template<typename _realT, class _derotFunctObj, typename _evCalcT = double>
struct mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >

An implementation of the Karhunen-Loeve Image Processing (KLIP) algorithm.

KLIP[25] is a principle components analysis (PCA) based technique for PSF estimation.

Template Parameters

_realT	is the floating point type in which to do calculations
_derotFunctObj	the ADIobservation derotator class.
_evCalcT	the real type in which to do eigen-decomposition. Should generally be double for stable results.

Definition at line 83 of file KLIPreduction.hpp.

#include <improc/KLIPreduction.hpp>

Inheritance diagram for mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >:

Public Member Functions
	KLIPreduction ()
	Default c'tor.

	KLIPreduction (const std::string &dir, const std::string &prefix, const std::string &ext)
	Construct and load the target file list.

	KLIPreduction (const std::string &fileListFile)
	Construct using a file containing the target file list.

	KLIPreduction (const std::string &dir, const std::string &prefix, const std::string &ext, const std::string &RDIdir, const std::string &RDIprefix, const std::string &RDIext="")

	KLIPreduction (const std::string &fileListFile, const std::string &RDIfileListFile)

void	meanSubtract (eigenCube< realT > &rims, eigenCube< realT > &tims, eigenImageT &cmask, std::vector< realT > &sds)
	Subtract the basis mean from each of the images.

int	regions (const std::vector< realT > &minr, const std::vector< realT > &maxr, const std::vector< realT > &minq, const std::vector< realT > &maxq)
	Run KLIP in a set of geometric search regions.

int	regions (realT minr, realT maxr, realT minq, realT maxq)
	Run KLIP in a geometric search region.

void	worker (eigenCube< realT > &rims, eigenCube< realT > &tims, eigenImageT &cmask, std::vector< size_t > &idx, realT dang, realT dangMax)

Public Member Functions inherited from mx::improc::ADIobservation< _realT, _derotFunctObj >
	ADIobservation (const std::string &dir, const std::string &prefix, const std::string &ext)

	ADIobservation (const std::string &fileListFile)

	ADIobservation (const std::string &dir, const std::string &prefix, const std::string &ext, const std::string &RDIdir, const std::string &RDIprefix, const std::string &RDIext="")

	ADIobservation (const std::string &fileListFile, const std::string &RDIfileListFile)

int	readFiles ()
	Read in the target files.

virtual int	postReadFiles ()
	Actions to take after the files are first read in by HCIobservation.

virtual int	postCoadd ()
	Post target coadd actions.

int	readRDIFiles ()
	Read in the RDI files.

virtual int	postRDIReadFiles ()
	Post reference read actions, including fake injection.

virtual int	postRDICoadd ()
	Post reference coadd actions.

int	readPSFSub (const std::string &dir, const std::string &prefix, const std::string &ext, size_t nReductions)
	Read in already PSF-subtracted files.

virtual void	makeMaskCube ()
	Populate the mask cube which is used for post-processing.

void	derotate ()
	De-rotate the PSF subtracted images.

int	injectFake (eigenCube< realT > &ims, std::vector< std::string > &fileList, derotFunctObj &derotF, realT RDIfluxScale, realT RDISepScale)
	Inkect the fake plants.

int	injectFake (eigenImageT &fakePSF, eigenCube< realT > &ims, int image_i, realT derotAngle, realT PA, realT sep, realT contrast, realT scale, realT RDIfluxScale, realT RDISepScale)
	Inject the fake planet into a single image.

Public Member Functions inherited from mx::improc::HCIobservation< _realT >
int	readPSFSub (const std::string &dir, const std::string &prefix, const std::string &ext, size_t nReductions)
	Read in already PSF-subtracted files.

	HCIobservation ()
	Default c'tor.

	HCIobservation (const std::string &dir, const std::string &prefix, const std::string &ext)
	Construct and load the target file list.

	HCIobservation (const std::string &fileListFile)
	Construct using a file containing the target file list.

	HCIobservation (const std::string &dir, const std::string &prefix, const std::string &ext, const std::string &RDIdir, const std::string &RDIprefix, const std::string &RDIext="")
	Construct and load the target file list and the RDI file list.

	HCIobservation (const std::string &fileListFile, const std::string &RDIfileListFile)
	Construct using a file containing the target file list and a file containing the RDI target file list.

void	load_fileList (const std::string &dir, const std::string &prefix, const std::string &ext)
	Load the file list.

void	load_fileList (const std::string &fileListFile)
	Load the file list from a file.

void	load_RDIfileList (const std::string &dir, const std::string &prefix, const std::string &ext)
	Load the RDI basis file list.

void	load_RDIfileList (const std::string &fileListFile)
	Load the RDI basis file list from a file.

int	threshold (std::vector< std::string > &fileList, const std::string &qualityFile, realT qualityThreshold)
	Read the image qualities from a qualityFile and apply the threshold to a fileList.

int	readFiles ()
	Read the list of files, cut to size, and preprocess.

int	readRDIFiles ()
	Read the list of reference files, cut to size, and preprocess.

void	coaddImages (int coaddCombineMethod, int coaddMaxImno, int coaddMaxTime, std::vector< std::string > &coaddKeywords, std::vector< double > &imageMJD, std::vector< fits::fitsHeader > &heads, eigenCube< realT > &ims)
	Coadd the images.

void	readMask ()
	Read the mask file, resizing to imSize if needed.

void	preProcess (eigenCube< realT > &ims)
	Do the pre-processing.

void	preProcess_meanSub (eigenCube< realT > &ims)
	Do mean subtraction as part of pre-processing.

void	preProcess_pixelTSNorm (eigenCube< realT > &ims)
	Do pixel time-series normalization as part of pre-processing.

int	readWeights ()
	Read the image weights from m_weightFile.

void	combineFinim ()
	Combine the images into a single final image.

void	outputPreProcessed ()
	Output the pre-processed target images.

void	outputRDIPreProcessed ()
	Output the pre-processed reference images.

void	stdFitsHeader (fits::fitsHeader &head)
	Fill in the HCIobservation standard FITS header.

void	writeFinim (fits::fitsHeader *addHead=0)
	Write the final combined image to disk.

void	outputPSFSub (fits::fitsHeader *addHead=0)
	Write the PSF subtracted images to disk.

Public Attributes
HCI::meanSubMethod	m_meanSubMethod { HCI::meanSubMethod::imageMean }
	Specify how the data are centered for PCA within each search region.

HCI::pixelTSNormMethod	m_pixelTSNormMethod {HCI::pixelTSNormMethod::none}
	Specify if each pixel time-series is normalized.

realT	m_pixelTSSigma {3}
	Sigma-clipping parameter for pixel time-series normalization.

std::vector< int >	m_Nmodes
	Specifies the number of modes to include in the PSF.

realT	m_minDPx { 0 }

realT	m_maxDPx { 0 }

int	m_excludeMethod { HCI::excludeNone }

int	m_excludeMethodMax { HCI::excludeNone }

int	m_includeRefNum { 0 }
	Number of reference images to include in the covariance matrix.

int	m_includeMethod { HCI::includeAll }
	Controls how number of included images is calculated.

Public Attributes inherited from mx::improc::ADIobservation< _realT, _derotFunctObj >
int	m_fakeMethod { HCI::single }
	Method for reading fake files, either HCI::single or HCI::list.

std::string	m_fakeFileName
	FITS file containing the fake planet PSF to inject or a list of fake images.

std::string	m_fakeScaleFileName
	One-column text file containing a scale factor for each point in time.

std::vector< realT >	m_fakeSep
	Separation(s) of the fake planet(s)

std::vector< realT >	m_fakePA
	Position angles(s) of the fake planet(s)

std::vector< realT >	m_fakeContrast
	Contrast(s) of the fake planet(s)

realT	m_RDIFluxScale { 1 }

realT	m_RDISepScale { 1 }

Public Attributes inherited from mx::improc::HCIobservation< _realT >
eigenCube< realT >	m_tgtIms
	The target image cube.

int	m_Nims { 0 }
	Number of images in m_tgtIms.

int	m_Nrows { 0 }
	Number of rows of the images in m_tgtIms.

int	m_Ncols { 0 }
	Number of columns of the images in m_tgtIms.

int	m_Npix { 0 }
	Pixels per image, that is Nrows*Ncols.

std::vector< double >	m_imageMJD
	Vector of target image times, in MJD.

std::vector< fits::fitsHeader >	m_heads
	Vector of FITS headers, one per file, populated with the values for the keywords.

bool	m_filesRead { false }
	Whether or not the m_fileList has been read.

bool	m_filesDeleted { false }
	Whether or not the specified files have been deleted from m_fileList.

std::vector< realT >	m_comboWeights
	Vector to hold the image weights read from the m_weightFile.

eigenCube< realT >	m_refIms
	The optional reference image cube.

std::vector< double >	m_RDIimageMJD
	Vector of reference image times, in MJD.

std::vector< fits::fitsHeader >	m_RDIheads
	Vector of FITS headers, one per reference file, populated with the values for the keywords.

bool	m_RDIfilesRead { false }
	Whether or not the reference files have been read.

bool	m_RDIfilesDeleted { false }
	Whether or not the specified files have been deleted from m_RDIfileList.

std::vector< eigenCube< realT > >	m_psfsub
	The PSF subtracted images.

eigenCube< realT >	m_finim
	The final combined images, one for each cube in psfsub.

std::vector< std::string >	m_fileList
	The list of files to read in.

int	m_deleteFront { 0 }
	Specify how many files from m_fileList to delete from the front of the list.

int	m_deleteBack { 0 }
	Specify how many files from m_fileList to delete from the back of the list.

std::string	m_qualityFile
	File containing 2 space-delimited columns of fileVame qualityValue pairs.

realT	m_qualityThreshold { 0 }
	Threshold to apply to qualityValues read from qualityFile.

bool	m_thresholdOnly { false }
	Just prints the names and qualities of the files which pass threshold, and stop.

std::string	m_MJDKeyword { "DATE-OBS" }
	Name of the keyword to use for the image date.

bool	m_MJDisISO8601 { true }
	Whether or not the date is in ISO 8601 format.

realT	m_MJDUnits { 1.0 }
	If the date is not ISO 8601, this specifies the conversion to Julian Days (i.e. seconds to days)

std::vector< std::string >	m_keywords
	Vector of FITS header keywords to read from the files in m_fileList.

int	m_imSize { 0 }
	Set the image size. Images are cut down to this size after reading.

std::vector< std::string >	m_RDIfileList
	The list of files to read in for the RDI basis.

int	m_RDIdeleteFront { 0 }
	Specify how many files from m_RDIfileList to delete from the front of the list.

int	m_RDIdeleteBack { 0 }
	Specify how many files from m_RDIfileList to delete from the back of the list.

std::string	m_RDIqualityFile
	File containing 2 space-delimited columns of fileMame qualityValue pairs for the reference images.

realT	m_RDIqualityThreshold { 0 }
	Threshold to apply to qualityValues read from qualityFile.

std::vector< std::string >	m_RDIkeywords
	Vector of FITS header keywords to read from the files in m_fileList.

int	m_coaddCombineMethod { HCI::noCombine }
	Determine how to coadd the raw images.

int	m_coaddMaxImno { 0 }
	Maximum number of images to coadd.

realT	m_coaddMaxTime { 0 }
	Maximum elapsed time over which to coadd the images.

std::vector< std::string >	m_coaddKeywords
	The values of these keywords will be averaged and replaced.

std::string	m_maskFile
	Specify a mask file to apply.

eigenImageT	m_mask
	The mask.

eigenCube< realT >	m_maskCube

bool	m_skipPreProcess { false }
	Don't do any of the pre-processing steps (including coadding).

bool	m_preProcess_beforeCoadd { false }
	controls whether pre-processing takes place before or after coadding

bool	m_preProcess_mask { true }
	If true, the mask is applied during each pre-processing step.

bool	m_preProcess_subradprof { false }
	If true, a radial profile is subtracted from each image.

realT	m_preProcess_azUSM_azW { 0 }
	Azimuthal boxcar width for azimuthal unsharp mask [pixels].

realT	m_preProcess_azUSM_maxAz { 45 }
	Mazimum azimuthal boxcar width for azimuthal unsharp mask [degrees].

realT	m_preProcess_azUSM_radW { 0 }
	Radial boxcar width for azimuthal unsharp mask [pixels].

int	m_preProcess_medianUSM_fwhm { 0 }
	Kernel FWHM for symmetric box median unsharp mask (USM)

realT	m_preProcess_gaussUSM_fwhm { 0 }
	Kernel FWHM for symmetric Gaussian unsharp mask (USM)

HCI::meanSubMethod	m_preProcess_meanSubMethod { HCI::meanSubMethod::none }
	The mean subtraction method during pre-processing.

HCI::pixelTSNormMethod	m_preProcess_pixelTSNormMethod { HCI::pixelTSNormMethod::none }
	Specify if each pixel time-series is normalized.

realT	m_pixelTSSigma { 3 }
	Sigma-clipping parameter for pixel time-series normalization.

std::string	m_preProcess_outputPrefix
	Set path and file prefix to output the pre-processed images.

bool	m_preProcess_only { false }
	If true, then we stop after pre-processing.

int	m_combineMethod { HCI::meanCombine }
	Determine how to combine the PSF subtracted images.

std::string	m_weightFile
	Specifies a file containing the image weights, for combining with weighted mean.

realT	m_sigmaThreshold { 0 }
	The standard deviation threshold used if combineMethod == HCI::sigmaMeanCombine.

realT	m_minGoodFract { 0.0 }

std::string	m_auxDataDir { "/tmp/klipReduceAux/" }
	Location for temporary auxilliary output files (e.g. masks)

bool	m_moveAuxDataDir { true }
	Whether or not to move the temp. aux files.

int	m_doWriteFinim { 1 }
	Set whether the final combined image is written to disk.

std::string	m_outputDir
	The directory where to write output files.

std::string	m_finimName { "finim_" }
	The base file name of the output final image.

bool	m_exactFinimName { false }
	Use m_finimName exactly as specified, without appending a number or an extension.

bool	m_doOutputPSFSub { false }
	Controls whether or not the individual PSF subtracted images are written to disk.

std::string	m_PSFSubPrefix

Additional Inherited Members
Public Types inherited from mx::improc::HCIobservation< _realT >
typedef _realT	realT
	The arithmetic type used for calculations. Does not have to match the type in images on disk.

typedef Eigen::Array< realT, Eigen::Dynamic, Eigen::Dynamic >	eigenImageT
	The Eigen image array type basted on realT.

Constructor & Destructor Documentation

◆ KLIPreduction() [1/5]

template<typename _realT , class _derotFunctObj , typename _evCalcT >

mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::KLIPreduction ( )

Default c'tor.

Definition at line 342 of file KLIPreduction.hpp.

◆ KLIPreduction() [2/5]

template<typename _realT , class _derotFunctObj , typename _evCalcT >

mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::KLIPreduction	(	const std::string &	dir,
		const std::string &	prefix,
		const std::string &	ext
	)

Construct and load the target file list.

Populates the m_fileList vector by searching on disk for files which match "dir/prefix*.ext". See load_fileList

Parameters

[in]	dir	the directory to search for files.
[in]	prefix	the prefix of the files
[in]	ext	the extension of the files

Definition at line 347 of file KLIPreduction.hpp.

◆ KLIPreduction() [3/5]

template<typename _realT , class _derotFunctObj , typename _evCalcT >

mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::KLIPreduction ( const std::string & fileListFile )

explicit

Construct using a file containing the target file list.

Populates the m_fileList vector by reading the file, which should be a single column of new-line delimited file names.

Parameters

[in] fileListFile the full path to a file containing a list of files

Definition at line 355 of file KLIPreduction.hpp.

◆ KLIPreduction() [4/5]

template<typename _realT , class _derotFunctObj , typename _evCalcT >

mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::KLIPreduction	(	const std::string &	dir,
		const std::string &	prefix,
		const std::string &	ext,
		const std::string &	RDIdir,
		const std::string &	RDIprefix,
		const std::string &	RDIext = `""`
	)

Populates the m_fileList vector by searching on disk for files which match "dir/prefix*.ext". See load_fileList

Populates the m_RDIfileList vector by searching on disk for files which match "RDIdir/RDIprefix*.RDIext". See load_RDIfileList

Parameters

[in]	dir	the directory to search for files.
[in]	prefix	the prefix of the files
[in]	ext	the extension of the files, default is .fits
[in]	RDIdir	the directory to search for the reference files.
[in]	RDIprefix	the initial part of the file name for the reference files. Can be empty "".
[in]	RDIext	[optional] the extension to append to the RDI file name, must include the '.'. If empty "" then same extension as target files is used.

Definition at line 361 of file KLIPreduction.hpp.

◆ KLIPreduction() [5/5]

template<typename _realT , class _derotFunctObj , typename _evCalcT >

mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::KLIPreduction	(	const std::string &	fileListFile,
		const std::string &	RDIfileListFile
	)

explicit

Construct using a file containing the target file list and a file containing the RDI target file list Populates the m_fileList vector by reading the file, which should be a single column of new-line delimited file names.

Populates the m_RDIfileList vector by reading the file, which should be a single column of new-line delimited file names.

Parameters

[in]	fileListFile	a file name path to read for the target file names.
[in]	RDIfileListFile	a file name path to read for the reference file names.

Definition at line 372 of file KLIPreduction.hpp.

Member Function Documentation

◆ meanSubtract()

template<typename realT , class derotFunctObj , typename evCalcT >

void mx::improc::KLIPreduction< realT, derotFunctObj, evCalcT >::meanSubtract	(	eigenCube< realT > &	rims,
		eigenCube< realT > &	tims,
		eigenImageT &	cmask,
		std::vector< realT > &	sds
	)

Subtract the basis mean from each of the images.

The mean is subtracted according to m_meanSubMethod.

Parameters

	rims	[in.out] The reference images. These are mean subtracted on output.
	tims	[in.out] The target images, which can be the same cube as rims (tested by pointer comparison), in which case they will be ignored. Mean subtractedon output.
[in]	cmask	the cutout mask. Ignored if empty.
[out]	sds	The standard deviation of the mean subtracted reference images.

Definition at line 384 of file KLIPreduction.hpp.

References mx::improc::eigenCube< dataT >::image(), mx::improc::HCI::imageMean, mx::improc::imageMedian(), mx::improc::HCI::imageMedian, mx::improc::eigenCube< dataT >::mean(), mx::improc::HCI::meanImage, mx::improc::eigenCube< dataT >::median(), mx::improc::HCI::medianImage, mx::improc::HCI::none, mx::improc::HCI::rmsSigmaClipped, mx::improc::HCI::unknown, and mx::math::vectorVariance().

◆ regions() [1/2]

template<typename _realT , class _derotFunctObj , typename _evCalcT >

int mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::regions	(	const std::vector< realT > &	minr,
		const std::vector< realT > &	maxr,
		const std::vector< realT > &	minq,
		const std::vector< realT > &	maxq
	)

Run KLIP in a set of geometric search regions.

The arguments are 4 vectors, where each entry defines one component of the search region.

Returns: 0 on success; -1 on error

Parameters

[in]	minr
[in]	maxr
[in]	minq
[in]	maxq

Definition at line 540 of file KLIPreduction.hpp.

References mx::improc::cutImageRegion(), mx::math::dtor(), mx::improc::HCI::excludeAngle, mx::improc::HCI::excludeImno, mx::improc::HCI::excludeNone, mx::improc::HCI::excludePixel, mx::sys::get_curr_time(), mx::improc::eigenCube< dataT >::image(), and mx::fits::fitsFile< dataT >::write().

Referenced by mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::regions().

◆ regions() [2/2]

template<typename _realT , class _derotFunctObj , typename _evCalcT = double>

int mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::regions	(	realT	minr,
		realT	maxr,
		realT	minq,
		realT	maxq
	)

inline

Run KLIP in a geometric search region.

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Returns: 0 on success; -1 on error

Parameters

[in]	minr
[in]	maxr
[in]	minq
[in]	maxq

Definition at line 289 of file KLIPreduction.hpp.

References mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::regions().

◆ worker()

template<typename _realT , class _derotFunctObj , typename _evCalcT >

void mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::worker	(	eigenCube< realT > &	rims,
		eigenCube< realT > &	tims,
		eigenImageT &	cmask,
		std::vector< size_t > &	idx,
		realT	dang,
		realT	dangMax
	)

omp_get_num_threads();

Definition at line 947 of file KLIPreduction.hpp.

References mx::improc::eigenCube< dataT >::asVectors(), mx::math::calcKLModes(), mx::improc::eigenCube< dataT >::cube(), mx::math::eigenSYRK(), mx::improc::HCI::excludeNone, mx::sys::get_curr_time(), mx::ipc::ompLoopWatcher< _outputT, _printPretty, _printLoops, _printPercent, _printNLine, _time >::incrementAndOutputStatus(), mx::improc::insertImageRegion(), mx::improc::maskCircle(), mx::math::six_fifths(), and mx::fits::fitsFile< dataT >::write().

Member Data Documentation

◆ m_excludeMethod

template<typename _realT , class _derotFunctObj , typename _evCalcT = double>

int mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::m_excludeMethod { HCI::excludeNone }

Controls how reference images are excluded, if at all, from the covariance matrix for each target image based on a minimum criterion. Can have the following values:

HCI::excludeNone = no exclusion, all images included [default]
HCI::excludePixel = exclude based on pixels of rotation at the inner edge of the region
HCI::excludeAngle = exclude based on degrees of rotation at the inner edge of the region
HCI::excludeImno = exclude based on number of images

Definition at line 206 of file KLIPreduction.hpp.

◆ m_excludeMethodMax

template<typename _realT , class _derotFunctObj , typename _evCalcT = double>

int mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::m_excludeMethodMax { HCI::excludeNone }

Controls how reference images are excluded, if at all, from the covariance matrix for each target image based on a maximum criterion. Can have the following values:

HCI::excludeNone = no exclusion, all images included [default]
HCI::excludePixel = exclude based on pixels of rotation at the inner edge of the region
HCI::excludeAngle = exclude based on degrees of rotation at the inner edge of the region
HCI::excludeImno = exclude based on number of images

Definition at line 218 of file KLIPreduction.hpp.

◆ m_includeMethod

template<typename _realT , class _derotFunctObj , typename _evCalcT = double>

int mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::m_includeMethod { HCI::includeAll }

Controls how number of included images is calculated.

The number of included images is calculated after exclusion is complete. Can have the following values:

HCI::includeAll = all remaining images are included [default]
HCI::includeCorr = the m_includeRefNum of the remaining images which are most correlated with the target are included
HCI::includeTime = the m_includeRefNum of the remaining images which are closest in time to the target are included
HCI::includeAngle = the m_includeRefNum of the remaining images which are closest in angle to the target are included
HCI::includeImno = the m_includeRefNum of the remaining images which are closest in image number to the target are included

Definition at line 241 of file KLIPreduction.hpp.

◆ m_includeRefNum

template<typename _realT , class _derotFunctObj , typename _evCalcT = double>

int mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::m_includeRefNum { 0 }

Number of reference images to include in the covariance matrix.

If > 0, then at most this many images, determined by highest cross-correlation, are included. This is determined after rotational/image-number exclusion. If == 0, then all reference images are included.

Definition at line 226 of file KLIPreduction.hpp.

◆ m_maxDPx

template<typename _realT , class _derotFunctObj , typename _evCalcT = double>

realT mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::m_maxDPx { 0 }

Specify the maximum pixel difference at the inner edge of the search region

Definition at line 194 of file KLIPreduction.hpp.

◆ m_meanSubMethod

template<typename _realT , class _derotFunctObj , typename _evCalcT = double>

HCI::meanSubMethod mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::m_meanSubMethod { HCI::meanSubMethod::imageMean }

Specify how the data are centered for PCA within each search region.

Can have the following values:

HCI::meanSubMethod::imageMean = the mean of each image (within the search region) is subtracted from itself
HCI::meanSubMethod::imageMedian = the median of each image (within the search region) is subtracted from itself
HCI::meanSubMethod::imageMode = the mode of each image (within the search region) is subtracted from itself
HCI::meanSubMethod::meanImage = the mean image of the data is subtracted from each image
HCI::meanSubMethod::medianImage = the median image of the data is subtracted from each image

Definition at line 158 of file KLIPreduction.hpp.

◆ m_minDPx

template<typename _realT , class _derotFunctObj , typename _evCalcT = double>

realT mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::m_minDPx { 0 }

Specify the minimum pixel difference at the inner edge of the search region

Definition at line 190 of file KLIPreduction.hpp.

◆ m_Nmodes

template<typename _realT , class _derotFunctObj , typename _evCalcT = double>

std::vector<int> mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::m_Nmodes

Specifies the number of modes to include in the PSF.

The output image is a cube with a plane for each entry in m_Nmodes. Only the number of eigenvalues required for the maximum value of m_Nmodes are calculated, so this can have an important impact on speed.

Can be initialized as:

red.m_Nmodes={5,10,15,20};

Definition at line 184 of file KLIPreduction.hpp.

◆ m_pixelTSNormMethod

template<typename _realT , class _derotFunctObj , typename _evCalcT = double>

HCI::pixelTSNormMethod mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::m_pixelTSNormMethod {HCI::pixelTSNormMethod::none}

Specify if each pixel time-series is normalized.

This normalizaton is applied after centering. Can have the following values:

HCI::pixelTSNormMethod::none: no normalization (the default)
HCI::pixelTSNormMethod::rms: divide by the time-series rms
HCI::pixelTSNormMethod::rmsSigmaClipped: divide by the sigma-slipped time-series rms. The sigma is provided by m_pixelTSSigma.

Definition at line 167 of file KLIPreduction.hpp.

◆ m_pixelTSSigma

template<typename _realT , class _derotFunctObj , typename _evCalcT = double>

realT mx::improc::KLIPreduction< _realT, _derotFunctObj, _evCalcT >::m_pixelTSSigma {3}

Sigma-clipping parameter for pixel time-series normalization.

Definition at line 169 of file KLIPreduction.hpp.

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

improc/KLIPreduction.hpp

Public Member Functions

Public Attributes

Additional Inherited Members

Constructor & Destructor Documentation

◆ KLIPreduction() [1/5]

◆ KLIPreduction() [2/5]

◆ KLIPreduction() [3/5]

◆ KLIPreduction() [4/5]

◆ KLIPreduction() [5/5]

Member Function Documentation

◆ meanSubtract()

◆ regions() [1/2]

◆ regions() [2/2]

◆ worker()

Member Data Documentation

◆ m_excludeMethod

◆ m_excludeMethodMax

◆ m_includeMethod

◆ m_includeRefNum

◆ m_maxDPx

◆ m_meanSubMethod

◆ m_minDPx

◆ m_Nmodes

◆ m_pixelTSNormMethod

◆ m_pixelTSSigma