template<typename dataT>
class mx::improc::eigenCube< dataT >

An image cube with an Eigen-like API.

Definition at line 32 of file eigenCube.hpp.

#include <improc/eigenCube.hpp>

Public Member Functions
	eigenCube (Index nrows, Index ncols, Index nplanes)
	C'tor which will allocate space..
	eigenCube (dataT *ndata, size_t nrows, size_t ncols, size_t nplanes)
	C'tor taking an existing array as an argument.
	eigenCube (const eigenCube< dataT > &ec)
	Copy a cube into independently owned storage.
	eigenCube (eigenCube< dataT > &&ec) noexcept
	Move a cube, transferring any owned storage.
eigenCube< dataT > &	operator= (const eigenCube< dataT > &ec)
	Copy a cube into independently owned storage.
eigenCube< dataT > &	operator= (eigenCube< dataT > &&ec) noexcept
	Move a cube, transferring any owned storage.
void	clear ()
	De-allocate and set all sizes to 0.
Eigen::Map< Eigen::Array< dataT, Eigen::Dynamic, Eigen::Dynamic > >	cube ()
	Returns a 2D Eigen::Eigen::Map pointed at the entire cube.
Eigen::Map< Eigen::Array< dataT, Eigen::Dynamic, Eigen::Dynamic > >	image (Index n)
	Returns a 2D Eigen::Eigen::Map pointed at the specified image.
const Eigen::Map< Eigen::Array< dataT, Eigen::Dynamic, Eigen::Dynamic > >	image (Index n) const
	Returns a 2D Eigen::Eigen::Map pointed at the specified image.
Eigen::Map< Eigen::Array< dataT, Eigen::Dynamic, Eigen::Dynamic >, Eigen::Unaligned, Eigen::Stride< Eigen::Dynamic, Eigen::Dynamic > >	pixel (Index i, Index j)
	Returns an Eigen::Eigen::Map-ed vector of the pixels at the given coordinate.
Eigen::Map< Eigen::Array< dataT, Eigen::Dynamic, Eigen::Dynamic > >	asVectors ()
	Return an Eigen::Eigen::Map of the cube where each image is a vector.
void	Covar (Eigen::Matrix< dataT, Eigen::Dynamic, Eigen::Dynamic > &cv)
	Calculate the covariance matrix of the images in the cube.
template<typename eigenT>
void	sum (eigenT &mim)
	Calculate the sum image of the cube.
template<typename eigenT>
void	mean (eigenT &mim)
	Calculate the mean image of the cube.
template<typename eigenT, typename eigenCubeT>
void	mean (eigenT &mim, eigenCubeT &mask, double minGoodFract=0.0)
	Calculate the mean image of the cube with a mask.
template<typename eigenT>
void	mean (eigenT &mim, std::vector< dataT > &weights)
	Calculate the weighted mean image of the cube.
template<typename eigenT, typename eigenCubeT>
void	mean (eigenT &mim, std::vector< dataT > &weights, eigenCubeT &mask, double minGoodFract=0.0)
	Calculate the weighted mean image of the cube, with a mask cube.
template<typename eigenT>
void	median (eigenT &mim)
	Calculate the median image of the cube.
template<typename eigenT, typename eigenCubeT>
void	median (eigenT &mim, eigenCubeT &mask, double minGoodFract=0.0)
	Calculate the median image of the cube with a mask.
template<typename eigenT>
void	sigmaMean (eigenT &mim, Scalar sigma)
	Calculate the sigma clipped mean image of the cube.
template<typename eigenT, typename eigenCubeT>
void	sigmaMean (eigenT &mim, eigenCubeT &mask, Scalar sigma, double minGoodFract=0.0)
	Calculate the sigma clipped mean image of the cube, with a mask cube.
template<typename eigenT>
void	sigmaMean (eigenT &mim, std::vector< dataT > &weights, Scalar sigma)
	Calculate the sigma clipped weighted mean image of the cube.
template<typename eigenT, typename eigenCubeT>
void	sigmaMean (eigenT &mim, std::vector< dataT > &weights, eigenCubeT &mask, Scalar sigma, double minGoodFract=0.0)
	Calculate the sigma clipped weighted mean image of the cube, with a mask cube.

Protected Member Functions
template<typename eigenCubeT>
void	validateMaskedCombination (const eigenCubeT &mask, double minGoodFract) const
	Validate a mask and good-pixel threshold for a masked combination.
void	validateWeights (const std::vector< dataT > &weights) const
	Validate the number of weights for a weighted combination.
bool	hasEnoughGoodPixels (size_t goodPixels, double minGoodFract) const
	Test whether a nonempty set of good pixels meets the requested fraction.

Constructor & Destructor Documentation

◆ eigenCube() [1/4]

template<typename dataT>

mx::improc::eigenCube< dataT >::eigenCube	(	Index	nrows,
		Index	ncols,
		Index	nplanes )

C'tor which will allocate space..

Parameters

[in]	nrows	Number of rows in the cube
[in]	ncols	Number of columns the cube
[in]	nplanes	Number of planes in the cube

Definition at line 334 of file eigenCube.hpp.

◆ eigenCube() [2/4]

template<typename dataT>

mx::improc::eigenCube< dataT >::eigenCube	(	dataT *	ndata,
		size_t	nrows,
		size_t	ncols,
		size_t	nplanes )

C'tor taking an existing array as an argument.

The existing array is used as is, as in a map, and ownership is not taken. You are responsible for memory management, e.g. free-ing this array.

Parameters

[in]	ndata	Allocated array with a cube of nrows x ncols x nplanes
[in]	nrows	Number of rows in the cube
[in]	ncols	Number of columns the cube
[in]	nplanes	Number of planes in the cube

Definition at line 345 of file eigenCube.hpp.

◆ eigenCube() [3/4]

template<typename dataT>

mx::improc::eigenCube< dataT >::eigenCube ( const eigenCube< dataT > & ec )

Copy a cube into independently owned storage.

Parameters

[in] ec cube to copy.

Definition at line 356 of file eigenCube.hpp.

◆ eigenCube() [4/4]

template<typename dataT>

mx::improc::eigenCube< dataT >::eigenCube ( eigenCube< dataT > && ec )

noexcept

Move a cube, transferring any owned storage.

Parameters

[in,out] ec cube to move from.

Definition at line 362 of file eigenCube.hpp.

Member Function Documentation

◆ asVectors()

template<typename dataT>

Eigen::Map< Eigen::Array< dataT, Eigen::Dynamic, Eigen::Dynamic > > mx::improc::eigenCube< dataT >::asVectors ( )

Return an Eigen::Eigen::Map of the cube where each image is a vector.

Definition at line 561 of file eigenCube.hpp.

Referenced by Covar(), mx::AO::ifPInv(), mx::AO::m2cMatrix(), and unitTest::improcTest::eigenCubeTest::TEST_CASE().

◆ clear()

template<typename dataT>

void mx::improc::eigenCube< dataT >::clear ( )

De-allocate and set all sizes to 0.

Definition at line 464 of file eigenCube.hpp.

Referenced by operator=(), and unitTest::improcTest::eigenCubeTest::TEST_CASE().

◆ Covar()

template<typename dataT>

void mx::improc::eigenCube< dataT >::Covar ( Eigen::Matrix< dataT, Eigen::Dynamic, Eigen::Dynamic > & cv )

Calculate the covariance matrix of the images in the cube.

Definition at line 567 of file eigenCube.hpp.

References asVectors().

Referenced by unitTest::improcTest::eigenCubeTest::TEST_CASE().

◆ cube()

template<typename dataT>

Eigen::Map< Eigen::Array< dataT, Eigen::Dynamic, Eigen::Dynamic > > mx::improc::eigenCube< dataT >::cube ( )

Returns a 2D Eigen::Eigen::Map pointed at the entire cube.

Definition at line 528 of file eigenCube.hpp.

Referenced by TEST_CASE(), and unitTest::improcTest::eigenCubeTest::TEST_CASE().

◆ hasEnoughGoodPixels()

template<typename dataT>

bool mx::improc::eigenCube< dataT >::hasEnoughGoodPixels	(	size_t	goodPixels,
		double	minGoodFract ) const

protected

Test whether a nonempty set of good pixels meets the requested fraction.

Parameters

[in]	goodPixels	number of unmasked pixels.
[in]	minGoodFract	inclusive minimum fraction of good pixels.

Definition at line 319 of file eigenCube.hpp.

Referenced by mean(), mean(), median(), sigmaMean(), and sigmaMean().

◆ image() [1/2]

template<typename dataT>

Eigen::Map< Eigen::Array< dataT, Eigen::Dynamic, Eigen::Dynamic > > mx::improc::eigenCube< dataT >::image ( Index n )

Returns a 2D Eigen::Eigen::Map pointed at the specified image.

Parameters

[in] n the image number

Definition at line 534 of file eigenCube.hpp.

Referenced by mx::AO::influenceFunctionsGaussian(), mx::AO::analysis::fourierTemporalPSD< _realT, aosysT >::intensityPSD(), mx::wfp::lyotCoronagraph< _realT, _fpmaskFloatT >::loadFocalMask(), mx::AO::makeModfBasis(), mx::AO::makeZernikeBasis(), mx::AO::modesOnDM(), mx::AO::orthogonalizeBasis(), mx::unitTest::fitsTest::fitsFileTest::TEST_CASE(), TEST_CASE(), TEST_CASE(), unitTest::improcTest::eigenCubeTest::TEST_CASE(), unitTest::improcTest::eigenCubeTest::TEST_CASE(), unitTest::improcTest::eigenCubeTest::TEST_CASE(), unitTest::improcTest::eigenCubeTest::TEST_CASE(), unitTest::improcTest::eigenCubeTest::TEST_CASE(), unitTest::improcTest::eigenCubeTest::TEST_CASE(), and unitTest::improcTest::eigenCubeTest::TEST_CASE().

◆ image() [2/2]

template<typename dataT>

const Eigen::Map< Eigen::Array< dataT, Eigen::Dynamic, Eigen::Dynamic > > mx::improc::eigenCube< dataT >::image ( Index n ) const

Returns a 2D Eigen::Eigen::Map pointed at the specified image.

Parameters

[in] n the image number

Definition at line 540 of file eigenCube.hpp.

◆ mean() [1/4]

template<typename dataT>

template<typename eigenT>

void mx::improc::eigenCube< dataT >::mean ( eigenT & mim )

Calculate the mean image of the cube.

Template Parameters

eigenT an Eigen-like type.

Parameters

[out] mim the resultant mean image. Is resized.

Definition at line 590 of file eigenCube.hpp.

References pixel().

Referenced by unitTest::improcTest::eigenCubeTest::TEST_CASE(), unitTest::improcTest::eigenCubeTest::TEST_CASE(), unitTest::improcTest::eigenCubeTest::TEST_CASE(), and unitTest::improcTest::eigenCubeTest::TEST_CASE().

◆ mean() [2/4]

template<typename dataT>

template<typename eigenT, typename eigenCubeT>

void mx::improc::eigenCube< dataT >::mean	(	eigenT &	mim,
		eigenCubeT &	mask,
		double	minGoodFract = 0.0 )

Calculate the mean image of the cube with a mask.

A nonempty pixel sample is accepted when its good-pixel fraction is greater than or equal to minGoodFract. Rejected pixels are set to invalidNumber<Scalar>().

Template Parameters

eigenT	an Eigen-like type.
eigenCubeT	an eigenCube type.

Exceptions

mx::exception	with error_t::sizeerr if the mask dimensions do not match the cube.
mx::exception	with error_t::invalidarg if `minGoodFract` is not finite or is outside [0, 1].

Parameters

[out]	mim	the resultant mean image. Is resized.
[in]	mask	a mask cube. Only pixels with value 1 are included in the mean calculation.
[in]	minGoodFract	inclusive minimum fraction of good pixels in [0, 1].

Definition at line 606 of file eigenCube.hpp.

References hasEnoughGoodPixels(), mx::improc::invalidNumber(), pixel(), validateMaskedCombination(), and mx::math::vectorMean().

◆ mean() [3/4]

template<typename dataT>

template<typename eigenT>

void mx::improc::eigenCube< dataT >::mean	(	eigenT &	mim,
		std::vector< dataT > &	weights )

Calculate the weighted mean image of the cube.

Template Parameters

eigenT an Eigen-like type.

Exceptions

mx::exception with error_t::sizeerr if the weight count does not match the cube planes.

Parameters

[out]	mim	the resultant mean image. Is resized.
[in]	weights	a vector of weights to use for calculating the mean

Definition at line 647 of file eigenCube.hpp.

References pixel(), validateWeights(), and mx::math::vectorMean().

◆ mean() [4/4]

template<typename dataT>

template<typename eigenT, typename eigenCubeT>

void mx::improc::eigenCube< dataT >::mean	(	eigenT &	mim,
		std::vector< dataT > &	weights,
		eigenCubeT &	mask,
		double	minGoodFract = 0.0 )

Calculate the weighted mean image of the cube, with a mask cube.

A nonempty pixel sample is accepted when its good-pixel fraction is greater than or equal to minGoodFract. Rejected pixels are set to invalidNumber<Scalar>().

Template Parameters

eigenT	an Eigen-like type.
eigenCubeT	an eigenCube type.

Exceptions

mx::exception	with error_t::sizeerr if the mask dimensions or weight count do not match the cube.
mx::exception	with error_t::invalidarg if `minGoodFract` is not finite or is outside [0, 1].

Parameters

[out]	mim	the resultant mean image. Is resized.
[in]	weights	a vector of weights to use for calculating the mean
[in]	mask	a mask cube. Only pixels with value 1 are included in the mean calculation.
[in]	minGoodFract	inclusive minimum fraction of good pixels in [0, 1].

Definition at line 675 of file eigenCube.hpp.

References hasEnoughGoodPixels(), mx::improc::invalidNumber(), pixel(), validateMaskedCombination(), validateWeights(), and mx::math::vectorMean().

◆ median() [1/2]

template<typename dataT>

template<typename eigenT>

void mx::improc::eigenCube< dataT >::median ( eigenT & mim )

Calculate the median image of the cube.

Template Parameters

eigenT an Eigen-like type.

Parameters

[out] mim the resultant median image. Is resized.

Definition at line 717 of file eigenCube.hpp.

References mx::improc::imageMedian(), and pixel().

Referenced by unitTest::improcTest::eigenCubeTest::TEST_CASE(), unitTest::improcTest::eigenCubeTest::TEST_CASE(), unitTest::improcTest::eigenCubeTest::TEST_CASE(), and unitTest::improcTest::eigenCubeTest::TEST_CASE().

◆ median() [2/2]

template<typename dataT>

template<typename eigenT, typename eigenCubeT>

void mx::improc::eigenCube< dataT >::median	(	eigenT &	mim,
		eigenCubeT &	mask,
		double	minGoodFract = 0.0 )

Calculate the median image of the cube with a mask.

A nonempty pixel sample is accepted when its good-pixel fraction is greater than or equal to minGoodFract. Rejected pixels are set to invalidNumber<Scalar>().

Template Parameters

eigenT	an Eigen-like type.
eigenCubeT	an eigenCube type.

Exceptions

mx::exception	with error_t::sizeerr if the mask dimensions do not match the cube.
mx::exception	with error_t::invalidarg if `minGoodFract` is not finite or is outside [0, 1].

Parameters

[out]	mim	the resultant median image. Is resized.
[in]	mask	a mask cube. Only pixels with value 1 are included.
[in]	minGoodFract	the inclusive minimum fraction of good pixels.

Definition at line 735 of file eigenCube.hpp.

References hasEnoughGoodPixels(), mx::improc::invalidNumber(), pixel(), validateMaskedCombination(), and mx::math::vectorMedianInPlace().

◆ operator=() [1/2]

template<typename dataT>

eigenCube< dataT > & mx::improc::eigenCube< dataT >::operator= ( const eigenCube< dataT > & ec )

Copy a cube into independently owned storage.

Parameters

[in] ec cube to copy.

Definition at line 391 of file eigenCube.hpp.

◆ operator=() [2/2]

template<typename dataT>

eigenCube< dataT > & mx::improc::eigenCube< dataT >::operator= ( eigenCube< dataT > && ec )

noexcept

Move a cube, transferring any owned storage.

Parameters

[in,out] ec cube to move from.

Definition at line 409 of file eigenCube.hpp.

References clear().

◆ pixel()

template<typename dataT>

Eigen::Map< Eigen::Array< dataT, Eigen::Dynamic, Eigen::Dynamic >, Eigen::Unaligned, Eigen::Stride< Eigen::Dynamic, Eigen::Dynamic > > mx::improc::eigenCube< dataT >::pixel	(	Index	i,
		Index	j )

Returns an Eigen::Eigen::Map-ed vector of the pixels at the given coordinate.

Definition at line 549 of file eigenCube.hpp.

Referenced by mean(), mean(), mean(), mean(), median(), median(), sigmaMean(), sigmaMean(), sigmaMean(), sigmaMean(), sum(), TEST_CASE(), and unitTest::improcTest::eigenCubeTest::TEST_CASE().

◆ sigmaMean() [1/4]

template<typename dataT>

template<typename eigenT, typename eigenCubeT>

void mx::improc::eigenCube< dataT >::sigmaMean	(	eigenT &	mim,
		eigenCubeT &	mask,
		Scalar	sigma,
		double	minGoodFract = 0.0 )

Calculate the sigma clipped mean image of the cube, with a mask cube.

A nonempty pixel sample is accepted when its good-pixel fraction is greater than or equal to minGoodFract. Rejected pixels are set to invalidNumber<Scalar>().

Template Parameters

eigenT	an Eigen-like type.
eigenCubeT	an eigenCube type.

Exceptions

mx::exception	with error_t::sizeerr if the mask dimensions do not match the cube.
mx::exception	with error_t::invalidarg if `minGoodFract` is not finite or is outside [0, 1].

Parameters

[out]	mim	the resultant mean image. Is resized.
[in]	mask	a mask cube. Only pixels with value 1 are included in the mean calculation.
[in]	sigma	the sigma value at which to clip.
[in]	minGoodFract	inclusive minimum fraction of good pixels in [0, 1].

Definition at line 804 of file eigenCube.hpp.

References hasEnoughGoodPixels(), mx::improc::invalidNumber(), pixel(), validateMaskedCombination(), and mx::math::vectorSigmaMean().

◆ sigmaMean() [2/4]

template<typename dataT>

template<typename eigenT>

void mx::improc::eigenCube< dataT >::sigmaMean	(	eigenT &	mim,
		Scalar	sigma )

Calculate the sigma clipped mean image of the cube.

Template Parameters

eigenT an Eigen-like type.

Parameters

[out]	mim	the resultant mean image
[in]	sigma	the sigma value at which to clip.

Definition at line 775 of file eigenCube.hpp.

References pixel(), and mx::math::vectorSigmaMean().

Referenced by unitTest::improcTest::eigenCubeTest::TEST_CASE(), unitTest::improcTest::eigenCubeTest::TEST_CASE(), and unitTest::improcTest::eigenCubeTest::TEST_CASE().

◆ sigmaMean() [3/4]

template<typename dataT>

template<typename eigenT, typename eigenCubeT>

void mx::improc::eigenCube< dataT >::sigmaMean	(	eigenT &	mim,
		std::vector< dataT > &	weights,
		eigenCubeT &	mask,
		Scalar	sigma,
		double	minGoodFract = 0.0 )

Calculate the sigma clipped weighted mean image of the cube, with a mask cube.

A nonempty pixel sample is accepted when its good-pixel fraction is greater than or equal to minGoodFract. Rejected pixels are set to invalidNumber<Scalar>().

Template Parameters

eigenT	an Eigen-like type.
eigenCubeT	an eigenCube type.

Exceptions

mx::exception	with error_t::sizeerr if the mask dimensions or weight count do not match the cube.
mx::exception	with error_t::invalidarg if `minGoodFract` is not finite or is outside [0, 1].

Parameters

[out]	mim	the resultant mean image. Is resized.
[in]	weights	a vector of weights to use for calculating the mean
[in]	mask	a mask cube. Only pixels with value 1 are included in the mean calculation.
[in]	sigma	the sigma value at which to clip.
[in]	minGoodFract	inclusive minimum fraction of good pixels in [0, 1].

Definition at line 870 of file eigenCube.hpp.

References hasEnoughGoodPixels(), mx::improc::invalidNumber(), pixel(), validateMaskedCombination(), validateWeights(), and mx::math::vectorSigmaMean().

◆ sigmaMean() [4/4]

template<typename dataT>

template<typename eigenT>

void mx::improc::eigenCube< dataT >::sigmaMean	(	eigenT &	mim,
		std::vector< dataT > &	weights,
		Scalar	sigma )

Calculate the sigma clipped weighted mean image of the cube.

Template Parameters

eigenT an Eigen-like type.

Exceptions

mx::exception with error_t::sizeerr if the weight count does not match the cube planes.

Parameters

[out]	mim	the resultant mean image. Is resized.
[in]	weights	a vector of weights to use for calculating the mean
[in]	sigma	the sigma value at which to clip.

Definition at line 843 of file eigenCube.hpp.

References pixel(), validateWeights(), and mx::math::vectorSigmaMean().

◆ sum()

template<typename dataT>

template<typename eigenT>

void mx::improc::eigenCube< dataT >::sum ( eigenT & mim )

Calculate the sum image of the cube.

Template Parameters

eigenT an Eigen-like type.

Parameters

[out] mim the resultant sum image. Is resized.

Definition at line 574 of file eigenCube.hpp.

References pixel().

◆ validateMaskedCombination()

template<typename dataT>

template<typename eigenCubeT>

void mx::improc::eigenCube< dataT >::validateMaskedCombination	(	const eigenCubeT &	mask,
		double	minGoodFract ) const

protected

Validate a mask and good-pixel threshold for a masked combination.

Parameters

[in]	mask	mask cube whose dimensions must match this cube.
[in]	minGoodFract	inclusive minimum fraction of good pixels in [0, 1].

Definition at line 296 of file eigenCube.hpp.

References mx::exception, mx::invalidarg, mx::math::isFinite(), and mx::sizeerr.

Referenced by mean(), mean(), median(), sigmaMean(), and sigmaMean().

◆ validateWeights()

template<typename dataT>

void mx::improc::eigenCube< dataT >::validateWeights ( const std::vector< dataT > & weights ) const

protected

Validate the number of weights for a weighted combination.

Parameters

[in] weights weights whose count must match the number of planes.

Definition at line 310 of file eigenCube.hpp.

References mx::exception, and mx::sizeerr.

Referenced by mean(), mean(), sigmaMean(), and sigmaMean().

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

improc/eigenCube.hpp

Public Member Functions

Protected Member Functions

Constructor & Destructor Documentation

◆ eigenCube() [1/4]

◆ eigenCube() [2/4]

◆ eigenCube() [3/4]

◆ eigenCube() [4/4]

Member Function Documentation

◆ asVectors()

◆ clear()

◆ Covar()

◆ cube()

◆ hasEnoughGoodPixels()

◆ image() [1/2]

◆ image() [2/2]

◆ mean() [1/4]

◆ mean() [2/4]

◆ mean() [3/4]

◆ mean() [4/4]

◆ median() [1/2]

◆ median() [2/2]

◆ operator=() [1/2]

◆ operator=() [2/2]

◆ pixel()

◆ sigmaMean() [1/4]

◆ sigmaMean() [2/4]

◆ sigmaMean() [3/4]

◆ sigmaMean() [4/4]

◆ sum()

◆ validateMaskedCombination()

◆ validateWeights()