astro.fits

Class AbstractSkyMaker.SkyRandomModel

java.lang.Object

astro.fits.AbstractFitsImageModel

astro.fits.AbstractSkyMaker.SkyRandomModel

All Implemented Interfaces:

MultidimensionalDataModel

Enclosing class:

AbstractSkyMaker

protected static class AbstractSkyMaker.SkyRandomModel
extends AbstractFitsImageModel

Returns a randomized image model with specified read-noise and gain. If the model is set to preserve flux, gain is only applied to the total errors, thus making it possible to achieve any artificial S/N and at the same time keeping the ADUs constant.

Author:

wooz

Field Summary

Fields

Modifier and Type	Field and Description
private boolean	debug
private boolean	fluxpreserve
private PoissonRandom	noise
(package private) long	t0

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	SkyRandomModel(double[] fits, Rectangle box)

Method Summary

Modifier and Type	Method and Description
VectorG	evaluateModel(VectorG parameters, VectorG t)
float[]	getFloatImageModel(VectorG parameters) Returns the image model
int	getParameterCount() In total, there are three parameter, the bias background, the read noise and the gain.
boolean	isFluxPreserve() If true, ADU returned are not scaled to gain, only errors are.
private double	randomize(double bias, double ron, double gain, int i0)
void	setDebug(boolean b)
void	setFluxPreserve(boolean fluxpreserve)

Methods inherited from class astro.fits.AbstractFitsImageModel

aboveBackground, dimension, dimensionOfIndependent, equalData, getArea, getFloatImageData, getFloatImageDataErrors, getFloatImageResiduals, getImageData, getImageDataErrors, getImageModel, getImageResiduals, getMeasureCount, getMeasurementErrors, getMeasures, getMetric, getModel, getResiduals, getRms, getTimes, getTotalErrors, getUpLeft, getYX, photonAndReadoutNoise, setAduErrors, subtract

Methods inherited from class java.lang.Object

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

Field Detail

fluxpreserve

private boolean fluxpreserve

noise

private final PoissonRandom noise

debug

private boolean debug

t0

long t0

Constructor Detail

SkyRandomModel

protected SkyRandomModel(double[] fits,
                         Rectangle box)

Method Detail

setDebug

public void setDebug(boolean b)

getParameterCount

public int getParameterCount()

In total, there are three parameter, the bias background, the read noise and the gain.

getFloatImageModel

public float[] getFloatImageModel(VectorG parameters)

Returns the image model

Overrides:

getFloatImageModel in class AbstractFitsImageModel

evaluateModel

public VectorG evaluateModel(VectorG parameters,
                             VectorG t)

randomize

private double randomize(double bias,
                         double ron,
                         double gain,
                         int i0)

Parameters:

bias -

ron -

gain -

iy -

ix -

Returns:

isFluxPreserve

public boolean isFluxPreserve()

If true, ADU returned are not scaled to gain, only errors are.

Returns:

the fluxpreserve

setFluxPreserve

public void setFluxPreserve(boolean fluxpreserve)

Parameters:

fluxpreserve - the fluxpreserve to set