Class EvaluationRmsChecker
java.lang.Object
org.hipparchus.optim.nonlinear.vector.leastsquares.EvaluationRmsChecker
- All Implemented Interfaces:
ConvergenceChecker<LeastSquaresProblem.Evaluation>
public class EvaluationRmsChecker
extends Object
implements ConvergenceChecker<LeastSquaresProblem.Evaluation>
Check if an optimization has converged based on the change in computed RMS.
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Constructor Summary
ConstructorDescriptionEvaluationRmsChecker
(double tol) Create a convergence checker for the RMS with the same relative and absolute tolerance.EvaluationRmsChecker
(double relTol, double absTol) Create a convergence checker for the RMS with a relative and absolute tolerance. -
Method Summary
Modifier and TypeMethodDescriptionboolean
converged
(int iteration, LeastSquaresProblem.Evaluation previous, LeastSquaresProblem.Evaluation current) Check if the optimization algorithm has converged.
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Constructor Details
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EvaluationRmsChecker
public EvaluationRmsChecker(double tol) Create a convergence checker for the RMS with the same relative and absolute tolerance.Convenience constructor for when the relative and absolute tolerances are the same. Same as
new EvaluationRmsChecker(tol, tol)
.- Parameters:
tol
- the relative and absolute tolerance.- See Also:
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EvaluationRmsChecker
public EvaluationRmsChecker(double relTol, double absTol) Create a convergence checker for the RMS with a relative and absolute tolerance.The optimization has converged when the RMS of consecutive evaluations are equal to within the given relative tolerance or absolute tolerance.
- Parameters:
relTol
- the relative tolerance.absTol
- the absolute tolerance.- See Also:
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Method Details
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converged
public boolean converged(int iteration, LeastSquaresProblem.Evaluation previous, LeastSquaresProblem.Evaluation current) Check if the optimization algorithm has converged.- Specified by:
converged
in interfaceConvergenceChecker<LeastSquaresProblem.Evaluation>
- Parameters:
iteration
- Current iteration.previous
- Best point in the previous iteration.current
- Best point in the current iteration.- Returns:
true
if the algorithm is considered to have converged.
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