de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures
Class Measure

java.lang.Object
  de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure

All Implemented Interfaces:

InstantiableFromParameterSet, Storable, Cloneable

Direct Known Subclasses:

BTExplainingAwayResidual, BTMutualInformation, InhomogeneousMarkov, PMMExplainingAwayResidual, PMMMutualInformation

public abstract class Measure
extends Object
implements Cloneable, Storable, InstantiableFromParameterSet

Class for structure measures that derive an optimal structure with respect to some criterion within a class of possible structures from data.

Author:

Jan Grau

Constructor Summary

Measure()

Method Summary

Measure	clone()
protected static void	fillTensor(Tensor t, double[][] weights) Fills a Tensor t with the weights defined in weights.
protected static void	fillTensor(Tensor t, double[][][] weights) Fills a Tensor t with the weights defined in weights.
protected static double[][][]	getCMI(double[][][][][][] fgStats, double[][][][][][] bgStats, double n) Computes the conditional mutual information from fgStats and bgStats counted on sequences with a total weight of n.
protected static double[][]	getCMI(double[][][][] fgStats, double[][][][] bgStats, double n, double nFg, double nBg) Computes the conditional mutual information from fgStats and bgStats counted on sequences with a total weight of nFg and nBg, respectively.
static double[][][]	getEAR(double[][][][][][] fgStats, double[][][][][][] bgStats, double nFg, double nBg) Computes the explaining away residual from fgStats and bgStats counted on sequences with a total weight of nFg and nBg, respectively.
protected static double[][]	getEAR(double[][][][] fgStats, double[][][][] bgStats, double nFg, double nBg) Computes the explaining away residual from fgStats and bgStats counted on sequences with a total weight of nFg and nBg, respectively.
abstract String	getInstanceName() Returns the name of the Measure and possibly some additional information about the current instance.
protected static double[][][]	getMI(double[][][][][][] counts, double n) Computes the mutual information from counts counted on sequences with a total weight of n.
protected static double[][]	getMI(double[][][][] counts, double n) Computes the mutual information from counts counted on sequences with a total weight of n.
abstract int[][]	getParents(Sample fg, Sample bg, double[] weightsFg, double[] weightsBg, int length) Returns the optimal parents for the given data and weights.
protected static double[][][][]	getStatistics(Sample s, double[] weights, int length, double ess) Counts the occurrences of symbols of the AlphabetContainer of Sample s using weights.
protected static double[][][][][][]	getStatisticsOrderTwo(Sample s, double[] weights, int length, double ess) Counts the occurrences of symbols of the AlphabetContainer of Sample s using weights.
boolean	isShiftable() Indicates if Measure supports shifts.
protected static double	sum(double[] ar) Computes the sum of all elements in the array ar.
protected static int[][]	toParents(int[] o, byte order) Creates a new parent structure as defined by getParents(Sample, Sample, double[], double[], int) from an order and a topological ordering of positions.
protected static double[]	union(double[][] ar) Linearizes the arrays in the two-dimensional array ar to form a new, one-dimensional array.

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.jstacs.Storable

toXML

Methods inherited from interface de.jstacs.InstantiableFromParameterSet

getCurrentParameterSet

Constructor Detail

Measure

public Measure()

Method Detail

getInstanceName

public abstract String getInstanceName()

Returns the name of the Measure and possibly some additional information about the current instance.

Returns:

the name of the Measure

getParents

public abstract int[][] getParents(Sample fg,
                                   Sample bg,
                                   double[] weightsFg,
                                   double[] weightsBg,
                                   int length)
                            throws Exception

Returns the optimal parents for the given data and weights. The returned array of parents p at each position i is build as follows:

• p[i][p.length - 1] contains the index i itself
• p[i][p.length - 2] contains the "most important" parent
• ...
• p[i][0] contains the "least important" parent

Parameters:

fg - the data of the current (foreground) class

bg - the data of the negative (background) class

weightsFg - the weights for the sequences of fg

weightsBg - the weights for the sequences of bg

length - the length of the model, must be equal to the length of the sequences

Returns:

the the array p with the optimal parents

Throws:

Exception - if the lengths do not match or other problems concerning the data occur

clone

public Measure clone()
              throws CloneNotSupportedException

Overrides:

clone in class Object

Throws:

CloneNotSupportedException

toParents

protected static int[][] toParents(int[] o,
                                   byte order)

Creates a new parent structure as defined by getParents(Sample, Sample, double[], double[], int) from an order and a topological ordering of positions.

Parameters:

o - the topological ordering

order - the order

Returns:

the parent structure in a two-dimensional array

fillTensor

protected static void fillTensor(Tensor t,
                                 double[][] weights)

Fills a Tensor t with the weights defined in weights.

Parameters:

t - the Tensor to be filled

weights - the weights

fillTensor

protected static void fillTensor(Tensor t,
                                 double[][][] weights)

Fills a Tensor t with the weights defined in weights.

Parameters:

t - the Tensor to be filled

weights - the weights

getMI

protected static double[][][] getMI(double[][][][][][] counts,
                                    double n)

Computes the mutual information from counts counted on sequences with a total weight of n.

Parameters:

counts - the counts as returned by getStatisticsOrderTwo(Sample, double[], int, double)

n - the total weight

Returns:

the mutual information

getCMI

protected static double[][][] getCMI(double[][][][][][] fgStats,
                                     double[][][][][][] bgStats,
                                     double n)

Computes the conditional mutual information from fgStats and bgStats counted on sequences with a total weight of n.

Parameters:

fgStats - the counts in the foreground sequences as returned by getStatisticsOrderTwo(Sample, double[], int, double)

bgStats - the counts in the foreground sequences as returned by getStatisticsOrderTwo(Sample, double[], int, double)

n - the total weight

Returns:

the conditional mutual information

getEAR

public static double[][][] getEAR(double[][][][][][] fgStats,
                                  double[][][][][][] bgStats,
                                  double nFg,
                                  double nBg)

Computes the explaining away residual from fgStats and bgStats counted on sequences with a total weight of nFg and nBg, respectively.

Parameters:

fgStats - the counts in the foreground sequences as returned by getStatisticsOrderTwo(Sample, double[], int, double)

bgStats - the counts in the foreground sequences as returned by getStatisticsOrderTwo(Sample, double[], int, double)

nFg - the total weight in the foreground

nBg - the total weight in the background

Returns:

the explaining away residual

getStatisticsOrderTwo

protected static double[][][][][][] getStatisticsOrderTwo(Sample s,
                                                          double[] weights,
                                                          int length,
                                                          double ess)
                                                   throws Exception

Counts the occurrences of symbols of the AlphabetContainer of Sample s using weights. The array counts is indexed as follows:
counts[first index][second index][third index][symbol at first index][symbol at second index][symbol at third index] .

Parameters:

s - the data

weights - the weights

length - the length of the sequences

ess - the equivalent sample size

Returns:

the array counts with the symbol occurrences

Throws:

Exception - if the lengths do not match or other problems concerning the data occur

getStatistics

protected static double[][][][] getStatistics(Sample s,
                                              double[] weights,
                                              int length,
                                              double ess)
                                       throws Exception

Counts the occurrences of symbols of the AlphabetContainer of Sample s using weights. The array counts is indexed as follows:
counts[first index][second index][symbol at first index][symbol at second index] .

Parameters:

s - the data

weights - the weights

length - the length of the sequences

ess - the equivalent sample size

Returns:

the array counts with the symbol occurrences

Throws:

Exception - if the lengths do not match or other problems concerning the data occur

getMI

protected static double[][] getMI(double[][][][] counts,
                                  double n)

Computes the mutual information from counts counted on sequences with a total weight of n.

Parameters:

counts - the counts as defined in getStatistics(Sample, double[], int, double).

n - the total weight

Returns:

the mutual information

getCMI

protected static double[][] getCMI(double[][][][] fgStats,
                                   double[][][][] bgStats,
                                   double n,
                                   double nFg,
                                   double nBg)

Computes the conditional mutual information from fgStats and bgStats counted on sequences with a total weight of nFg and nBg, respectively.

Parameters:

fgStats - the counts as defined in getStatistics(Sample, double[], int, double) on the foreground

bgStats - the counts as defined in getStatistics(Sample, double[], int, double) on the background

n - the total weight

nFg - the total weight in the foreground

nBg - the total weight in the background

Returns:

the conditional mutual information

getEAR

protected static double[][] getEAR(double[][][][] fgStats,
                                   double[][][][] bgStats,
                                   double nFg,
                                   double nBg)

Computes the explaining away residual from fgStats and bgStats counted on sequences with a total weight of nFg and nBg, respectively.

Parameters:

fgStats - the counts as defined in getStatistics(Sample, double[], int, double) on the foreground

bgStats - the counts as defined in getStatistics(Sample, double[], int, double) on the background

nFg - the total weight in the foreground

nBg - the total weight in the background

Returns:

the explaining away residual

sum

protected static double sum(double[] ar)

Computes the sum of all elements in the array ar.

Parameters:

ar - the array

Returns:

the sum of the elements of the array

union

protected static double[] union(double[][] ar)

Linearizes the arrays in the two-dimensional array ar to form a new, one-dimensional array.

Parameters:

ar - the two-dimensional array

Returns:

the linearized one-dimensional array

isShiftable

public boolean isShiftable()

Indicates if Measure supports shifts.

Returns:

if Measure supports shifts