Documentation of 'jhplot.stat.PCA' Java class.
PCA
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jhplot.stat

Class PCA


  • public class PCA
extends java.lang.Object
    Perform a principle component analysis

    • Constructor Summary

      Constructors 
      Constructor and Description
      PCA(double[][] xy)
      Initialize 2D PCA analysis
      PCA(P1D p1d)
      Perform PCA analysis using P1D object (in 2D).

    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method and Description
      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
      java.lang.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(java.lang.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 java.lang.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(java.lang.String[] args)

      • doc

        public void doc()
        Show online documentation.
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