baseCode.math
Class MatrixStats

java.lang.Object
  baseCode.math.MatrixStats

public class MatrixStats

extends java.lang.Object

Copyright (c) 2004 Columbia University

Version:

$Id: MatrixStats.java,v 1.10 2004/08/17 21:17:40 pavlidis Exp $

Author:

pavlidis

Constructor Summary

MatrixStats()

Method Summary

static DenseDoubleMatrix2DNamed	correlationMatrix(AbstractNamedDoubleMatrix data)
static SparseDoubleMatrix2DNamed	correlationMatrix(AbstractNamedDoubleMatrix data, double threshold)
static void	countsNormalize(AbstractNamedDoubleMatrix matrixToNormalize, double sigma) Normalize a count matrix in place to be a transition matrix.
static double	max(AbstractNamedDoubleMatrix matrix) Compute the maximum value in the matrix.
static double	min(AbstractNamedDoubleMatrix matrix) Find the minimum of the entire matrix.
static void	rbfNormalize(AbstractNamedDoubleMatrix matrixToNormalize, double sigma) Normalize a matrix in place to be a transition matrix.

Methods inherited from class java.lang.Object

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

Constructor Detail

MatrixStats

public MatrixStats()

Method Detail

correlationMatrix

public static DenseDoubleMatrix2DNamed correlationMatrix(AbstractNamedDoubleMatrix data)

Parameters:

data - DenseDoubleMatrix2DNamed

Returns:

DenseDoubleMatrix2DNamed

correlationMatrix

public static SparseDoubleMatrix2DNamed correlationMatrix(AbstractNamedDoubleMatrix data,
                                                          double threshold)

Parameters:

data - DenseDoubleMatrix2DNamed

threshold - only correlations with absolute values above this level are stored.

Returns:

SparseDoubleMatrix2DNamed

min

public static double min(AbstractNamedDoubleMatrix matrix)

Find the minimum of the entire matrix.

Parameters:

matrix - DenseDoubleMatrix2DNamed

Returns:

the smallest value in the matrix

max

public static double max(AbstractNamedDoubleMatrix matrix)

Compute the maximum value in the matrix.

Parameters:

matrix - DenseDoubleMatrix2DNamed

Returns:

the largest value in the matrix

rbfNormalize

public static void rbfNormalize(AbstractNamedDoubleMatrix matrixToNormalize,
                                double sigma)

Normalize a matrix in place to be a transition matrix. Assumes that values operate such that small values like p values represent closer distances, and the values are probabilities.

Each point is first transformed via v' = exp(-v/sigma). Then the values for each node's edges are adjusted to sum to 1.

Parameters:

matrixToNormalize -

sigma - a scaling factor for the input values.

countsNormalize

public static void countsNormalize(AbstractNamedDoubleMatrix matrixToNormalize,
                                   double sigma)

Normalize a count matrix in place to be a transition matrix. Assumes that the values are defined as "bigger is better"

Parameters:

matrixToNormalize -

sigma -