Package de.gsi.dataset.testdata.spi

Class GaussFunction

java.lang.Object

de.gsi.dataset.spi.AbstractStylable<D>

de.gsi.dataset.spi.AbstractDataSet<D>

de.gsi.dataset.spi.AbstractErrorDataSet<D>

de.gsi.dataset.testdata.spi.AbstractTestFunction<GaussFunction>

de.gsi.dataset.testdata.spi.GaussFunction

All Implemented Interfaces:

DataSet, DataSet2D, DataSetError, DataSetMetaData, EventSource, TestDataSet<GaussFunction>, java.io.Serializable

public class GaussFunction
extends AbstractTestFunction<GaussFunction>

abstract error data set for graphical testing purposes this implementation generates a Gaussian function

Author:

rstein

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface de.gsi.dataset.DataSetError

DataSetError.ErrorType

Field Summary

Fields inherited from class de.gsi.dataset.spi.AbstractDataSet

axisListener, dimension

Fields inherited from interface de.gsi.dataset.DataSet

DIM_X, DIM_Y, DIM_Z

Fields inherited from interface de.gsi.dataset.DataSetMetaData

TAG_GAIN_RANGE, TAG_OVERSHOOT, TAG_UNDERSHOOT

Constructor Summary

Constructors

Constructor	Description
GaussFunction(java.lang.String name, int count)
GaussFunction(java.lang.String name, int count, double mean, double sigma)

Method Summary

Modifier and Type	Method	Description
static double	gauss(double x)
static double	gauss(double x, double mu, double sigma)
double[]	generateY(int count)	generate test data set

Methods inherited from class de.gsi.dataset.testdata.spi.AbstractTestFunction

generateX, get, getDataCount, getErrorNegative, getErrorPositive, getErrorType, getStyle, set, update

Methods inherited from class de.gsi.dataset.spi.AbstractErrorDataSet

fireInvalidated, getThis, lock, recomputeLimits, setErrorType

Methods inherited from class de.gsi.dataset.spi.AbstractDataSet

addDataLabel, addDataStyle, autoNotification, binarySearch, binarySearch, clearMetaInfo, copyAxisDescription, copyDataLabelsAndStyles, copyMetaData, equalDataLabels, equalEditConstraints, equalErrorValues, equalMetaData, equals, equals, equalValues, getAxisDescriptions, getDataLabel, getDataLabelMap, getDataStyleMap, getDimension, getEditConstraints, getErrorList, getIndex, getInfoList, getMetaInfo, getName, getValue, getValues, getWarningList, hashCode, removeDataLabel, removeStyle, setEditConstraints, setName, toString, updateEventListener

Methods inherited from class de.gsi.dataset.spi.AbstractStylable

getStyle, setStyle

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface de.gsi.dataset.DataSet

getAxisDescription, getAxisDescriptions, getDataLabel, getIndex, getName, getStyle, getValue, getValues, lock, recomputeLimits, set, setStyle

Methods inherited from interface de.gsi.dataset.DataSet2D

getDimension, getValue, getX, getXIndex, getXValues, getY, getYIndex, getYValues

Methods inherited from interface de.gsi.dataset.DataSetError

getErrorNegative, getErrorPositive, getErrorsNegative, getErrorsPositive

Methods inherited from interface de.gsi.dataset.event.EventSource

addListener, autoNotification, invokeListener, invokeListener, invokeListener, isAutoNotification, removeListener, updateEventListener

Methods inherited from interface de.gsi.dataset.testdata.TestDataSet

fireInvalidated

Constructor Detail

GaussFunction

public GaussFunction(java.lang.String name,
                     int count)

Parameters:

name - data set name

count - number of samples

GaussFunction

public GaussFunction(java.lang.String name,
                     int count,
                     double mean,
                     double sigma)

Parameters:

name - data set name

count - number of samples

mean - mean position [0,count[

sigma - standard deviation [0, inf[

Method Detail

generateY

public double[] generateY(int count)

Description copied from interface: TestDataSet

generate test data set

Parameters:

count - number of bins

Returns:

the generated array

gauss

public static double gauss(double x)

Parameters:

x - coordinate X

Returns:

value of Gaussian function at x (mean = 0, sigma = 1)

gauss

public static double gauss(double x,
                           double mu,
                           double sigma)

Parameters:

x - coordiante x

mu - mean value of Gaussian function

sigma - standard deviation of Gaussian function

Returns:

value of Gaussian function at x