The GaussianModel2D class represents a two-dimensional Gaussian curve. More...

#include <datamodels2d.h>

Inheritance diagram for CTL::GaussianModel2D:

Collaboration diagram for CTL::GaussianModel2D:

Public Types
enum	{ Type = 1002 }

Public Types inherited from CTL::AbstractDataModel2D
enum	{ Type = 1000 }

Public Types inherited from CTL::SerializationInterface
enum	{ Type = -1, UserType = 65536 }

Public Member Functions
int	type () const override

float	valueAt (float x, float y) const override
	Returns the value from the model at position (x, y). More...

AbstractDataModel2D *	clone () const override

	GaussianModel2D (float amplitude=1.0f, float mean=0.0f, float std=1.0f, float correlation=0.0f)
	Constructs a GaussianModel2D; a model representing a two-dimensional Gaussian curve. More...

	GaussianModel2D (float amplitude, float meanX, float meanY, float stdX, float stdY, float correlation=0.0f)
	Constructs a GaussianModel2D; a model representing a two-dimensional Gaussian curve. More...

QVariant	toVariant () const override

QVariant	parameter () const override

void	setParameter (const QVariant &parameter) override
	Sets the parameters contained in parameter (a QVariantMap). More...

virtual void	setParameter (const QVariant &parameter)

void	setParameter (const QString &name, const QVariant &value)

Public Member Functions inherited from CTL::AbstractDataModel2D
void	setParameter (const QString &name, const QVariant &value)

void	fromVariant (const QVariant &variant) override

QString	name () const

void	setName (const QString &name)

Chunk2D< float >	sampleChunk (const SamplingRange &xRange, const SamplingRange &yRange, uint nbSamplesX, uint nbSamplesY) const

Public Member Functions inherited from CTL::SerializationInterface
virtual	~SerializationInterface ()=default

Private Member Functions
void	setSaveCorr (float corr)
	Helper function to set correlation value within valid range.

void	setSaveStdX (float std)
	Helper function to set standard deviation value within valid range.

void	setSaveStdY (float std)
	Helper function to set standard deviation value within valid range.

Private Attributes
float	_ampl = 1.0f

float	_meanX = 0.0f

float	_meanY = 0.0f

float	_stdX = 1.0f

float	_stdY = 1.0f

float	_corr = 0.0f

Friends
template<class >
struct	SerializationHelper::RegisterWithSerializationHelper

Additional Inherited Members
Protected Member Functions inherited from CTL::AbstractDataModel2D
	AbstractDataModel2D (const AbstractDataModel2D &)=default

	AbstractDataModel2D (AbstractDataModel2D &&)=default

AbstractDataModel2D &	operator= (const AbstractDataModel2D &)=default

AbstractDataModel2D &	operator= (AbstractDataModel2D &&)=default

Protected Member Functions inherited from CTL::SerializationInterface
	SerializationInterface ()=default

	SerializationInterface (const SerializationInterface &)=default

	SerializationInterface (SerializationInterface &&)=default

SerializationInterface &	operator= (const SerializationInterface &)=default

SerializationInterface &	operator= (SerializationInterface &&)=default

Related Functions inherited from CTL::AbstractDataModel2D
std::shared_ptr< AbstractDataModel2D >	operator+ (std::shared_ptr< AbstractDataModel2D > lhs, std::shared_ptr< AbstractDataModel2D > rhs)

std::shared_ptr< AbstractDataModel2D >	operator- (std::shared_ptr< AbstractDataModel2D > lhs, std::shared_ptr< AbstractDataModel2D > rhs)

std::shared_ptr< AbstractDataModel2D >	operator * (std::shared_ptr< AbstractDataModel2D > lhs, std::shared_ptr< AbstractDataModel2D > rhs)

std::shared_ptr< AbstractDataModel2D >	operator/ (std::shared_ptr< AbstractDataModel2D > lhs, std::shared_ptr< AbstractDataModel2D > rhs)

std::shared_ptr< AbstractDataModel2D > &	operator+= (std::shared_ptr< AbstractDataModel2D > &lhs, const std::shared_ptr< AbstractDataModel2D > &rhs)

std::shared_ptr< AbstractDataModel2D > &	operator-= (std::shared_ptr< AbstractDataModel2D > &lhs, const std::shared_ptr< AbstractDataModel2D > &rhs)

std::shared_ptr< AbstractDataModel2D > &	operator *= (std::shared_ptr< AbstractDataModel2D > &lhs, const std::shared_ptr< AbstractDataModel2D > &rhs)

std::shared_ptr< AbstractDataModel2D > &	operator/= (std::shared_ptr< AbstractDataModel2D > &lhs, const std::shared_ptr< AbstractDataModel2D > &rhs)

Detailed Description

The GaussianModel2D class represents a two-dimensional Gaussian curve.

This model maps input values according to a two-dimensional Gaussian function.

Constructor & Destructor Documentation

◆ GaussianModel2D() [1/2]

CTL::GaussianModel2D::GaussianModel2D	(	float	amplitude = `1.0f`,
		float	mean = `0.0f`,
		float	std = `1.0f`,
		float	correlation = `0.0f`
	)

explicit

Constructs a GaussianModel2D; a model representing a two-dimensional Gaussian curve.

This creates a model representing a two-dimensional Gaussian function specified by amplitude, mean, std, and correlation.

The passed parameters mean and std will be uses for both dimensions. Same as GaussianModel2D(amplitude, mean, mean, std, std, correlation).

Note that the input to std must be strictly positive, i.e. std > 0; and correlation must be between (excluding the borders) -1 and 1, i.e. -1.0 < correlation < 1.0.

Throws an std::domain_error for invalid input.

See also: valueAt()

◆ GaussianModel2D() [2/2]

CTL::GaussianModel2D::GaussianModel2D	(	float	amplitude,
		float	meanX,
		float	meanY,
		float	stdX,
		float	stdY,
		float	correlation = `0.0f`
	)

Constructs a GaussianModel2D; a model representing a two-dimensional Gaussian curve.

This creates a model representing a two-dimensional Gaussian function specified by amplitude, meanX, meanY, stdX, stdY, and correlation.

Note that the input to both standard deviation parameters (stdX, stdY) must be strictly positive, i.e. stdX > 0, stdY > 0; and correlation must be between (excluding the borders) -1 and 1, i.e. -1.0 < correlation < 1.0.

Throws an std::domain_error for invalid input.

See also: valueAt()

Member Function Documentation

◆ parameter()

QVariant CTL::GaussianModel2D::parameter ( ) const

overridevirtual

Returns the parameters of this model as a QVariant.

Default implementation returns an empty QVariant. Override in custom classes to encode all relevant information from the class' members. The returned QVariant must contain all information to fully specify the objects state. In particular, calling setParameter(parameter()) should not change the state of an object.

Reimplemented from CTL::AbstractDataModel2D.

◆ setParameter() [1/3]

void CTL::GaussianModel2D::setParameter ( const QVariant & parameter )

overridevirtual

Sets the parameters contained in parameter (a QVariantMap).

The value passed to parameter must be a QVariantMap containing one or multiple of the following (key, value)-pairs:

-("amplitude", [float] amplitude), -("meanX", [float] meanX), -("meanY", [float] meanY), -("stdX", [float] stdX), -("stdY", [float] stdY), -("correlation", [float] correlation).

stdX and stdY must be strictly positive, i.e. i.e. stdX > 0, stdY > 0; for other input, a warning is generated and a default value of 1.0 will be set. correlation must be between (excluding the borders) -1 and 1, i.e. -1.0 < correlation < 1.0; for other input, a warning is generated and a default value of 0.0 will be set.

Example: setting mean in y direction to 3, amplitude to 2.5 and a correlation of 0.5

auto gaussian = std::make_shared<GaussianModel2D>();
gaussian->setParameter(QVariantMap{ { "meanY", 3.0f },
                                    { "amplitude", 2.5f },
                                    { "correlation", 0.5f } } );

Reimplemented from CTL::AbstractDataModel2D.

◆ setParameter() [2/3]

void CTL::AbstractDataModel2D::setParameter

Sets the parameter with tag name to value, by passing a QVariantMap containing only the name, value pair as its sole entry to setParameter(const QVariant&).

This method is only useful if setParameter(const QVariant&) is implemented in a way that it allows for individual parameters to be set if the QVariant passed to it does only contain a selection of parameters. When overriding setParameter(const QVariant&) in custom classes, this method will be shadowed. In case you implemented setParameter(const QVariant&) in the way described above (i.e. such that setting individual parameters is possible), re-enable this method in the sub-class via

using AbstractDataModel2D::setParameter;

.

◆ setParameter() [3/3]

void CTL::AbstractDataModel2D::setParameter

Sets the parameters of this model based on data held in parameter.

Default implementation does nothing. Override in custom classes to extract all relevant information from parameter and set class members accordingly. A call to this method (given an appropriate input parameter) should prepare the full state of the object. In particular, calling setParameter(parameter()) should not change the state of an object.

◆ toVariant()

QVariant CTL::GaussianModel2D::toVariant ( ) const

overridevirtual

Interface to store all member variables in a QVariant.

Stores the object's type-id.

Reimplement this method such that it stores all newly introduced object data when sub-classing. This needs to cover everything that is necessary to fully determine the state of an object. Best practice is to invoke the base class version of this method to take care of all content originating from underlying base classes.

A typical reimplementation in sub-classes might look like this:

QVariantMap ret = DirectBaseClass::toVariant().toMap();
ret.insert("my member variable", _myMemberVariable);
return ret;

Reimplemented from CTL::AbstractDataModel2D.

◆ type()

int CTL::GaussianModel2D::type ( ) const

inlineoverridevirtual

Returns the type-id of the serializable object. Used in deserialization to determine the proper object type.

Add derived classes to the enumeration using the CTL_TYPE_ID macro.

Reimplemented from CTL::AbstractDataModel2D.

◆ valueAt()

float CTL::GaussianModel2D::valueAt	(	float	x,
		float	y
	)		const

overridevirtual

Returns the value from the model at position (x, y).

With the defining parameters of the Gaussian curve according to the constructor (see GaussianModel2D()):

amplitude: \( A \)
meanX: \( \mu_x \)
meanY: \( \mu_y \)
stdX: \( \sigma_x \)
stdY: \( \sigma_y \)
correlation: \( c \)

the resulting value is given by follwoing relation:

\( f(x)= \frac{A}{2\pi \sigma_x \sigma_y \sqrt{1-c^2}} \cdot \exp\left[-\frac{1}{2 (1-c^2)} \cdot \left( \frac{(x-\mu_x)^2}{\sigma_x^2} + \frac{(y-\mu_y)^2}{\sigma_y^2} - \frac{2c \cdot (x-\mu_x)(y-\mu_y)}{\sigma_x \sigma_y} \right) \right] \)

Implements CTL::AbstractDataModel2D.

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

modules/src/models/datamodels2d.h
modules/src/models/datamodels2d.cpp

Public Types

Public Member Functions

Private Member Functions

Private Attributes

Friends

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ GaussianModel2D() [1/2]

◆ GaussianModel2D() [2/2]

Member Function Documentation

◆ parameter()

◆ setParameter() [1/3]

◆ setParameter() [2/3]

◆ setParameter() [3/3]

◆ toVariant()

◆ type()

◆ valueAt()