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Unfit
3.1.1
Data fitting and optimization software
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#include <NelderMeadTestFunctions.hpp>
Public Member Functions | |
| std::vector< double > | operator() (const std::vector< double > &x) |
Public Member Functions inherited from Unfit::GenericCostFunction | |
| virtual | ~GenericCostFunction () |
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:
| x | (input) vector containing coordinates of x and y |
(x^2 + y^2 + z^2).
Number of dimensions = 3 The global minimum is: (0, 0, 0) Initial guess:
Reference:
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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:
| x | (input) vector containing coordinates of x, y and z |
Implements Unfit::GenericCostFunction.
1.8.13