Polynomial Curve Fitting. More...

Public Types
enum class	Strategy : uint8_t { IncrementalLeastSquares , LeastSquares , HouseholderQR , BDCSVD , COD , COUNT }
	Possible Fit strategies. More...

Public Member Functions
Polynomial< Scalar >	calcPolynomial () const
	Calculates the polynomial.

const ScrollingBuffer< std::pair< Scalar, Scalar > > &	data () const
	Gets the underlying buffer.

bool	empty () const
	Checks if the container has no elements.

	PolynomialRegressor (size_t polynomialDegree, size_t windowSize, Strategy strategy=Strategy::HouseholderQR)
	Constructor.

void	push_back (const Scalar &x, const Scalar &y)
	Add a data point to the polynomial.

void	push_back (const std::pair< Scalar, Scalar > &dataPoint)
	Add a data point to the polynomial.

void	reset ()
	Reset the polynomial coefficients and saved data.

void	setPolynomialDegree (size_t polynomialDegree)
	Set the Polynomial Degree and resets the data.

void	setStrategy (Strategy strategy)
	Set the strategy for the fit and resets the data.

void	setWindowSize (size_t windowSize)
	Sets the amount of points used for the fit (sliding window)

bool	windowSizeReached () const
	Checks if the amount of data points equals the window size.

Private Member Functions
void	pop_front ()
	Removes the first data point from the polynomial fit (sliding window)

Private Attributes
ScrollingBuffer< std::pair< Scalar, Scalar > >	_data
	Values added to the fit.

IncrementalLeastSquares< Scalar >	_incrementalLSQ
	Incremental LSQ Regressor.

size_t	_polyDegree
	Polynomial degree to fit.

Strategy	_strategy
	Strategy to use to fit the polynomial.

size_t	_windowSize
	Amount of points to store.

Detailed Description

template<typename Scalar = double>
class NAV::PolynomialRegressor< Scalar >

Polynomial Curve Fitting.

Template Parameters

Scalar Data type to store

Definition at line 38 of file PolynomialRegressor.hpp.

Member Enumeration Documentation

◆ Strategy

template<typename Scalar = double>

enum class NAV::PolynomialRegressor::Strategy : uint8_t

strong

Possible Fit strategies.

Enumerator
IncrementalLeastSquares	Incremental Least Squares (only polynomials of order <= 2)
LeastSquares	Least Squares (bas if even mildly ill-conditioned)
HouseholderQR	Householder QR decomposition.
BDCSVD	Bidiagonal Divide and Conquer SVD.
COD	Complete Orthogonal Decomposition.
COUNT	Amount of items in the enum.

Definition at line 42 of file PolynomialRegressor.hpp.

Constructor & Destructor Documentation

◆ PolynomialRegressor()

template<typename Scalar = double>

NAV::PolynomialRegressor< Scalar >::PolynomialRegressor	(	size_t	polynomialDegree,
		size_t	windowSize,
		Strategy	strategy = Strategy::HouseholderQR )

inline

Constructor.

Parameters

[in]	polynomialDegree	Degree of the polynomial to fit
[in]	windowSize	Amount of points to use for the fit (sliding window)
[in]	strategy	Strategy to use

Definition at line 56 of file PolynomialRegressor.hpp.

Member Function Documentation

◆ calcPolynomial()

template<typename Scalar = double>

Polynomial< Scalar > NAV::PolynomialRegressor< Scalar >::calcPolynomial ( ) const

inlinenodiscard

Calculates the polynomial.

Definition at line 143 of file PolynomialRegressor.hpp.

◆ data()

template<typename Scalar = double>

const ScrollingBuffer< std::pair< Scalar, Scalar > > & NAV::PolynomialRegressor< Scalar >::data ( ) const

inlinenodiscard

Gets the underlying buffer.

Definition at line 199 of file PolynomialRegressor.hpp.

◆ empty()

template<typename Scalar = double>

bool NAV::PolynomialRegressor< Scalar >::empty ( ) const

inlinenodiscard

Checks if the container has no elements.

Definition at line 196 of file PolynomialRegressor.hpp.

◆ pop_front()

template<typename Scalar = double>

void NAV::PolynomialRegressor< Scalar >::pop_front ( )

inlineprivate

Removes the first data point from the polynomial fit (sliding window)

Definition at line 214 of file PolynomialRegressor.hpp.

◆ push_back() [1/2]

template<typename Scalar = double>

void NAV::PolynomialRegressor< Scalar >::push_back	(	const Scalar &	x,
		const Scalar &	y )

inline

Add a data point to the polynomial.

Parameters

[in]	x	X Value
[in]	y	Y Value

Definition at line 111 of file PolynomialRegressor.hpp.

◆ push_back() [2/2]

template<typename Scalar = double>

void NAV::PolynomialRegressor< Scalar >::push_back ( const std::pair< Scalar, Scalar > & dataPoint )

inline

Add a data point to the polynomial.

Parameters

[in] dataPoint Data point

Definition at line 103 of file PolynomialRegressor.hpp.

◆ reset()

template<typename Scalar = double>

void NAV::PolynomialRegressor< Scalar >::reset ( )

inline

Reset the polynomial coefficients and saved data.

Definition at line 136 of file PolynomialRegressor.hpp.

◆ setPolynomialDegree()

template<typename Scalar = double>

void NAV::PolynomialRegressor< Scalar >::setPolynomialDegree ( size_t polynomialDegree )

inline

Set the Polynomial Degree and resets the data.

Parameters

[in] polynomialDegree Degree of the polynomial to fit

Definition at line 81 of file PolynomialRegressor.hpp.

◆ setStrategy()

template<typename Scalar = double>

void NAV::PolynomialRegressor< Scalar >::setStrategy ( Strategy strategy )

inline

Set the strategy for the fit and resets the data.

Parameters

strategy Strategy to use for fitting data

Definition at line 93 of file PolynomialRegressor.hpp.

◆ setWindowSize()

template<typename Scalar = double>

void NAV::PolynomialRegressor< Scalar >::setWindowSize ( size_t windowSize )

inline

Sets the amount of points used for the fit (sliding window)

Parameters

[in] windowSize Amount of points to use for the fit

Definition at line 65 of file PolynomialRegressor.hpp.

◆ windowSizeReached()

template<typename Scalar = double>

bool NAV::PolynomialRegressor< Scalar >::windowSizeReached ( ) const

inlinenodiscard

Checks if the amount of data points equals the window size.

Definition at line 190 of file PolynomialRegressor.hpp.

Field Documentation

◆ _data

template<typename Scalar = double>

ScrollingBuffer<std::pair<Scalar, Scalar> > NAV::PolynomialRegressor< Scalar >::_data

private

Values added to the fit.

Definition at line 209 of file PolynomialRegressor.hpp.

◆ _incrementalLSQ

template<typename Scalar = double>

IncrementalLeastSquares<Scalar> NAV::PolynomialRegressor< Scalar >::_incrementalLSQ

private

Incremental LSQ Regressor.

Definition at line 211 of file PolynomialRegressor.hpp.

◆ _polyDegree

template<typename Scalar = double>

size_t NAV::PolynomialRegressor< Scalar >::_polyDegree

private

Polynomial degree to fit.

Definition at line 205 of file PolynomialRegressor.hpp.

◆ _strategy

template<typename Scalar = double>

Strategy NAV::PolynomialRegressor< Scalar >::_strategy

private

Strategy to use to fit the polynomial.

Definition at line 203 of file PolynomialRegressor.hpp.

◆ _windowSize

template<typename Scalar = double>

size_t NAV::PolynomialRegressor< Scalar >::_windowSize

private

Amount of points to store.

Definition at line 207 of file PolynomialRegressor.hpp.

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

/home/runner/work/INSTINCT/INSTINCT/src/Navigation/Math/PolynomialRegressor.hpp

Public Types

Public Member Functions

Private Member Functions

Private Attributes

Detailed Description

Member Enumeration Documentation

◆ Strategy

Constructor & Destructor Documentation

◆ PolynomialRegressor()

Member Function Documentation

◆ calcPolynomial()

◆ data()

◆ empty()

◆ pop_front()

◆ push_back() [1/2]

◆ push_back() [2/2]

◆ reset()

◆ setPolynomialDegree()

◆ setStrategy()

◆ setWindowSize()

◆ windowSizeReached()

Field Documentation

◆ _data

◆ _incrementalLSQ

◆ _polyDegree

◆ _strategy

◆ _windowSize