Fit a four parameter Gaussian curve to some data. More...

#include <GaussianEquation.hpp>

Inheritance diagram for Unfit::Examples::GaussianEquation:

Public Member Functions
	GaussianEquation (const std::vector< double > &data_x, const std::vector< double > &data_y)

std::vector< double >	operator() (const std::vector< double > &param)

Public Member Functions inherited from Unfit::GenericCostFunction
virtual	~GenericCostFunction ()

Private Attributes
const std::vector< double >	data_x_

const std::vector< double >	data_y_

Detailed Description

Fit a four parameter Gaussian curve to some data.

Here the goal is to fit a Gaussian curve with four parameters. The function is given by:

f(x) = A * exp (-(x - B)*(x - B) / 2*C*C) + D

The goal is to find the values of A, B, C & D that best fit the data. In terms of the model, A = param[0], B = param[1], C = param[2] and D = param[3].

Constructor & Destructor Documentation

◆ GaussianEquation()

Unfit::Examples::GaussianEquation::GaussianEquation	(	const std::vector< double > &	data_x,
		const std::vector< double > &	data_y
	)

inline

Create the cost function. Here the experimental data must be passed in, and cannot be changed (if you want to, just create another cost function object). Here the experimental data is two vectors, the independent variable (x), and the dependent variable (y).

Intended use : GaussianEquation cost_func(data_x, data_y);

Parameters

data_x	A vector of independent variable values
data_y	A vector of experimental observations

Member Function Documentation

◆ operator()()

std::vector<double> Unfit::Examples::GaussianEquation::operator() ( const std::vector< double > & param )

inlinevirtual

Calculate the linear distance (residuals) between our model and the data. This method encapsulates the model, and expects the current estimates of the unknown parameters as an input. See the class documentation for details about the model.

Intended use : residuals = cost_func(param)

Parameters

param A vector containing the current estimates of the parameters we are trying to fit

Returns: A vector containing the residuals

Implements Unfit::GenericCostFunction.

Member Data Documentation

◆ data_x_

const std::vector<double> Unfit::Examples::GaussianEquation::data_x_

private

A vector to store the experimental x values

◆ data_y_

const std::vector<double> Unfit::Examples::GaussianEquation::data_y_

private

A vector to store the experimental observations y

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

examples/GaussianEquation.hpp

Public Member Functions

Private Attributes