Unfit  3.1.1
Data fitting and optimization software
Public Member Functions | List of all members
Unfit::UnitTests::SampleCostFunction5 Class Reference

#include <NelderMeadTestFunctions.hpp>

Inheritance diagram for Unfit::UnitTests::SampleCostFunction5:
Unfit::GenericCostFunction

Public Member Functions

std::vector< double > operator() (const std::vector< double > &x)
 
- Public Member Functions inherited from Unfit::GenericCostFunction
virtual ~GenericCostFunction ()
 

Detailed Description

The Sample function 4 is defined as

(x^2 + (y - 11)^2 + (y^2 - 7 + x)^2).

Number of dimensions = 2 The global minimum is: (3, 2) Initial guess: (0, 0)

Reference: We overload the operator as is required in GenericCostFunction to calculate the cost of the function.

Behaviour: cost = x^2 + (y - 11)^2 + (y^2 - 7 + x)^2

Intended use : SampleCostFunction4 Func; cost = Func(const std::vector<double> x);

NOTE that the returned cost is the sqare root of the evaluation due to the fact the Nelder Mead class will square the cost.

Parameters:

Parameters
x(input) vector containing coordinates of x and y
Returns
cost The Sample function 5 is defined as

(x^2 + y^2 + z^2).

Number of dimensions = 3 The global minimum is: (0, 0, 0) Initial guess:

Reference:

Member Function Documentation

◆ operator()()

std::vector<double> Unfit::UnitTests::SampleCostFunction5::operator() ( const std::vector< double > &  x)
inlinevirtual

We overload the operator as is required in GenericCostFunction to calculate the cost of the function.

Behaviour: cost = x^2 + y^2 + z^2

Intended use : SampleCostFunction5 Func; cost = Func(const std::vector<double> x);

NOTE that the returned cost is the sqare root of the evaluation due to the fact the Nelder Mead class will square the cost.

Parameters:

Parameters
x(input) vector containing coordinates of x, y and z
Returns
cost

Implements Unfit::GenericCostFunction.


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