tinyopt::solvers::SolverGN< Hessian_t > Class Template Reference

Inheritance diagram for tinyopt::solvers::SolverGN< Hessian_t >:

Public Types
using	Base = SolverBase<typename Hessian_t::Scalar, SQRT(traits::params_trait<Hessian_t>::Dims)>
using	Scalar = typename Hessian_t::Scalar
using	H_t = Hessian_t
using	Grad_t = Vector<Scalar, Dims>
Public Types inherited from tinyopt::solvers::SolverBase< MatX::Scalar, SQRT(traits::params_trait< MatX >::Dims)>
using	Scalar

Public Member Functions
	SolverGN (const Options &options={})
void	InitWith (const Grad_t &g, const H_t &h)
	Initialize solver with specific gradient and hessian.
virtual void	reset ()
	Reset the solver state and clear gradient & hessian.
template<int D = Dims, std::enable_if_t< D==Dynamic, int > = 0>
bool	resize (int dims)
	Resize H and grad if needed, return true if they were resized.
template<int D = Dims, std::enable_if_t< D !=Dynamic, int > = 0>
bool	resize (int dims=Dims)
	Resize H and grad if needed, return true if they were resized.
void	clear ()
	Set gradient and hessian to 0s.
template<typename X_t>
bool	ResizeIfNeeded (const X_t &x)
	Check whether we need to resize the system (gradient), return true if it did.
template<typename X_t, typename AccFunc>
Scalar	Evaluate (const X_t &x, const AccFunc &acc, bool save)
	Accumulate residuals and return the final error.
template<typename X_t, typename AccFunc>
bool	Accumulate (const X_t &x, const AccFunc &acc)
	Accumulate residuals and update the gradient, returns true on success.
template<typename X_t, typename AccFunc>
bool	Build (const X_t &x, const AccFunc &acc_func, bool resize_and_clear=true)
std::optional< Vector< Scalar, Dims > >	Solve () const override
	Solve the linear system dx = -H^-1 * grad, returns nullopt on failure.
virtual Index	dims () const override
Scalar	MaxStdDev (bool use_damped=true) const
virtual std::optional< H_t >	Covariance () const
	Latest Covariance estimate.
const H_t &	Hessian () const
	Latest, eventually damped Hessian approximation (JtJ).
const H_t &	H () const
H_t &	H ()
const Grad_t &	Gradient () const
Grad_t &	Gradient ()
Scalar	GradientNorm () const
Scalar	GradientSquaredNorm () const
Public Member Functions inherited from tinyopt::solvers::SolverBase< MatX::Scalar, SQRT(traits::params_trait< MatX >::Dims)>
	SolverBase (const Options &options={})
bool	Clamp (Grad_t &g, Scalar minmax) const
	Clamp the gradient 'g' to within [-minmax, minmax], if minmax is not 0. Returns true if 'g' was clamped.
void	NormalizeCost (Cost &cost)
	Eventually normalize the cost.
virtual void	GoodStep (Scalar=0.0f)
virtual void	BadStep (Scalar=0.0f)
virtual void	FailedStep ()
virtual void	Rebuild (bool)
virtual std::string	stateAsString () const
const Cost &	cost () const

Public Attributes
const Options	options_

Static Public Attributes
static constexpr bool	IsNLLS = true
static constexpr bool	FirstOrder = false
static constexpr Index	Dims = SQRT(traits::params_trait<Hessian_t>::Dims)
Static Public Attributes inherited from tinyopt::solvers::SolverBase< MatX::Scalar, SQRT(traits::params_trait< MatX >::Dims)>
static constexpr Index	Dims

Protected Attributes
H_t	H_
Grad_t	grad_
Protected Attributes inherited from tinyopt::solvers::SolverBase< MatX::Scalar, SQRT(traits::params_trait< MatX >::Dims)>
const Options	options_
Cost	cost_

Member Function Documentation

Build()

template<typename Hessian_t = MatX>

template<typename X_t, typename AccFunc>

bool tinyopt::solvers::SolverGN< Hessian_t >::Build ( const X_t & x, const AccFunc & acc_func, bool resize_and_clear = true )

inline

Build the gradient and hessian by accumulating residuals and their jacobians Returns true on success

Covariance()

template<typename Hessian_t = MatX>

virtual std::optional< H_t > tinyopt::solvers::SolverGN< Hessian_t >::Covariance ( ) const

inlinevirtual

Latest Covariance estimate.

Reimplemented in tinyopt::solvers::SolverLM< Hessian_t >, and tinyopt::solvers::SolverLM< Hessian_t >.

dims()

template<typename Hessian_t = MatX>

virtual Index tinyopt::solvers::SolverGN< Hessian_t >::dims ( ) const

inlineoverridevirtual

Implements tinyopt::solvers::SolverBase< MatX::Scalar, SQRT(traits::params_trait< MatX >::Dims)>.

MaxStdDev()

template<typename Hessian_t = MatX>

Scalar tinyopt::solvers::SolverGN< Hessian_t >::MaxStdDev ( bool use_damped = true ) const

inline

Return the square root of the maximum (co)variance of the H.inv() H being the damped Hessian H_ if use_damped == true (faster) or un-damped Hessian() (accurate)

reset()

template<typename Hessian_t = MatX>

virtual void tinyopt::solvers::SolverGN< Hessian_t >::reset ( )

inlinevirtual

Reset the solver state and clear gradient & hessian.

Reimplemented in tinyopt::solvers::SolverDogLeg< Hessian_t >, tinyopt::solvers::SolverDogLeg< Hessian_t >, tinyopt::solvers::SolverLM< Hessian_t >, and tinyopt::solvers::SolverLM< Hessian_t >.

Solve()

template<typename Hessian_t = MatX>

std::optional< Vector< Scalar, Dims > > tinyopt::solvers::SolverGN< Hessian_t >::Solve ( ) const

inlineoverridevirtual

Solve the linear system dx = -H^-1 * grad, returns nullopt on failure.

Implements tinyopt::solvers::SolverBase< MatX::Scalar, SQRT(traits::params_trait< MatX >::Dims)>.

Reimplemented in tinyopt::solvers::SolverLM< Hessian_t >, and tinyopt::solvers::SolverLM< Hessian_t >.

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

• include/tinyopt/solvers/gn.h