Class which, starting from an experimental variogram, enables fitting the various parameters of a Covariance part of a Model. More...

#include <ModelOptimVMap.hpp>

Inheritance diagram for ModelOptimVMap:

Detailed Description

Class which, starting from an experimental variogram, enables fitting the various parameters of a Covariance part of a Model.

Public Member Functions
	ModelOptimVMap (Model model, Constraints constraints=nullptr, const Option_AutoFit &mauto=Option_AutoFit(), const Option_VarioFit &optvar=Option_VarioFit())

	ModelOptimVMap (const ModelOptimVMap &m)

ModelOptimVMap &	operator= (const ModelOptimVMap &m)

virtual	~ModelOptimVMap ()

int	fit (const DbGrid *dbmap, bool flagGoulard=true, bool verbose=false)

int	loadEnvironment (const DbGrid *dbmap, bool flagGoulard=true, bool verbose=false)

Public Member Functions inherited from AModelOptim
	AModelOptim (Model model, Constraints constraints=nullptr, const Option_AutoFit &mauto=Option_AutoFit(), const Option_VarioFit &optvar=Option_VarioFit())

	AModelOptim (const AModelOptim &m)

AModelOptim &	operator= (const AModelOptim &m)

virtual	~AModelOptim ()

Static Public Member Functions
static double	evalCost (unsigned int nparams, const double current, double grad, void *my_func_data)

Constructor & Destructor Documentation

ModelOptimVMap::ModelOptimVMap	(	Model *	model,
		Constraints *	constraints = `nullptr`,
		const Option_AutoFit &	mauto = `Option_AutoFit()`,
		const Option_VarioFit &	optvar = `Option_VarioFit()`
	)

ModelOptimVMap::ModelOptimVMap ( const ModelOptimVMap & m )

ModelOptimVMap::~ModelOptimVMap ( )

virtual

double ModelOptimVMap::evalCost	(	unsigned int	nparams,
		const double *	current,
		double *	grad,
		void *	my_func_data
	)

static

int ModelOptimVMap::loadEnvironment	(	const DbGrid *	dbmap,
		bool	flagGoulard = `true`,
		bool	verbose = `false`
	)

ModelOptimVMap & ModelOptimVMap::operator= ( const ModelOptimVMap & m )

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