cluster.cpp File Reference

#include "geoslib_old_f.h"
#include "Basic/Law.hpp"
#include <limits.h>

Macros
#define	DBL_MAXIMUM   1.e30
#define	DATA(iech, ivar)   (data[(iech) * nvar + (ivar)])
#define	DATA1(iech, ivar)   (data1[(iech) * nvar + (ivar)])
#define	DATA2(iech, ivar)   (data2[(iech) * nvar + (ivar)])
#define	CDATA(icl, ivar)   (cdata[(icl) * nvar + (ivar)])
#define	DISTMATRIX(i, j)   (distmatrix[(i) * nech + (j)])

Functions
double *	kclusters (double *data, int nvar, int nech, int nclusters, int npass, int mode, int verbose)
int *	kmedoids (double *data, int nvar, int nech, int nclusters, int npass, int verbose)

Macro Definition Documentation

#define CDATA	(		icl,
			ivar
	)		(cdata[(icl) * nvar + (ivar)])

#define DATA	(		iech,
			ivar
	)		(data[(iech) * nvar + (ivar)])

#define DATA1	(		iech,
			ivar
	)		(data1[(iech) * nvar + (ivar)])

#define DATA2	(		iech,
			ivar
	)		(data2[(iech) * nvar + (ivar)])

#define DBL_MAXIMUM   1.e30

#define DISTMATRIX	(		i,
			j
	)		(distmatrix[(i) * nech + (j)])

Function Documentation

double* kclusters	(	double *	data,
		int	nvar,
		int	nech,
		int	nclusters,
		int	npass,
		int	mode,
		int	verbose
	)

Perform k-means clustering on a given set of variables. The number of clusters is given in input

Returns

Array of cluster coordinates

Parameters

[in]	data	Array of values
[in]	nvar	Number of samples
[in]	nech	Number of variables
[in]	nclusters	Number if clusters
[in]	npass	Number of times clustering is performed
[in]	mode	0 for k-means and 1 for k-medians
[in]	verbose	Verbose option

int* kmedoids	(	double *	data,
		int	nvar,
		int	nech,
		int	nclusters,
		int	npass,
		int	verbose
	)

Perform k-medoids clustering on a given set of variables. The number of clusters is given in input

Returns

Array of cluster indices

Parameters

[in]	data	Array of values
[in]	nvar	Number of samples
[in]	nech	Number of variables
[in]	nclusters	Number if clusters
[in]	npass	Number of times clustering is performed
[in]	verbose	Verbose option