual void RemoveAndAddPoints(const std::vector & indices_to_remove,
const std::vector & points_to_add,
std::vector & indices_added,
std::vector & indices_of_updated_neighbours) = 0;
/// Remove the point labelled by index and return the list of
/// points whose nearest neighbours have changed in the process
inline void RemovePoint (const int & index,
std::vector & indices_of_updated_neighbours) {
std::vector indices_added;
std::vector points_to_add;
std::vector indices_to_remove(1);
indices_to_remove[0] = index;
RemoveAndAddPoints(indices_to_remove, points_to_add, indices_added,
indices_of_updated_neighbours
);};
/// Removes the two points labelled by index1, index2 and adds in the
/// a point with coordinates newpoint; it returns an index for the new
/// point (index 3) and a std::vector of indices of neighbours whose
/// nearest neighbour has changed (the list includes index3, i.e. the new
/// point).
inline void RemoveCombinedAddCombination(
const int & index1, const int & index2,
const EtaPhi & newpoint,
int & index3,
std::vector & indices_of_updated_neighbours) {
std::vector indices_added(1);
std::vector points_to_add(1);
std::vector indices_to_remove(2);
indices_to_remove[0] = index1;
indices_to_remove[1] = index2;
points_to_add[0] = newpoint;
RemoveAndAddPoints(indices_to_remove, points_to_add, indices_added,
indices_of_updated_neighbours
);
index3 = indices_added[0];
};
/// destructor -- here it is now implemented
virtual ~DynamicNearestNeighbours () {}
};
FASTJET_END_NAMESPACE
#endif // __FASTJET_DYNAMICNEARESTNEIGHBOURS_HH__