103#ifndef vtkKMeansStatistics_h
104#define vtkKMeansStatistics_h
106#include "vtkFiltersStatisticsModule.h"
109VTK_ABI_NAMESPACE_BEGIN
181 vtkStringToken parameterName,
const std::string& algorithmParameters)
override;
maintain an unordered list of data objects
general representation of visualization data
dynamic, self-adjusting array of double
dynamic, self-adjusting array of vtkIdType
a simple class to control print indentation
dynamic, self-adjusting array of int
measure distance from k-means cluster centers
int MaxNumIterations
This is the maximum number of iterations allowed if the new cluster centers have not yet converged.
void SelectAssessFunctor(vtkTable *inData, vtkDataObject *inMeta, vtkStringArray *rowNames, AssessFunctor *&dfunc) override
Provide the appropriate assessment functor.
static vtkKMeansStatistics * New()
virtual void UpdateClusterCenters(vtkTable *newClusterElements, vtkTable *curClusterElements, vtkIdTypeArray *numMembershipChanges, vtkIdTypeArray *numDataElementsInCluster, vtkDoubleArray *error, vtkIdTypeArray *startRunID, vtkIdTypeArray *endRunID, vtkIntArray *computeRun)
Subroutine to update new cluster centers from the old centers.
char * KValuesArrayName
This is the name of the column that specifies the number of clusters in each run.
vtkKMeansDistanceFunctor * DistanceFunctor
This is the Distance functor.
bool SetParameter(const char *parameter, int index, vtkVariant value) override
A convenience method for setting properties by name.
void AppendAlgorithmParameters(std::string &algorithmParameters) const override
Provide a string that can be used to recreate an instance of this algorithm.
virtual vtkIdType GetTotalNumberOfObservations(vtkIdType numObservations)
Subroutine to get the total number of observations.
std::size_t ConsumeNextAlgorithmParameter(vtkStringToken parameterName, const std::string &algorithmParameters) override
Implement the inverse of AppendAlgorithmParameters(): given parameters, update this algorithm.
void PrintSelf(ostream &os, vtkIndent indent) override
Methods invoked by print to print information about the object including superclasses.
int DefaultNumberOfClusters
This is the default number of clusters used when the user does not provide initial cluster centers.
void Test(vtkTable *, vtkStatisticalModel *, vtkTable *) override
Execute the calculations required by the Test option.
void Derive(vtkStatisticalModel *) override
Execute the calculations required by the Derive option.
int InitializeDataAndClusterCenters(vtkTable *inParameters, vtkTable *inData, vtkTable *dataElements, vtkIdTypeArray *numberOfClusters, vtkTable *curClusterElements, vtkTable *newClusterElements, vtkIdTypeArray *startRunID, vtkIdTypeArray *endRunID)
Subroutine to initialize the cluster centers using those provided by the user in input port LEARN_PAR...
virtual void CreateInitialClusterCenters(vtkIdType numToAllocate, vtkIdTypeArray *numberOfClusters, vtkTable *inData, vtkTable *curClusterElements, vtkTable *newClusterElements)
Subroutine to initialize cluster centerss if not provided by the user.
~vtkKMeansStatistics() override
double Tolerance
This is the percentage of data elements that swap cluster IDs.
void Assess(vtkTable *, vtkStatisticalModel *, vtkTable *) override
Execute the calculations required by the Assess option.
bool Aggregate(vtkDataObjectCollection *, vtkStatisticalModel *) override
Given a collection of models, calculate aggregate model NB: not implemented.
void Learn(vtkTable *, vtkTable *, vtkStatisticalModel *) override
Execute the calculations required by the Learn option.
virtual void SetDistanceFunctor(vtkKMeansDistanceFunctor *)
Set the DistanceFunctor.
a base class for statistical modeling of other data
A base class for a functor that assesses data.
vtkStatisticsAlgorithm()
Return a new instance of a subclass named and configured by the algorithmParameters.
a vtkAbstractArray subclass for strings
Represent a string by its integer hash.
A table, which contains similar-typed columns of data.
A type representing the union of many types.