Detailed Description

Structure for performing the kmeans clustering algorithm on a set of samples.

Definition at line 36 of file LALInferenceClusteredKDE.h.

Data Fields
gsl_matrix *	data
	Data to be clustered (typically whitened) More...

INT4	dim
	Dimension of data. More...

INT4	npts
	Number of points being clustered. More...

INT4	k
	Number of clusters. More...

INT4	has_changed
	Flag indicating a change to cluster assignmens. More...

REAL8(*	dist )(gsl_vector x, gsl_vector y)
	Distance funtion. More...

void(*	centroid )(gsl_vector centroid, gsl_matrix data, INT4 *mask)
	Find centroid. More...

INT4 *	assignments
	Cluster assignments. More...

INT4 *	sizes
	Cluster sizes. More...

INT4 *	mask
	Mask used to select data from individual clusters. More...

REAL8 *	weights
	Fraction of data points in each cluster. More...

gsl_vector *	mean
	Mean of unwhitened data (for tranforming points) More...

gsl_vector *	std
	Std deviations of unwhitened data. More...

gsl_matrix *	cov
	Covariance matrix of data. More...

gsl_matrix *	centroids
	Array with rows containing cluster centroids. More...

gsl_matrix *	recursive_centroids
	Matrix used to accumulate tested centroids. More...

gsl_rng *	rng
	Random number generator. More...

REAL8	error
	Error of current clustering. More...

LALInferenceKDE **	KDEs
	Array of KDEs, one for each cluster. More...

Field Documentation

◆ data

gsl_matrix* LALInferenceKmeans::data

Data to be clustered (typically whitened)

Definition at line 39 of file LALInferenceClusteredKDE.h.

◆ dim

INT4 LALInferenceKmeans::dim

Dimension of data.

Definition at line 40 of file LALInferenceClusteredKDE.h.

◆ npts

INT4 LALInferenceKmeans::npts

Number of points being clustered.

Definition at line 41 of file LALInferenceClusteredKDE.h.

◆ k

INT4 LALInferenceKmeans::k

Number of clusters.

Definition at line 42 of file LALInferenceClusteredKDE.h.

◆ has_changed

INT4 LALInferenceKmeans::has_changed

Flag indicating a change to cluster assignmens.

Definition at line 43 of file LALInferenceClusteredKDE.h.

◆ dist

REAL8(* LALInferenceKmeans::dist) (gsl_vector *x, gsl_vector *y)

Distance funtion.

Definition at line 45 of file LALInferenceClusteredKDE.h.

◆ centroid

void(* LALInferenceKmeans::centroid) (gsl_vector *centroid, gsl_matrix *data, INT4 *mask)

Find centroid.

Definition at line 46 of file LALInferenceClusteredKDE.h.

◆ assignments

INT4* LALInferenceKmeans::assignments

Cluster assignments.

Definition at line 48 of file LALInferenceClusteredKDE.h.

◆ sizes

INT4* LALInferenceKmeans::sizes

Cluster sizes.

Definition at line 49 of file LALInferenceClusteredKDE.h.

◆ mask

INT4* LALInferenceKmeans::mask

Mask used to select data from individual clusters.

Definition at line 50 of file LALInferenceClusteredKDE.h.

◆ weights

REAL8* LALInferenceKmeans::weights

Fraction of data points in each cluster.

Definition at line 51 of file LALInferenceClusteredKDE.h.

◆ mean

gsl_vector* LALInferenceKmeans::mean

Mean of unwhitened data (for tranforming points)

Definition at line 52 of file LALInferenceClusteredKDE.h.

◆ std

gsl_vector* LALInferenceKmeans::std

Std deviations of unwhitened data.

Definition at line 53 of file LALInferenceClusteredKDE.h.

◆ cov

gsl_matrix* LALInferenceKmeans::cov

Covariance matrix of data.

Definition at line 54 of file LALInferenceClusteredKDE.h.

◆ centroids

gsl_matrix* LALInferenceKmeans::centroids

Array with rows containing cluster centroids.

Definition at line 55 of file LALInferenceClusteredKDE.h.

◆ recursive_centroids

gsl_matrix* LALInferenceKmeans::recursive_centroids

Matrix used to accumulate tested centroids.

Definition at line 56 of file LALInferenceClusteredKDE.h.

◆ rng

gsl_rng* LALInferenceKmeans::rng

Random number generator.

Definition at line 57 of file LALInferenceClusteredKDE.h.

◆ error

REAL8 LALInferenceKmeans::error

Error of current clustering.

Definition at line 59 of file LALInferenceClusteredKDE.h.

◆ KDEs

LALInferenceKDE** LALInferenceKmeans::KDEs

Array of KDEs, one for each cluster.

Definition at line 61 of file LALInferenceClusteredKDE.h.