jhplot.stat
Class PCA

java.lang.Object
  jhplot.stat.PCA

public class PCA
extends Object

Perform a principle component analysis

Author:

Yann RICHET, Sergei Chekanov

Constructor Summary

PCA(double[][] xy)
Initialize 2D PCA analysis

PCA(P1D p1d)
Perform PCA analysis using P1D object (in 2D).

Method Summary

double[][]	center_reduce(double[][] x)
void	doc() Show online documentation.
void	eval()
double	getCoordinate(int k, int i) Positions of the last coordinates of the projection vectors (eigenvectors)
double[][]	getCovariance() Get covariance matrix
double[]	getD() Get transpose
double	getEigenvalue(int k) Information about eigenvalues
double	getEigenvalueTot(int k) Express eigenvalues as percentage of total
double	getMean(int k) Get means for the component k
double	getStd(int k) Get standard deviations
String	getSummary() Return projection vectors and information per projection vector.
double[]	inv_center_reduce(double[] y)
double[][]	inv_center_reduce(double[][] y)
static void	main(String[] args)

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

PCA

public PCA(double[][] xy)

Initialize 2D PCA analysis

Parameters:

xy - array in X

PCA

public PCA(P1D p1d)

Perform PCA analysis using P1D object (in 2D). All weights for points are set to 1. X and Y component of P1D are used for the PCA.

Parameters:

p1d - P1D input objects

Method Detail

eval

public void eval()

center_reduce

public double[][] center_reduce(double[][] x)

inv_center_reduce

public double[] inv_center_reduce(double[] y)

inv_center_reduce

public double[][] inv_center_reduce(double[][] y)

getSummary

public String getSummary()

Return projection vectors and information per projection vector.

Returns:

text

getEigenvalue

public double getEigenvalue(int k)

Information about eigenvalues

Parameters:

k - - integer value (axis index of the projection)

Returns:

getEigenvalueTot

public double getEigenvalueTot(int k)

Express eigenvalues as percentage of total

Parameters:

k - integer value (axis index of the projection)

Returns:

getCoordinate

public double getCoordinate(int k,
                            int i)

Positions of the last coordinates of the projection vectors (eigenvectors)

Parameters:

k - - integer value (axis index)

i - - index (position)

Returns:

getCovariance

public double[][] getCovariance()

Get covariance matrix

Returns:

getD

public double[] getD()

Get transpose

Returns:

getMean

public double getMean(int k)

Get means for the component k

Parameters:

k - index of the axis

Returns:

getStd

public double getStd(int k)

Get standard deviations

Parameters:

k - index of the axis

Returns:

main

public static void main(String[] args)

doc

public void doc()

Show online documentation.