ClusterHierarchical Class Reference

Hierarchical clustering with generic clustering functions. More...

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

Collaboration diagram for ClusterHierarchical:

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, float offset, 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.

Cluster data using SimilarityComparator and ClusterFunctor.

Creates a DistanceMatrix (if an empty matrix is passed) and the clustering is started. Clustering stops if the ClusterHierarchical::threshold_ is reached by the ClusterFunctor.

First template parameter is the cluster object type, Second template parameter is the similarity functor applicable to the type.

For example, 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