DiscrepancyContainer Class Reference

This class is used to compute, store and display discrepancies. More...

Public Member Functions
	DiscrepancyContainer (Discrepancy[] discrepancies)
	Creates a DiscrepancyContainer for the given discrepancies. More...
void	init (int n, String title, String xLabel, String yLabel)
	Initialize the container with enough space for n values of the parameter and sets the values to 0. More...
void	init (int n)
	Calls init(n,"","Parameter", "Discrepancy"). More...
void	reset (int i)
	Resets the values of the discrepancies at index i to 0. More...
void	reset ()
	Calls reset(i) for all indices i.
void	compute (int i, double[] points, int n)
	Computes the discrepancies of the first n values contained in points and sets the values at index i. More...
void	compute (int i, double[][] points, int n, int s)
	Computes the discrepancies of the first n values contained in points using the first s coordinates and sets the values at index i. More...
void	add (int i, double[] points, int n)
	Computes the discrepancies of the first n values contained in points, and adds the values at index i. More...
void	addSquare (int i, double[] points, int n)
	Computes the square of the discrepancies of the first n values contained in points, and adds the values at index i. More...
void	add (int i, double[][] points, int n, int s)
	Computes the discrepancies of the first n values contained in points using the first s coordinates, and adds the values at index i. More...
void	addSquare (int i, double[][] points, int n, int s)
	Computes the square discrepancies of the first n values contained in points using the first s coordinates, and adds the values at index i. More...
void	scale (int i, double scale)
	Multiplies all the discrepancies at index i by scale;. More...
void	scale (double scale)
	Calls scale(i,scale) for all indices i. More...
void	log2 (int i)
	Takes the logarithm in base 2 of the discrepancy values at index i. More...
void	square (int i)
	Squares the discrepancy values at index i. More...
void	setParam (int i, double paramValue)
	Sets the parameter value at index i to parmValue. More...
String	regressionToString ()
	Formats and returns a String containing the linear regression slopes for the discrepancies as function of the parameter.
void	toTexFile (String filename)
	Creates a file named filename.tex containing LaTeX code that can be compiled by pdfLaTeX to a graph of the discrepancies as function of the parameter. More...
void	toDatFile (String filename, String header)
	Creates a file named filename.dat and writes in it the given header, a table showing the discrepancies for the different values of the parameter and the linear regression slopes. More...
String	toString ()
	Returns a String containing a table showing the discrepancies for the different values of the parameter.

Protected Member Functions
void	calcRegressionSlope ()
	Computes the linear regression slope for the discrepancies as function of the parameter. More...

Package Attributes
int	nbDisc
String	xLabel
String	yLabel

Detailed Description

This class is used to compute, store and display discrepancies.

The method add computes the discrepancy of a given array of points for the selected discrepancies and associates them with a given index. One can assign a parameter value to this index (using setParam ) so that a graph or a data file is created showing the discrepancies as functions of the parameter. One can also scale the discrepancies of an index with a given scale factor or take the logarithm of the discrepancies.

The discrepancies are computed, assuming that the theoretical distribution of the points is over the unit hypercube \([0,1]^s\); thus all the coordinates of the points must be in \([0,1]\).

Constructor & Destructor Documentation

DiscrepancyContainer()

DiscrepancyContainer

(

Discrepancy []

discrepancies

)

Creates a DiscrepancyContainer for the given discrepancies.

Parameters

discrepancies

array containing the discrepancies to be used

Member Function Documentation

add() [1/2]

void add	(	int	i,
		double []	points,
		int	n
	)

Computes the discrepancies of the first n values contained in points, and adds the values at index i.

**NOTE: This method does not replace the values, it adds to them. Can be used with scale to calculate an average discrepancy over more than one point set.

Parameters

i	index where to add the discrepancies
points	values for which to compute the discrepancies
n	number of points to use

add() [2/2]

void add	(	int	i,
		double	points[][],
		int	n,
		int	s
	)

Computes the discrepancies of the first n values contained in points using the first s coordinates, and adds the values at index i.

**NOTE: This method does not replace the values, it adds to them. Can be used with scale to calculate an average discrepancy over more than one point set.

Parameters

i	index where to add the discrepancies
points	values for which to compute the discrepancies
n	number of points to use
s	number of coordinates to use for each point

addSquare() [1/2]

void addSquare	(	int	i,
		double []	points,
		int	n
	)

Computes the square of the discrepancies of the first n values contained in points, and adds the values at index i.

**NOTE: This method does not replace the values, it adds to them. Can be used with scale to calculate an average square discrepancy over more than one point set.

Parameters

i	index where to add the discrepancies
points	values for which to compute the discrepancies
n	number of points to use

addSquare() [2/2]

void addSquare	(	int	i,
		double	points[][],
		int	n,
		int	s
	)

Computes the square discrepancies of the first n values contained in points using the first s coordinates, and adds the values at index i.

**NOTE: This method does not replace the values, it adds to them. Can be used with scale to calculate an average square discrepancy over more than one point set.

Parameters

i	index where to add the discrepancies
points	values for which to compute the discrepancies
n	number of points to use
s	number of coordinates to use for each point

calcRegressionSlope()

void calcRegressionSlope ( )

protected

Computes the linear regression slope for the discrepancies as function of the parameter.

Used by regressionToString.

compute() [1/2]

void compute	(	int	i,
		double []	points,
		int	n
	)

Computes the discrepancies of the first n values contained in points and sets the values at index i.

Parameters

i	index where to add the discrepancies
points	values for which to compute the discrepancies
n	number of points to use

compute() [2/2]

void compute	(	int	i,
		double	points[][],
		int	n,
		int	s
	)

Computes the discrepancies of the first n values contained in points using the first s coordinates and sets the values at index i.

Parameters

i	index where to add the discrepancies
points	values for which to compute the discrepancies
n	number of points to use
s	number of coordinates to use for each point

init() [1/2]

void init	(	int	n,
		String	title,
		String	xLabel,
		String	yLabel
	)

Initialize the container with enough space for n values of the parameter and sets the values to 0.

Also sets the labels for the parameter and the discrepancy that will be used for graphs and data file.

Parameters

n	number of values the parameter will take
title	title
xLabel	label name for the parameter
yLabel	label name for the discrepancy

init() [2/2]

void init

(

int

n

)

Calls init(n,"","Parameter", "Discrepancy").

Parameters

n	Number of values the parameter will take.

log2()

void log2

(

int

i

)

Takes the logarithm in base 2 of the discrepancy values at index i.

Parameters

i	index where to take the logarithm

reset()

void reset

(

int

i

)

Resets the values of the discrepancies at index i to 0.

Parameters

i	index to reset

scale() [1/2]

void scale	(	int	i,
		double	scale
	)

Multiplies all the discrepancies at index i by scale;.

Parameters

i	index where to scale
scale	scale factor

scale() [2/2]

void scale

(

double

scale

)

Calls scale(i,scale) for all indices i.

Parameters

scale

scale factor

setParam()

void setParam	(	int	i,
		double	paramValue
	)

Sets the parameter value at index i to parmValue.

Parameters

i	index where to set the parameter value
paramValue	value to set the parameter

square()

void square

(

int

i

)

Squares the discrepancy values at index i.

Parameters

i	index where to take the logarithm

toDatFile()

void toDatFile	(	String	filename,
		String	header
	)

Creates a file named filename.dat and writes in it the given header, a table showing the discrepancies for the different values of the parameter and the linear regression slopes.

Parameters

filename	name of the output file (without any extension)
header	header of the file (can be empty)

toTexFile()

void toTexFile

(

String

filename

)

Creates a file named filename.tex containing LaTeX code that can be compiled by pdfLaTeX to a graph of the discrepancies as function of the parameter.

Parameters

filename

name of the LaTeX file to be created (without the .tex extension)

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

• DiscrepancyContainer.java