Clustering Class Reference

List of all members.

Public Member Functions
	Clustering (void)
	~Clustering (void)

Static Public Member Functions
static void	Eigen (glm::mat2 &rvec, glm::vec2 &rval, glm::mat2 covariance)
static void	SVD (glm::vec2 &rw, glm::mat2 &ru, glm::mat2 &rvt, glm::mat2 covariance)
static float	getDensity (glm::vec2 pos, glm::vec2 mean, glm::mat2 covariance)
static glm::mat2	CalculateCovariance (glm::vec2 radii, float phi)
static void	kMeans (glm::vec2 **x, glm::vec2 *m, float *numComponents, float **g, int N, int K, int Iterations)
static void	DoClustering (glm::vec2 *m, glm::mat2 *c, glm::vec2 *x, int N, int K)
static glm::vec4 *	CalculateTFTexture (glm::vec2 *m, glm::mat2 *covariance, glm::vec4 *color)

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Constructor & Destructor Documentation

Clustering::Clustering

(

void

)

Standard Konstruktor Clustering

Clustering::~Clustering

(

void

)

Standard Dekonstruktor Clustering

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Member Function Documentation

glm::mat2 Clustering::CalculateCovariance ( glm::vec2  radii, float  phi  )

static

Method calculates Covariance Matrix

Parameters:

radii	... radiii
phi	... phi

Returns:

Covariance Matrix

glm::vec4 * Clustering::CalculateTFTexture ( glm::vec2 *  m, glm::mat2 *  covariance, glm::vec4 *  color  )

static

Draw Cluster on TF

Parameters:

m	... Meanvalues
c	... Covariance Matrix
x	... Color

void Clustering::DoClustering ( glm::vec2 *  m, glm::mat2 *  c, glm::vec2 *  x, int  N, int  K  )

static

Performs Clustering

Parameters:

m	... Meanvalues
c	... Covariance Matrix
x	... Data vector
k	... Number of Clusters

void Clustering::Eigen ( glm::mat2 &  rvec, glm::vec2 &  rval, glm::mat2  covariance  )

static

Calculates Eigenvectors and values

Parameters:

rvec	... Eigenvector
rval	... Eigenvalues
covariance	... Covariance Matrix

float Clustering::getDensity ( glm::vec2  pos, glm::vec2  mean, glm::mat2  covariance  )

static

Returns Density of sample ponts

Parameters:

pos	... Position to estimate Density
mean	... mean value of cluster
covariance	... covariance of cluster

void Clustering::kMeans ( glm::vec2 **  x, glm::vec2 *  m, float *  numComponents, float **  g, int  N, int  K, int  Iterations  )

static

Performs kMeans Clustering

Parameters:

x	... Data vector
x	... Data vector
m	... Meanvalues
numComponents	... Number of Samples of each Clusters
g	... Properbility
K	... Number of Clusters
N	... Number of Samples
Iterations...	Number of Iterations

void Clustering::SVD ( glm::vec2 &  rw, glm::mat2 &  ru, glm::mat2 &  rvt, glm::mat2  covariance  )

static

Performs Singluar Value Decomposition

Parameters:

rw	... rw values
ru	... rv matrix
rvt	... rvt matrix
covariance	... Covariance Matrix

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The documentation for this class was generated from the following files:

• Clustering.h
• Clustering.cpp