ModelFunction Class Reference
[Classes of the ODIN data processing framework (odindata library)]

#include <fitting.h>

Inheritance diagram for ModelFunction:

[legend]Collaboration diagram for ModelFunction:

[legend]List of all members.

Public Member Functions
virtual float	evaluate_f (float x) const=0
virtual fvector	evaluate_df (float x) const=0
virtual unsigned int	numof_fitpars () const=0
virtual fitpar &	get_fitpar (unsigned int i)=0
bool	fit (const Array< float, 1 > &yvals, const Array< float, 1 > &ysigma=defaultArray, const Array< float, 1 > &xvals=defaultArray, unsigned int max_iterations=500, double tolerance=1.0e-4)
Array< float, 1 >	get_function (const Array< float, 1 > &xvals) const
Static Public Attributes
static const Array< float, 1 >	defaultArray
Protected Member Functions
	ModelFunction ()
virtual	~ModelFunction ()
Protected Attributes
fitpar	dummy_fitpar

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Detailed Description

Base class of all multi-dimensional function classes which are used for fitting. The function has an independent variable 'x' (the argument to evaluate_f), a dependent variable 'y' (the result of evaluate_f) and a number of function parameters. To use this class, derive from it and overload the virtual functions 'evaluate_f' (function value), 'evaluate_df' (first derivative), 'numof_fitpars', and 'get_fitpar'. Parameters which are modified during the fit should be members of type fitpar.

Definition at line 64 of file fitting.h.

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Member Function Documentation

virtual float ModelFunction::evaluate_f

(

float

x

)

const [pure virtual]

Returns the function value at position 'x'.

Implemented in ExponentialFunction, ExponentialFunctionWithOffset, GaussianFunction, and SinusFunction.

virtual fvector ModelFunction::evaluate_df

(

float

x

)

const [pure virtual]

Returns the first derivatives at position 'x'.

Implemented in ExponentialFunction, ExponentialFunctionWithOffset, GaussianFunction, and SinusFunction.

virtual unsigned int ModelFunction::numof_fitpars

(

)

const [pure virtual]

Returns the number of independent fitting parameters.

Implemented in ExponentialFunction, ExponentialFunctionWithOffset, GaussianFunction, and SinusFunction.

virtual fitpar& ModelFunction::get_fitpar

(

unsigned int

i

)

[pure virtual]

Returns reference to the i'th fitting parameter.

Implemented in ExponentialFunction, ExponentialFunctionWithOffset, GaussianFunction, and SinusFunction.

bool ModelFunction::fit	(	const Array< float, 1 > &	yvals,
		const Array< float, 1 > &	ysigma = defaultArray,
		const Array< float, 1 > &	xvals = defaultArray,
		unsigned int	max_iterations = 500,
		double	tolerance = 1.0e-4
	)

Fit the function to the given dataset. The current parameters are taken as starting values. Fits the function to the y-values 'yvals', and optionally to the corresponding y-error bars 'ysigma' and x-vals 'xvals'. If no error-bars are given, they are all set to 0.1 and if no x-vals are given equidistant points with an increment of one are chosen, i.e. xvals(i)=i; A maximum of 'max_iterations' iterations and the given 'tolerance' is used for the fit. Returns true on success.

Array<float,1> ModelFunction::get_function

(

const Array< float, 1 > &

xvals

)

const

Returns the function values for x-values 'xvals'.

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

• fitting.h

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