Class chi_fit_funct (o2scl)

O2scl : Class List

template<class vec_t = boost::numeric::ublas::vector<double>, class mat_t = boost::numeric::ublas::matrix<double>, class fit_func_t = fit_funct>
class chi_fit_funct : public o2scl::gen_fit_funct<boost::numeric::ublas::vector<double>, boost::numeric::ublas::matrix<double>>

Standard fitting function based on one-dimensional data with a numerical Jacobian.

This class specifies the deviations (in operator() ) and Jacobian (in jac()) for a fitting class like fit_nonlin. It assumes a one-dimensional data set with no uncertainty in the abcissae and a fitting function specified in a form similar to fit_funct.

The default method for numerically computing the Jacobian is from jacobian_gsl. This default is identical to the GSL approach, except that the default value of jacobian_gsl::epsmin is non-zero. See jacobian_gsl for more details.

Default template arguments

• vec_t - boost::numeric::ublas::vector < double >

• mat_t - boost::numeric::ublas::matrix < double >

• func_t - fit_funct

  Idea for Future:

  Allow a user-specified Jacobian or make that into a separate class?

  Default constructor?

Data and uncertainties

size_t ndat_

const vec_t *xdat_

const vec_t *ydat_

const vec_t *yerr_

fit_func_t *fun_

Fitting function.

chi_fit_funct(const chi_fit_funct&)

chi_fit_funct &operator=(const chi_fit_funct&)

Public Functions

inline chi_fit_funct(size_t ndat, const vec_t &xdat, const vec_t &ydat, const vec_t &yerr, fit_func_t &fun)

Create an object with specified data and specified fitting function.

inline void set_data(size_t ndat, const vec_t &xdat, const vec_t &ydat, const vec_t &yerr)

Set the data to be fit.

inline void set_func(fit_func_t &fun)

Set the fitting function.

inline virtual double chi2(size_t np, const vec_t &p)

Return \( \chi^2 \).

inline virtual void operator()(size_t np, const vec_t &p, size_t nd, vec_t &f)

Using parameters in p, compute the relative deviations in f.

inline virtual void jac(size_t np, vec_t &p, size_t nd, vec_t &f, mat_t &J)

Using parameters in p, compute the Jacobian in J.

inline virtual size_t get_ndata()

Return the number of data points.

Public Members

jacobian_gsl<std::function<int(size_t, const vec_t&, vec_t&)>, vec_t, mat_t> auto_jac

Automatic Jacobian object.

Protected Functions

inline int jac_mm_funct(size_t np, const vec_t &p, vec_t &f)

Reformulate operator() into a mm_funct object.

Protected Attributes

std::function<int(size_t, const vec_t&, vec_t&)> mfm

Function object for Jacobian object.