ClusterHierarchical Class Reference

Hierarchical clustering with generic clustering functions. More...

#include <OpenMS/COMPARISON/CLUSTERING/ClusterHierarchical.h>

Public Member Functions
	ClusterHierarchical ()
	default constructor More...
	ClusterHierarchical (const ClusterHierarchical &source)
	copy constructor More...
virtual	~ClusterHierarchical ()
	destructor More...
template<typename Data , typename SimilarityComparator >
void	cluster (std::vector< Data > &data, const SimilarityComparator &comparator, const ClusterFunctor &clusterer, std::vector< BinaryTreeNode > &cluster_tree, DistanceMatrix< float > &original_distance)
	Clustering function. More...
void	cluster (std::vector< PeakSpectrum > &data, const BinnedSpectrumCompareFunctor &comparator, double sz, UInt sp, const ClusterFunctor &clusterer, std::vector< BinaryTreeNode > &cluster_tree, DistanceMatrix< float > &original_distance)
	clustering function for binned PeakSpectrum More...
double	getThreshold ()
	get the threshold More...
void	setThreshold (double x)

Private Attributes
double	threshold_
	the threshold given to the ClusterFunctor More...

Detailed Description

Hierarchical clustering with generic clustering functions.

ClusterHierarchical clusters objects with corresponding distancemethod and clusteringmethod.

Constructor & Destructor Documentation

ClusterHierarchical() [1/2]

ClusterHierarchical ( )

inline

default constructor

ClusterHierarchical() [2/2]

ClusterHierarchical ( const ClusterHierarchical &  source )

inline

copy constructor

~ClusterHierarchical()

virtual ~ClusterHierarchical ( )

inlinevirtual

destructor

Member Function Documentation

cluster()

void cluster ( std::vector< Data > &  data, const SimilarityComparator &  comparator, const ClusterFunctor &  clusterer, std::vector< BinaryTreeNode > &  cluster_tree, DistanceMatrix< float > &  original_distance  )

inline

Clustering function.

Conducts the SimilarityComparator with a ClusterFunctor an produces a clustering. Will create a DistanceMatrix if not yet created and start the clustering up to the given ClusterHierarchical::threshold_ used for the ClusterFunctor. The type of the objects to be clustered has to be the first template argument, the similarity functor applicable to this type must be the second template argument, e.g. for PeakSpectrum with a PeakSpectrumCompareFunctor. The similarity functor must provide the similarity calculation with the ()-operator and yield normalized values in range of [0,1] for the type of < Data >.

Parameters

data	vector of objects to be clustered
comparator	similarity functor fitting for types in data
clusterer	a clustermethod implementation, baseclass ClusterFunctor
cluster_tree	the vector that will hold the BinaryTreeNodes representing the clustering (for further investigation with the ClusterAnalyzer methods)
original_distance	the DistanceMatrix holding the pairwise distances of the elements in data, will be made newly if given size does not fit to the number of elements given in @ data

See also

ClusterFunctor, BinaryTreeNode, ClusterAnalyzer

References DistanceMatrix< Value >::clear(), DistanceMatrix< Value >::dimensionsize(), DistanceMatrix< Value >::resize(), and DistanceMatrix< Value >::setValueQuick().

Referenced by SpectraMerger::mergeSpectraPrecursors().

getThreshold()

double getThreshold ( )

inline

get the threshold

setThreshold()

void setThreshold ( double  x )

inline

set the threshold (in terms of distance) The default is 1, i.e. only at similarity 0 the clustering stops. Warning: clustering is not supported by all methods yet (e.g. SingleLinkage does ignore it).

Member Data Documentation

threshold_

double threshold_

private

the threshold given to the ClusterFunctor