LevMarqFitting Struct Reference

LibRPA: LIBRPA::utils::LevMarqFitting Struct Reference
LibRPA
LIBRPA::utils::LevMarqFitting Struct Reference

Non-linear fitting using the Levenberg-Marquardt algorithm. More...

#include <fitting.h>

Public Member Functions

 LevMarqFitting (const LevMarqFitting &s)=delete
 
 LevMarqFitting (LevMarqFitting &&s)=delete
 
LevMarqFittingoperator= (const LevMarqFitting &s)=delete
 
LevMarqFittingoperator= (LevMarqFitting &&s)=delete
 
void fit (std::vector< double > &pars, const std::vector< double > &xs, const std::vector< double > &ys, const std::function< double(double, const std::vector< double > &)> &func, const std::function< void(std::vector< double > &, double, const std::vector< double > &)> &grad)
 perform the fitting More...
 
std::vector< double > fit_eval (std::vector< double > &pars, const std::vector< double > &xs, const std::vector< double > &ys, const std::function< double(double, const std::vector< double > &)> &func, const std::function< void(std::vector< double > &, double, const std::vector< double > &)> &grad, const std::vector< double > &xs_eval)
 perform the fitting and evaluate the functin on a set of abscissa points
 

Public Attributes

int d_maxiter
 Maximal number of iterations.
 
double d_init_lambda
 
double d_up_factor
 
double d_down_factor
 
double d_target_derr
 Target difference betwee errors of adjacent parameters estimate.
 
int d_final_it
 
double d_final_err
 
double d_final_derr
 

Detailed Description

Non-linear fitting using the Levenberg-Marquardt algorithm.

Member Function Documentation

◆ fit()

void LIBRPA::utils::LevMarqFitting::fit ( std::vector< double > &  pars,
const std::vector< double > &  xs,
const std::vector< double > &  ys,
const std::function< double(double, const std::vector< double > &)> &  func,
const std::function< void(std::vector< double > &, double, const std::vector< double > &)> &  grad 
)

perform the fitting

Parameters
[in,out]parsinitial parameters array, optimized after fitting
[in]xsabscissa
[in]ysvalues
[in]funcfunction to fit the data against
[in]gradgradient with respect to parameters
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The documentation for this struct was generated from the following files: