Compute ensemble averaged statistics, by repetitively calling the member-function of a certain statistical measure with different data. More...

#include <GooseEYE/GooseEYE.h>

Public Member Functions
	Ensemble ()=default
	Constructor.

	Ensemble (const std::vector< size_t > &roi, bool periodic=true, bool variance=true)
	Constructor.

array_type::array< double >	result () const
	Get ensemble average.

array_type::array< double >	variance () const
	Get ensemble variance.

array_type::array< double >	data_first () const
	Get raw-data: ensemble sum of the first moment: x_1 + x_2 + ...

array_type::array< double >	data_second () const
	Get raw-data: ensemble sum of the second moment: x_1^2 + x_2^2 + ...

array_type::array< double >	norm () const
	Get raw-data: normalisation (number of measurements per pixel).

array_type::array< double >	distance () const
	Get the relative distance of each pixel in the 'region-of-interest' to its center.

array_type::array< double >	distance (size_t axis) const
	Get the relative distance of each pixel in the 'region-of-interest' to its center, along a specific axis (distance can now be positive and negative).

array_type::array< double >	distance (const std::vector< double > &h) const
	Get the relative distance of each pixel in the 'region-of-interest' to its center.

array_type::array< double >	distance (const std::vector< double > &h, size_t axis) const
	Get the relative distance of each pixel in the 'region-of-interest' to its center, along a specific axis (distance can now be positive and negative).

template<class T >
void	mean (const T &f)
	Add realization to arithmetic mean.

template<class T , class M >
void	mean (const T &f, const M &fmask)
	Add realization to arithmetic mean.

template<class T >
void	S2 (const T &f, const T &g)
	Add realization to 2-point correlation: P(f(i) * g(i + di)).

template<class T , class M >
void	S2 (const T &f, const T &g, const M &fmask, const M &gmask)
	Add realization to 2-point correlation: P(f(i) * g(i + di)).

template<class T >
void	C2 (const T &f, const T &g)
	Add realization to 2-point cluster function: P(f(i) == g(i + di)).

template<class T , class M >
void	C2 (const T &f, const T &g, const M &fmask, const M &gmask)
	Add realization to 2-point cluster function: P(f(i) == g(i + di)).

template<class T >
void	W2 (const T &w, const T &f)
	Add realization to weighted 2-point correlation.

template<class T , class M >
void	W2 (const T &w, const T &f, const M &fmask)
	Add realization to weighted 2-point correlation.

template<class C , class T >
void	W2c (const C &clusters, const C &centers, const T &f, path_mode mode=path_mode::Bresenham)
	Add realization to collapsed weighted 2-point correlation.

template<class C , class T , class M >
void	W2c (const C &clusters, const C &centers, const T &f, const M &fmask, path_mode mode=path_mode::Bresenham)
	Add realization to collapsed weighted 2-point correlation.

template<class T >
void	heightheight (const T &f)
	Add realization to height-height correlation.

template<class T , class M >
void	heightheight (const T &f, const M &fmask)
	Add realization to height-height correlation.

template<class T >
void	L (const T &f, path_mode mode=path_mode::Bresenham)
	Add realization to lineal-path function.

Detailed Description

Compute ensemble averaged statistics, by repetitively calling the member-function of a certain statistical measure with different data.

Note:

One class instance can only be used to compute one statistical measure.
Simple wrapper functions are provided to compute the statistical measure on one image.
The normalized result can be read at any moment using 'result', without affecting the raw-data.
The raw-data and normalization are separately stored as class member variables.

Definition at line 1402 of file GooseEYE.h.

Constructor & Destructor Documentation

◆ Ensemble()

GooseEYE::Ensemble::Ensemble	(	const std::vector< size_t > &	roi,
		bool	periodic = true,
		bool	variance = true )

inline

Constructor.

Parameters

roi	Shape of the 'region-of-interest' on which the statistics are computed.
periodic	Switch to assume image periodic.
variance	Switch to compute the variance together with the mean.

Definition at line 14 of file Ensemble.hpp.

Member Function Documentation

◆ C2() [1/2]

template<class T >

void GooseEYE::Ensemble::C2	(	const T &	f,
		const T &	g )

inline

Add realization to 2-point cluster function: P(f(i) == g(i + di)).

Parameters

f	The image.
g	The comparison image.

Definition at line 84 of file Ensemble_C2.hpp.

◆ C2() [2/2]

template<class T , class M >

void GooseEYE::Ensemble::C2	(	const T &	f,
		const T &	g,
		const M &	fmask,
		const M &	gmask )

inline

Add realization to 2-point cluster function: P(f(i) == g(i + di)).

Parameters

f	The image.
g	The comparison image.
fmask	Mask certain pixels of f (binary, 1: masked, 0: not masked).
gmask	Mask certain pixels of g (binary, 1: masked, 0: not masked).

Definition at line 15 of file Ensemble_C2.hpp.

◆ data_first()

array_type::array< double > GooseEYE::Ensemble::data_first ( ) const

inline

Get raw-data: ensemble sum of the first moment: x_1 + x_2 + ...

Returns: The sum along the 'region-of-interest' set at construction.

Definition at line 53 of file Ensemble.hpp.

◆ data_second()

array_type::array< double > GooseEYE::Ensemble::data_second ( ) const

inline

Get raw-data: ensemble sum of the second moment: x_1^2 + x_2^2 + ...

Returns: The sum along the 'region-of-interest' set at construction.

Definition at line 59 of file Ensemble.hpp.

◆ distance() [1/4]

array_type::array< double > GooseEYE::Ensemble::distance ( ) const

inline

Get the relative distance of each pixel in the 'region-of-interest' to its center.

Returns: The distances along the 'region-of-interest' set at construction.

Definition at line 103 of file Ensemble.hpp.

◆ distance() [2/4]

array_type::array< double > GooseEYE::Ensemble::distance ( const std::vector< double > & h ) const

inline

Get the relative distance of each pixel in the 'region-of-interest' to its center.

Convert the distance to physical dimensions.

Parameters

h	The physical dimensions of one pixel (in each direction).

Returns: The distances along the 'region-of-interest' set at construction.

Definition at line 114 of file Ensemble.hpp.

◆ distance() [3/4]

array_type::array< double > GooseEYE::Ensemble::distance	(	const std::vector< double > &	h,
		size_t	axis ) const

inline

Get the relative distance of each pixel in the 'region-of-interest' to its center, along a specific axis (distance can now be positive and negative).

Convert the distance to physical dimensions.

Parameters

h	The physical dimensions of one pixel (in each direction).
axis	Select axis.

Returns: The distances along the 'region-of-interest' set at construction.

Definition at line 127 of file Ensemble.hpp.

◆ distance() [4/4]

array_type::array< double > GooseEYE::Ensemble::distance ( size_t axis ) const

inline

Get the relative distance of each pixel in the 'region-of-interest' to its center, along a specific axis (distance can now be positive and negative).

Parameters

axis	Select axis.

Returns: The distances along the 'region-of-interest' set at construction.

Definition at line 71 of file Ensemble.hpp.

◆ heightheight() [1/2]

template<class T >

void GooseEYE::Ensemble::heightheight ( const T & f )

inline

Add realization to height-height correlation.

The height-height correlation, at position \( \Delta i \), is defined as: \( \frac{1}{N} \left( \sum_{i=1}^{N} (f_i - f_{i + \Delta i})^2 \right)^{1/2} \)

Parameters

f	The image.

Definition at line 80 of file Ensemble_heightheight.hpp.

◆ heightheight() [2/2]

template<class T , class M >

void GooseEYE::Ensemble::heightheight	(	const T &	f,
		const M &	fmask )

inline

Add realization to height-height correlation.

The height-height correlation, at position \( \Delta i \), is defined as: \( \frac{1}{N} \left( \sum_{i=1}^{N} (f_i - f_{i + \Delta i})^2 \right)^{1/2} \)

Parameters

f	The image.
fmask	Mask certain pixels of `f` (binary, 1: masked, 0: not masked).

Definition at line 15 of file Ensemble_heightheight.hpp.

◆ L()

template<class T >

void GooseEYE::Ensemble::L	(	const T &	f,
		path_mode	mode = path_mode::Bresenham )

inline

Add realization to lineal-path function.

Parameters

f	The image.
mode	Method to use (see "path_mode").

Definition at line 15 of file Ensemble_L.hpp.

◆ mean() [1/2]

template<class T >

void GooseEYE::Ensemble::mean ( const T & f )

Add realization to arithmetic mean.

Parameters

f	The image.

Definition at line 15 of file Ensemble_mean.hpp.

◆ mean() [2/2]

template<class T , class M >

void GooseEYE::Ensemble::mean	(	const T &	f,
		const M &	fmask )

Add realization to arithmetic mean.

Parameters

f	The image.
fmask	Mask certain pixels (binary, 1: masked, 0: not masked).

Definition at line 28 of file Ensemble_mean.hpp.

◆ norm()

array_type::array< double > GooseEYE::Ensemble::norm ( ) const

inline

Get raw-data: normalisation (number of measurements per pixel).

Returns: The norm along the 'region-of-interest' set at construction.

Definition at line 65 of file Ensemble.hpp.

◆ result()

array_type::array< double > GooseEYE::Ensemble::result ( ) const

inline

Get ensemble average.

Returns: The average along the 'region-of-interest' set at construction.

Definition at line 26 of file Ensemble.hpp.

◆ S2() [1/2]

template<class T >

void GooseEYE::Ensemble::S2	(	const T &	f,
		const T &	g )

inline

Add realization to 2-point correlation: P(f(i) * g(i + di)).

Parameters

f	The image.
g	The comparison image.

Definition at line 84 of file Ensemble_S2.hpp.

◆ S2() [2/2]

template<class T , class M >

void GooseEYE::Ensemble::S2	(	const T &	f,
		const T &	g,
		const M &	fmask,
		const M &	gmask )

inline

Add realization to 2-point correlation: P(f(i) * g(i + di)).

Parameters

f	The image.
g	The comparison image.
fmask	Mask certain pixels of f (binary, 1: masked, 0: not masked).
gmask	Mask certain pixels of g (binary, 1: masked, 0: not masked).

Definition at line 15 of file Ensemble_S2.hpp.

◆ variance()

array_type::array< double > GooseEYE::Ensemble::variance ( ) const

inline

Get ensemble variance.

Returns: The variance along the 'region-of-interest' set at construction.

Definition at line 37 of file Ensemble.hpp.

◆ W2() [1/2]

template<class T >

void GooseEYE::Ensemble::W2	(	const T &	w,
		const T &	f )

inline

Add realization to weighted 2-point correlation.

Parameters

w	The weights.
f	The image.

Definition at line 76 of file Ensemble_W2.hpp.

◆ W2() [2/2]

template<class T , class M >

void GooseEYE::Ensemble::W2	(	const T &	w,
		const T &	f,
		const M &	fmask )

inline

Add realization to weighted 2-point correlation.

Parameters

w	The weights.
f	The image.
fmask	Mask certain pixels of f (binary, 1: masked, 0: not masked).

Definition at line 15 of file Ensemble_W2.hpp.

◆ W2c() [1/2]

template<class C , class T , class M >

void GooseEYE::Ensemble::W2c	(	const C &	clusters,
		const C &	centers,
		const T &	f,
		const M &	fmask,
		path_mode	mode = path_mode::Bresenham )

inline

Add realization to collapsed weighted 2-point correlation.

Parameters

clusters	The clusters.
centers	The cluster-centers: label only at the center.
f	The image.
mode	Method to use (see "path_mode").
fmask	Mask certain pixels of f (binary, 1: masked, 0: not masked).

Definition at line 16 of file Ensemble_W2c.hpp.

◆ W2c() [2/2]

template<class C , class T >

void GooseEYE::Ensemble::W2c	(	const C &	clusters,
		const C &	centers,
		const T &	f,
		path_mode	mode = path_mode::Bresenham )

inline

Add realization to collapsed weighted 2-point correlation.

Parameters

clusters	The clusters.
centers	The cluster-centers: label only at the center.
f	The image.
mode	Method to use (see "path_mode").

Definition at line 123 of file Ensemble_W2c.hpp.

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

GooseEYE/GooseEYE.h
GooseEYE/Ensemble.hpp
GooseEYE/Ensemble_C2.hpp
GooseEYE/Ensemble_heightheight.hpp
GooseEYE/Ensemble_L.hpp
GooseEYE/Ensemble_mean.hpp
GooseEYE/Ensemble_S2.hpp
GooseEYE/Ensemble_W2.hpp
GooseEYE/Ensemble_W2c.hpp

Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ Ensemble()

Member Function Documentation

◆ C2() [1/2]

◆ C2() [2/2]

◆ data_first()

◆ data_second()

◆ distance() [1/4]

◆ distance() [2/4]

◆ distance() [3/4]

◆ distance() [4/4]

◆ heightheight() [1/2]

◆ heightheight() [2/2]

◆ L()

◆ mean() [1/2]

◆ mean() [2/2]

◆ norm()

◆ result()

◆ S2() [1/2]

◆ S2() [2/2]

◆ variance()

◆ W2() [1/2]

◆ W2() [2/2]

◆ W2c() [1/2]

◆ W2c() [2/2]