Base class for cluster functors. More...
#include <OpenMS/COMPARISON/CLUSTERING/ClusterFunctor.h>
Classes | |
| class | InsufficientInput |
| Exception thrown if not enough data (<2) is used. More... | |
Public Member Functions | |
| ClusterFunctor () | |
| default constructor | |
| ClusterFunctor (const ClusterFunctor &source) | |
| copy constructor | |
| virtual | ~ClusterFunctor () |
| destructor | |
| ClusterFunctor & | operator= (const ClusterFunctor &source) |
| assignment operator | |
| virtual void | operator() (DistanceMatrix< Real > &original_distance, std::vector< BinaryTreeNode > &cluster_tree, const Real threshold=1) const =0 |
| abstract for clustering the indices according to their respective element distances | |
Static Public Member Functions | |
| static void | registerChildren () |
| registers all derived products | |
Detailed Description
Base class for cluster functors.
Each cluster functor employs a different method for stepwise merging clusters up to a given threshold, starting from the most elementary partition of data. Elements are represented by indices of a given distance matrix, which also should represent the order of input.
Constructor & Destructor Documentation
| ClusterFunctor | ( | ) |
default constructor
| ClusterFunctor | ( | const ClusterFunctor & | source | ) |
copy constructor
| virtual ~ClusterFunctor | ( | ) | [virtual] |
destructor
Member Function Documentation
| virtual void operator() | ( | DistanceMatrix< Real > & | original_distance, | |
| std::vector< BinaryTreeNode > & | cluster_tree, | |||
| const Real | threshold = 1 | |||
| ) | const [pure virtual] |
abstract for clustering the indices according to their respective element distances
- Parameters:
-
original_distance DistanceMatrix<Real> containing the distances of the elements to be clustered, will be changed during clustering process, make sure to have a copy or be able to redo cluster_tree vector< BinaryTreeNode >, represents the clustering, each node contains the next merged clusters (not element indices) and their distance, strict order is kept: left_child < right_child, threshold Real value, the minimal distance from which on cluster merging is considered unrealistic. By default set to 1, i.e. complete clustering until only one cluster remains
original_distance is considered mirrored at the main diagonal, so only entrys up the main diagonal are used. The threshold can be taken from the maximal distance of two elements considered related and adapted in a way corresponding to the employed clustering method. The results are represented by cluster_tree, to get the actual clustering (with element indices) from a certain step of the clustering
- See also:
- BinaryTreeNode , ClusterAnalyzer::cut
| ClusterFunctor& operator= | ( | const ClusterFunctor & | source | ) |
assignment operator
| static void registerChildren | ( | ) | [static] |
registers all derived products
| OpenMS / TOPP release 1.10.0 | Documentation generated on Thu Mar 7 2013 09:42:50 using doxygen 1.7.1 |