gtsam::FitBasis< Basis > Class Template Reference

Detailed Description

template<class Basis>
class gtsam::FitBasis< Basis >

Class that does regression via least squares Example usage: size_t N = 3; auto fit = FitBasis<Chebyshev2>(data_points, noise_model, N); Vector coefficients = fit.parameters();.

where data_points are a map from x to y values indicating a function mapping at specific points, noise_model is the gaussian noise model, and N is the degree of the polynomial basis used to fit the function.

Public Member Functions
	FitBasis (const Sequence &sequence, const SharedNoiseModel &model, size_t N)
	Construct a new FitBasis object. More...
Parameters	parameters () const
	Return Fourier coefficients.

Static Public Member Functions
static NonlinearFactorGraph	NonlinearGraph (const Sequence &sequence, const SharedNoiseModel &model, size_t N)
	Create nonlinear FG from Sequence.
static GaussianFactorGraph::shared_ptr	LinearGraph (const Sequence &sequence, const SharedNoiseModel &model, size_t N)
	Create linear FG from Sequence.

Public Types
using	Parameters = typename Basis::Parameters

Constructor & Destructor Documentation

FitBasis()

template<class Basis >

gtsam::FitBasis< Basis >::FitBasis ( const Sequence &  sequence, const SharedNoiseModel &  model, size_t  N  )

inline

Construct a new FitBasis object.

Parameters

sequence	map of x->y values for a function, a.k.a. y = f(x).
model	The noise model to use.
N	The degree of the polynomial to fit.

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

• /Users/dellaert/git/github/gtsam/basis/FitBasis.h