astro.fits
Class FitsStatistic

java.lang.Object
  astro.fits.FitsStatistic

public class FitsStatistic
extends Object

Link between a fits (image) and the statistic package. Similar to IRAF imstat.

Nested Class Summary

static class	FitsStatistic.Add Reads a list of input files, decompresses them sequentially if necessary, adds them as doubles, but saves them as floats.
static class	FitsStatistic.AduMinMax Finds the location of the minimum and maximum.
static class	FitsStatistic.AduSplit Tests the fits file on the command line, if its 9th bit (value 2^8=256) is always set in the third quadrant (index number 2).
static class	FitsStatistic.Bias Does bias subtraction.
static class	FitsStatistic.Bitstat Gets the bit-statistic for a 16-bit fits
static class	FitsStatistic.CombinePixel From two dead/hot pixel maps, retain only pixel found in both.
static class	FitsStatistic.Constant Multidimensional that returns one.
static class	FitsStatistic.Coordinate Multidimensional that returns the x or y of the input vector.
static class	FitsStatistic.Count Counts how many pixel have ADU below the given value.
static class	FitsStatistic.DeadPixel Reads an input fits and marks all pixels above the below ADU value as dead pixels.
static class	FitsStatistic.Flat Does flatfielding subtraction.
static class	FitsStatistic.FlatSky Tries to re-establish the zero-point offset from the _f.fits files and put it into the corresponding _mos.fits.
static class	FitsStatistic.HotPixel Reads an input fits and marks all pixels above the given ADU value (default 65535) as hot pixels.
static class	FitsStatistic.Imstat IRAF imstat, without the akward extension modifier.
static class	FitsStatistic.Line Outputs average and std-dev of the quadrants along with header card values of the fits file.
static class	FitsStatistic.Mosaic Tries to re-establish the zero-point offset from the _f.fits files and put it into the corresponding _mos.fits.
static class	FitsStatistic.Nomode Reads a fits file, does an independant sky reduction on all extension found and writes the final fits.
static class	FitsStatistic.Normalize Does median normalization.
static class	FitsStatistic.Nosky Reads a fits file, does an independant sky reduction on all extension found and writes the final fits.
static class	FitsStatistic.RowMedian Prints the median of all rows in the specified fits image.
static class	FitsStatistic.Scale
static class	FitsStatistic.Square Multidimensional that returns the x or y of the input vector squared.
static class	FitsStatistic.WeightMap From a dead and a hot pixel map, we derive a weight map, i.e.
static class	FitsStatistic.XY Multidimensional that returns x times y

Field Summary

static String	BIASAV
private static String	BIASAVREM
static String	BIASRMS
private static String	BIASRMSREM
static String	BIASSEM
private static String	BIASSEMREM
static String	FAVREJ
private static String	FAVREJREM
static String	FCOMBINE
private static String	FCOMBINEREM
static String	FLATAV
private static String	FLATAVREM
static String	FLATRMS
private static String	FLATRMSREM
static String	FLATSEM
private static String	FLATSEMREM
static String	FMAXREJ
private static String	FMAXREJREM
static String	FRMSMAX
private static String	FRMSMAXREM
static String	FXMAX
private static String	FXMAXREM
static String	FXRMS
private static String	FXRMSREM
static String	FYMAX
private static String	FYMAXREM
static String	FYRMS
private static String	FYRMSREM
static String	MMAV
private static String	MMAVREM
static String	MMCOMB
private static String	MMCOMBREM
static String	MMRMS
static String	MMRMSMAX
private static String	MMRMSMAXREM
private static String	MMRMSREM
static String	MMSEM
private static String	MMSEMREM
static String	MMXMAX
private static String	MMXMAXREM
static String	MMYMAX
private static String	MMYMAXREM
static String	RGAINMAX
private static String	RGAINMAXREM
static String	RGAINMIN
private static String	RGAINMINREM
static String	ROWGAIN
private static String	ROWGAINREM
static String	ROWMAX
private static String	ROWMAXREM
static String	ROWMIN
private static String	ROWMINREM
static String	ZAVREJ
private static String	ZAVREJREM
static String	ZCOMBINE
private static String	ZCOMBINEREM
static String	ZMAXREJ
private static String	ZMAXREJREM
static String	ZRMSMAX
private static String	ZRMSMAXREM
static String	ZXMAX
private static String	ZXMAXREM
static String	ZXRMS
private static String	ZXRMSREM
static String	ZYMAX
private static String	ZYMAXREM
static String	ZYRMS
private static String	ZYRMSREM

Constructor Summary

FitsStatistic()

Method Summary

static Vector3D[]	aduMinMax(nom.tam.fits.ImageHDU hdu) Returns location of minimum and maximum ADU value in the first and second index, respectively.
static SortedMap<Double,List<Point>>	aduSort(nom.tam.fits.ImageHDU hdu) Sorts ADUs.
static nom.tam.fits.ImageHDU	avSigClipCombine(List<nom.tam.fits.ImageHDU> flat, FitsStatistic.Scale mode, boolean combav, double siglo, double sighi, int keep, boolean useav, int nmax) Combines images with the avsigclip algorithm, which is suitable for photon-noise limited data (or no read-out noise data).
static Vector2D	backgroundFrameMean(nom.tam.fits.ImageHDU hdu, Rectangle box, int thick) Background is mean of frame, RMS is standard deviation, no clipping.
static Vector2D	backgroundFrameMedian(nom.tam.fits.ImageHDU hdu, Rectangle box, int thick) Background is mean of frame, RMS is standard deviation, no clipping.
static Vector2D	backgroundMean(nom.tam.fits.ImageHDU hdu, Rectangle box) Background is mean of frame, RMS is standard deviation, no clipping.
static Vector2D	backgroundMedian(nom.tam.fits.ImageHDU hdu, Rectangle box) Background is mean of frame, RMS is standard deviation, no clipping.
static Point2D	brightestBlob(double[][] adu, Dimension blob, Vector1D swindle) We scan an input image for the brightest blob.
static Point2D	brightestBlob(nom.tam.fits.ImageHDU src, Rectangle window, Dimension blob) We scan an input image for the brightest blob.
static Point2D	brightestBlob(nom.tam.fits.ImageHDU src, Rectangle window, Dimension blob, Vector1D swindle) We scan an input image for the brightest blob.
static nom.tam.fits.Fits	debias(nom.tam.fits.Fits raw, nom.tam.fits.Fits bias, int numext) Subtracts two fits from each other.
static nom.tam.fits.ImageData	debias(nom.tam.fits.ImageHDU raw, nom.tam.fits.ImageHDU bias) Subtracts two fits from each other.
static List<VectorG>	extractBackground(double[][] src, nom.tam.fits.ImageHDU sig, int nreject, double lofac, double hifac) We get all the sky-background pixel in the image hdu by searching for the mode and retaining all pixel +/- lofac and hifac around it in term of adu-sigmas.
static List<VectorG>	extractBackground(nom.tam.fits.ImageHDU sky, nom.tam.fits.ImageHDU sig, int nreject, double lofac, double hifac) We get all the sky-background pixel in the image hdu by searching for the mode and retaining all pixel +/- lofac and hifac around it in term of adu-sigmas.
static nom.tam.fits.Fits	flatten(nom.tam.fits.Fits raw, nom.tam.fits.Fits flat, int numext) Flatfields an image by dividing through the flatfield.
static nom.tam.fits.ImageData	flatten(nom.tam.fits.ImageHDU raw, nom.tam.fits.ImageHDU flat) Subtracts two fits from each other.
static int[]	get16BitOccurence(nom.tam.fits.ImageHDU hdu) If the image hdu is a 16-bit image, we return the number of occurancies a bit is set in all image data.
static Statistic	getAduStatistic(double[][] hdu) Reads the entire pixel array in the HDU and return a statistic object.
static Statistic	getAduStatistic(nom.tam.fits.Fits fits) Reads the first non-null image HDU in the fits file and returns the statistic to it
static Statistic	getAduStatistic(nom.tam.fits.Fits fits, int skip) Skips the first non-null image HDU in the fits file and returns the statistic to the then next valid HDU.
static Statistic	getAduStatistic(float[][] hdu) Reads the entire pixel array in the HDU and return a statistic object.
static Statistic	getAduStatistic(nom.tam.fits.ImageHDU hdu) Reads the entire pixel array in the HDU and return a statistic object.
static Statistic	getAduStatistic(nom.tam.fits.ImageHDU hdu, Rectangle box) Reads the stated pixel array in the HDU and return a statistic object.
static double[][]	getAsArray(nom.tam.fits.ImageHDU src) Converts an image HDU to a double array, regardless of input type.
static double[][]	getAsArray(nom.tam.fits.ImageHDU src, Rectangle window) Converts an image HDU to a double array, regardless of input type.
static float[][]	getAsFloatArray(nom.tam.fits.ImageHDU src) Converts an image HDU to a float array, regardless of input type.
static float[][]	getAsFloatArray(nom.tam.fits.ImageHDU src, Rectangle window) Converts an image HDU to a double array, regardless of input type.
static Statistic	getBackgroundStatistic(nom.tam.fits.ImageHDU hdu, Rectangle active, int thick) Reads a frame for background statistics.
static Statistic	getRowStatistic(double[][] hdu, int row) Reads the entire pixel array in the HDU and return a statistic object for the specified row.
static nom.tam.fits.Fits	medianNormalize(nom.tam.fits.Fits raw, int numext) Flatfields an image by dividing through the flatfield.
static nom.tam.fits.ImageData	medianNormalize(nom.tam.fits.ImageHDU raw) Subtracts two fits from each other.
private static nom.tam.fits.ImageData	medianNormalize(nom.tam.fits.ImageHDU raw, Vector1D med)
static nom.tam.fits.ImageHDU	minMaxCombine(List<nom.tam.fits.ImageHDU> dark, boolean dumphi, boolean dumplo) Combines images by rejecting just the maximum abd/or minimum of the combined ADUs.
static nom.tam.fits.ImageHDU	removeMode(nom.tam.fits.ImageHDU sky, int n, double lofac, double hifac) Removes the mode of the image, can act as a simple version of background removal.
static nom.tam.fits.ImageHDU	removeSky(nom.tam.fits.ImageHDU sky, Multidimensional[] model, int n, double lofac, double hifac) Models the background and removes it from the image.
private static float[][][]	sanityCheck(List<nom.tam.fits.ImageHDU> bias) Takes a list of images and returns a three-dimensional double array, first index is the image number, then image column (y), followed by row data (x).
static GeneralLinearRegression	shuffleForRegression(List<VectorG> valid, Multidimensional[] model, boolean sigma) Shuffels ADU 4-vectors with x, y, ADU, [sigma] into the format for a general linear regression and fuels them into one.
static nom.tam.fits.ImageHDU	zeroCombine(List<nom.tam.fits.ImageHDU> bias, boolean combav, double rn, double gain) Takes a list of input image hdus and performs a zero-combination on these.
static nom.tam.fits.ImageHDU	zeroCombine(List<nom.tam.fits.ImageHDU> bias, boolean combav, double rn, double gain, double siglo, double sighi, int keep, boolean useav, int nmax) Takes a list of input image hdus and performs a zero-combination on these.

Methods inherited from class java.lang.Object

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

Field Detail

FLATRMS

public static final String FLATRMS

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Constant Field Values

FLATSEM

public static final String FLATSEM

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Constant Field Values

FLATAV

public static final String FLATAV

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Constant Field Values

FCOMBINE

public static final String FCOMBINE

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Constant Field Values

FRMSMAX

public static final String FRMSMAX

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Constant Field Values

FXRMS

public static final String FXRMS

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Constant Field Values

FYRMS

public static final String FYRMS

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Constant Field Values

FMAXREJ

public static final String FMAXREJ

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Constant Field Values

FXMAX

public static final String FXMAX

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Constant Field Values

FYMAX

public static final String FYMAX

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Constant Field Values

FAVREJ

public static final String FAVREJ

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Constant Field Values

ROWGAIN

public static final String ROWGAIN

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Constant Field Values

RGAINMAX

public static final String RGAINMAX

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Constant Field Values

ROWMAX

public static final String ROWMAX

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Constant Field Values

RGAINMIN

public static final String RGAINMIN

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Constant Field Values

ROWMIN

public static final String ROWMIN

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Constant Field Values

MMRMS

public static final String MMRMS

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Constant Field Values

MMSEM

public static final String MMSEM

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Constant Field Values

MMAV

public static final String MMAV

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Constant Field Values

MMCOMB

public static final String MMCOMB

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Constant Field Values

MMRMSMAX

public static final String MMRMSMAX

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Constant Field Values

MMXMAX

public static final String MMXMAX

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Constant Field Values

MMYMAX

public static final String MMYMAX

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Constant Field Values

BIASRMS

public static final String BIASRMS

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Constant Field Values

BIASSEM

public static final String BIASSEM

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Constant Field Values

BIASAV

public static final String BIASAV

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Constant Field Values

ZRMSMAX

public static final String ZRMSMAX

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Constant Field Values

ZXRMS

public static final String ZXRMS

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Constant Field Values

ZYRMS

public static final String ZYRMS

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Constant Field Values

ZCOMBINE

public static final String ZCOMBINE

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Constant Field Values

ZMAXREJ

public static final String ZMAXREJ

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ZXMAX

public static final String ZXMAX

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Constant Field Values

ZYMAX

public static final String ZYMAX

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Constant Field Values

ZAVREJ

public static final String ZAVREJ

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Constant Field Values

FLATRMSREM

private static final String FLATRMSREM

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Constant Field Values

FLATSEMREM

private static final String FLATSEMREM

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Constant Field Values

FLATAVREM

private static final String FLATAVREM

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Constant Field Values

FRMSMAXREM

private static final String FRMSMAXREM

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Constant Field Values

FXRMSREM

private static final String FXRMSREM

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Constant Field Values

FYRMSREM

private static final String FYRMSREM

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Constant Field Values

FCOMBINEREM

private static final String FCOMBINEREM

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Constant Field Values

FMAXREJREM

private static final String FMAXREJREM

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Constant Field Values

FXMAXREM

private static final String FXMAXREM

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Constant Field Values

FYMAXREM

private static final String FYMAXREM

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Constant Field Values

FAVREJREM

private static final String FAVREJREM

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ROWGAINREM

private static final String ROWGAINREM

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RGAINMAXREM

private static final String RGAINMAXREM

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Constant Field Values

ROWMAXREM

private static final String ROWMAXREM

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Constant Field Values

RGAINMINREM

private static final String RGAINMINREM

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Constant Field Values

ROWMINREM

private static final String ROWMINREM

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Constant Field Values

MMRMSREM

private static final String MMRMSREM

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Constant Field Values

MMSEMREM

private static final String MMSEMREM

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Constant Field Values

MMAVREM

private static final String MMAVREM

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Constant Field Values

MMCOMBREM

private static final String MMCOMBREM

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Constant Field Values

MMRMSMAXREM

private static final String MMRMSMAXREM

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Constant Field Values

MMXMAXREM

private static final String MMXMAXREM

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Constant Field Values

MMYMAXREM

private static final String MMYMAXREM

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Constant Field Values

BIASRMSREM

private static final String BIASRMSREM

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Constant Field Values

BIASSEMREM

private static final String BIASSEMREM

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Constant Field Values

BIASAVREM

private static final String BIASAVREM

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Constant Field Values

ZRMSMAXREM

private static final String ZRMSMAXREM

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Constant Field Values

ZXRMSREM

private static final String ZXRMSREM

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Constant Field Values

ZYRMSREM

private static final String ZYRMSREM

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Constant Field Values

ZCOMBINEREM

private static final String ZCOMBINEREM

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Constant Field Values

ZMAXREJREM

private static final String ZMAXREJREM

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Constant Field Values

ZXMAXREM

private static final String ZXMAXREM

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Constant Field Values

ZYMAXREM

private static final String ZYMAXREM

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Constant Field Values

ZAVREJREM

private static final String ZAVREJREM

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Constant Field Values

Constructor Detail

FitsStatistic

public FitsStatistic()

Method Detail

medianNormalize

public static nom.tam.fits.Fits medianNormalize(nom.tam.fits.Fits raw,
                                                int numext)
                                         throws nom.tam.fits.FitsException,
                                                IOException

Flatfields an image by dividing through the flatfield. If multiple extensions are found, each extension is used. Flatfielding fails, if image sizes are different or if different extension numbers are found.

Throws:

nom.tam.fits.FitsException

IOException

medianNormalize

public static nom.tam.fits.ImageData medianNormalize(nom.tam.fits.ImageHDU raw)
                                              throws nom.tam.fits.FitsException

Subtracts two fits from each other. If multiple extensions are found, each extension is used. Subtraction fails, if image sizes are different or if different extension numbers are found.

Throws:

nom.tam.fits.FitsException

medianNormalize

private static nom.tam.fits.ImageData medianNormalize(nom.tam.fits.ImageHDU raw,
                                                      Vector1D med)
                                               throws nom.tam.fits.FitsException

Throws:

nom.tam.fits.FitsException

avSigClipCombine

public static nom.tam.fits.ImageHDU avSigClipCombine(List<nom.tam.fits.ImageHDU> flat,
                                                     FitsStatistic.Scale mode,
                                                     boolean combav,
                                                     double siglo,
                                                     double sighi,
                                                     int keep,
                                                     boolean useav,
                                                     int nmax)
                                              throws nom.tam.fits.FitsException

Combines images with the avsigclip algorithm, which is suitable for photon-noise limited data (or no read-out noise data). No sigma-adjustment is done with the scaling, so images should have comparable intensity levels. On calculating the statistic, no sampling is done, thus we might loose some performance.

Throws:

nom.tam.fits.FitsException

minMaxCombine

public static nom.tam.fits.ImageHDU minMaxCombine(List<nom.tam.fits.ImageHDU> dark,
                                                  boolean dumphi,
                                                  boolean dumplo)
                                           throws nom.tam.fits.FitsException

Combines images by rejecting just the maximum abd/or minimum of the combined ADUs.

Throws:

nom.tam.fits.FitsException

zeroCombine

public static nom.tam.fits.ImageHDU zeroCombine(List<nom.tam.fits.ImageHDU> bias,
                                                boolean combav,
                                                double rn,
                                                double gain)
                                         throws nom.tam.fits.FitsException

Takes a list of input image hdus and performs a zero-combination on these.

Throws:

nom.tam.fits.FitsException

zeroCombine

public static nom.tam.fits.ImageHDU zeroCombine(List<nom.tam.fits.ImageHDU> bias,
                                                boolean combav,
                                                double rn,
                                                double gain,
                                                double siglo,
                                                double sighi,
                                                int keep,
                                                boolean useav,
                                                int nmax)
                                         throws nom.tam.fits.FitsException

Takes a list of input image hdus and performs a zero-combination on these. The images should be overscan-corrected and clipped to the useful area. No header entries are retained. On return, an average RMS value is added to the returned header with the key.

Throws:

nom.tam.fits.FitsException

get16BitOccurence

public static int[] get16BitOccurence(nom.tam.fits.ImageHDU hdu)
                               throws nom.tam.fits.FitsException

If the image hdu is a 16-bit image, we return the number of occurancies a bit is set in all image data.

Throws:

nom.tam.fits.FitsException

sanityCheck

private static float[][][] sanityCheck(List<nom.tam.fits.ImageHDU> bias)
                                throws nom.tam.fits.FitsException

Takes a list of images and returns a three-dimensional double array, first index is the image number, then image column (y), followed by row data (x).

Returns:

null, if only a single image is found

Throws:

nom.tam.fits.FitsException - If list is null, empty or not all images have identical size.

getAduStatistic

public static Statistic getAduStatistic(nom.tam.fits.ImageHDU hdu,
                                        Rectangle box)
                                 throws nom.tam.fits.FitsException

Reads the stated pixel array in the HDU and return a statistic object. This can further be used for pixel rejection and/or histogram calculations.

Throws:

nom.tam.fits.FitsException

getAduStatistic

public static Statistic getAduStatistic(nom.tam.fits.ImageHDU hdu)
                                 throws nom.tam.fits.FitsException

Reads the entire pixel array in the HDU and return a statistic object. This can further be used for pixel rejection and/or histogram calculations.

Throws:

nom.tam.fits.FitsException

getBackgroundStatistic

public static Statistic getBackgroundStatistic(nom.tam.fits.ImageHDU hdu,
                                               Rectangle active,
                                               int thick)
                                        throws nom.tam.fits.FitsException

Reads a frame for background statistics.

Throws:

nom.tam.fits.FitsException

getAduStatistic

public static Statistic getAduStatistic(double[][] hdu)
                                 throws nom.tam.fits.FitsException

Reads the entire pixel array in the HDU and return a statistic object. This can further be used for pixel rejection and/or histogram calculations.

Throws:

nom.tam.fits.FitsException

getAduStatistic

public static Statistic getAduStatistic(float[][] hdu)
                                 throws nom.tam.fits.FitsException

Reads the entire pixel array in the HDU and return a statistic object. This can further be used for pixel rejection and/or histogram calculations.

Throws:

nom.tam.fits.FitsException

getRowStatistic

public static Statistic getRowStatistic(double[][] hdu,
                                        int row)
                                 throws nom.tam.fits.FitsException

Reads the entire pixel array in the HDU and return a statistic object for the specified row.

Throws:

nom.tam.fits.FitsException

getAduStatistic

public static Statistic getAduStatistic(nom.tam.fits.Fits fits)
                                 throws nom.tam.fits.FitsException,
                                        IOException

Reads the first non-null image HDU in the fits file and returns the statistic to it

Throws:

nom.tam.fits.FitsException

IOException

getAduStatistic

public static Statistic getAduStatistic(nom.tam.fits.Fits fits,
                                        int skip)
                                 throws nom.tam.fits.FitsException,
                                        IOException

Skips the first non-null image HDU in the fits file and returns the statistic to the then next valid HDU.

Throws:

nom.tam.fits.FitsException

IOException

getAsArray

public static final double[][] getAsArray(nom.tam.fits.ImageHDU src)
                                   throws nom.tam.fits.FitsException

Converts an image HDU to a double array, regardless of input type. Does value BSCALE and BZERO.

Returns:

An array with y as the inner index, x as outer (see fits def)

Throws:

nom.tam.fits.FitsException

getAsArray

public static final double[][] getAsArray(nom.tam.fits.ImageHDU src,
                                          Rectangle window)
                                   throws nom.tam.fits.FitsException

Converts an image HDU to a double array, regardless of input type. Does value BSCALE and BZERO.

Throws:

nom.tam.fits.FitsException

brightestBlob

public static Point2D brightestBlob(nom.tam.fits.ImageHDU src,
                                    Rectangle window,
                                    Dimension blob)
                             throws nom.tam.fits.FitsException

We scan an input image for the brightest blob. This is the position of the brightest (=highest ADU sum) sub-rectangle of dimension blob, using the center position.

Throws:

nom.tam.fits.FitsException

brightestBlob

public static Point2D brightestBlob(nom.tam.fits.ImageHDU src,
                                    Rectangle window,
                                    Dimension blob,
                                    Vector1D swindle)
                             throws nom.tam.fits.FitsException

We scan an input image for the brightest blob. This is the position of the brightest (=highest ADU sum) sub-rectangle of dimension blob, using the center position. If the Vector1D is non-null, the value of the blob is set within.

Throws:

nom.tam.fits.FitsException

backgroundMean

public static Vector2D backgroundMean(nom.tam.fits.ImageHDU hdu,
                                      Rectangle box)
                               throws nom.tam.fits.FitsException

Background is mean of frame, RMS is standard deviation, no clipping.

Throws:

nom.tam.fits.FitsException

backgroundMedian

public static Vector2D backgroundMedian(nom.tam.fits.ImageHDU hdu,
                                        Rectangle box)
                                 throws nom.tam.fits.FitsException

Background is mean of frame, RMS is standard deviation, no clipping.

Throws:

nom.tam.fits.FitsException

backgroundFrameMean

public static Vector2D backgroundFrameMean(nom.tam.fits.ImageHDU hdu,
                                           Rectangle box,
                                           int thick)
                                    throws nom.tam.fits.FitsException

Background is mean of frame, RMS is standard deviation, no clipping.

Throws:

nom.tam.fits.FitsException

backgroundFrameMedian

public static Vector2D backgroundFrameMedian(nom.tam.fits.ImageHDU hdu,
                                             Rectangle box,
                                             int thick)
                                      throws nom.tam.fits.FitsException

Background is mean of frame, RMS is standard deviation, no clipping.

Throws:

nom.tam.fits.FitsException

brightestBlob

public static Point2D brightestBlob(double[][] adu,
                                    Dimension blob,
                                    Vector1D swindle)

We scan an input image for the brightest blob. This is the position of the brightest (=highest ADU sum) sub-rectangle of dimension blob, using the center position.

getAsFloatArray

public static final float[][] getAsFloatArray(nom.tam.fits.ImageHDU src)
                                       throws nom.tam.fits.FitsException

Converts an image HDU to a float array, regardless of input type. Does value BSCALE and BZERO.

Throws:

nom.tam.fits.FitsException

getAsFloatArray

public static final float[][] getAsFloatArray(nom.tam.fits.ImageHDU src,
                                              Rectangle window)
                                       throws nom.tam.fits.FitsException

Converts an image HDU to a double array, regardless of input type. Does value BSCALE and BZERO.

Throws:

nom.tam.fits.FitsException

aduSort

public static SortedMap<Double,List<Point>> aduSort(nom.tam.fits.ImageHDU hdu)
                                             throws nom.tam.fits.FitsException

Sorts ADUs. Returns a mapping of adu values to pixel positions.

Throws:

nom.tam.fits.FitsException

aduMinMax

public static Vector3D[] aduMinMax(nom.tam.fits.ImageHDU hdu)
                            throws nom.tam.fits.FitsException

Returns location of minimum and maximum ADU value in the first and second index, respectively. Return value has in z-component the ADU value

Throws:

nom.tam.fits.FitsException

extractBackground

public static List<VectorG> extractBackground(nom.tam.fits.ImageHDU sky,
                                              nom.tam.fits.ImageHDU sig,
                                              int nreject,
                                              double lofac,
                                              double hifac)
                                       throws nom.tam.fits.FitsException

We get all the sky-background pixel in the image hdu by searching for the mode and retaining all pixel +/- lofac and hifac around it in term of adu-sigmas.

Throws:

nom.tam.fits.FitsException

extractBackground

public static List<VectorG> extractBackground(double[][] src,
                                              nom.tam.fits.ImageHDU sig,
                                              int nreject,
                                              double lofac,
                                              double hifac)
                                       throws nom.tam.fits.FitsException

We get all the sky-background pixel in the image hdu by searching for the mode and retaining all pixel +/- lofac and hifac around it in term of adu-sigmas.

Throws:

nom.tam.fits.FitsException

removeMode

public static nom.tam.fits.ImageHDU removeMode(nom.tam.fits.ImageHDU sky,
                                               int n,
                                               double lofac,
                                               double hifac)
                                        throws nom.tam.fits.FitsException

Removes the mode of the image, can act as a simple version of background removal.

Throws:

nom.tam.fits.FitsException

shuffleForRegression

public static GeneralLinearRegression shuffleForRegression(List<VectorG> valid,
                                                           Multidimensional[] model,
                                                           boolean sigma)

Shuffels ADU 4-vectors with x, y, ADU, [sigma] into the format for a general linear regression and fuels them into one.

removeSky

public static nom.tam.fits.ImageHDU removeSky(nom.tam.fits.ImageHDU sky,
                                              Multidimensional[] model,
                                              int n,
                                              double lofac,
                                              double hifac)
                                       throws nom.tam.fits.FitsException

Models the background and removes it from the image.

Throws:

nom.tam.fits.FitsException

flatten

public static nom.tam.fits.Fits flatten(nom.tam.fits.Fits raw,
                                        nom.tam.fits.Fits flat,
                                        int numext)
                                 throws nom.tam.fits.FitsException,
                                        IOException

Flatfields an image by dividing through the flatfield. If multiple extensions are found, each extension is used. Flatfielding fails, if image sizes are different or if different extension numbers are found.

Throws:

nom.tam.fits.FitsException

IOException

flatten

public static nom.tam.fits.ImageData flatten(nom.tam.fits.ImageHDU raw,
                                             nom.tam.fits.ImageHDU flat)
                                      throws nom.tam.fits.FitsException

Subtracts two fits from each other. If multiple extensions are found, each extension is used. Subtraction fails, if image sizes are different or if different extension numbers are found.

Throws:

nom.tam.fits.FitsException

debias

public static nom.tam.fits.Fits debias(nom.tam.fits.Fits raw,
                                       nom.tam.fits.Fits bias,
                                       int numext)
                                throws nom.tam.fits.FitsException,
                                       IOException

Subtracts two fits from each other. If multiple extensions are found, each extension is used. Subtraction fails, if image sizes are different or if different extension numbers are found.

Throws:

nom.tam.fits.FitsException

IOException

debias

public static nom.tam.fits.ImageData debias(nom.tam.fits.ImageHDU raw,
                                            nom.tam.fits.ImageHDU bias)
                                     throws nom.tam.fits.FitsException

Subtracts two fits from each other. If multiple extensions are found, each extension is used. Subtraction fails, if image sizes are different or if different extension numbers are found.

Throws:

nom.tam.fits.FitsException