Interface DifferentiableMultivariateVectorialOptimizer
- All Known Implementing Classes:
AbstractLeastSquaresOptimizer
,GaussNewtonOptimizer
,LevenbergMarquardtOptimizer
,MultiStartDifferentiableMultivariateVectorialOptimizer
public interface DifferentiableMultivariateVectorialOptimizer
This interface represents an optimization algorithm for
vectorial differentiable objective functions
.
Optimization algorithms find the input point set that either maximize or minimize
an objective function.
- Since:
- 2.0
- Version:
- $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 févr. 2011) $
- See Also:
-
Method Summary
Modifier and TypeMethodDescriptionGet the convergence checker.int
Get the number of evaluations of the objective function.int
Get the number of iterations realized by the algorithm.int
Get the number of evaluations of the objective function jacobian .int
Get the maximal number of functions evaluations.int
Get the maximal number of iterations of the algorithm.optimize
(DifferentiableMultivariateVectorialFunction f, double[] target, double[] weights, double[] startPoint) Optimizes an objective function.void
Set the convergence checker.void
setMaxEvaluations
(int maxEvaluations) Set the maximal number of functions evaluations.void
setMaxIterations
(int maxIterations) Set the maximal number of iterations of the algorithm.
-
Method Details
-
setMaxIterations
void setMaxIterations(int maxIterations) Set the maximal number of iterations of the algorithm.- Parameters:
maxIterations
- maximal number of function calls .
-
getMaxIterations
int getMaxIterations()Get the maximal number of iterations of the algorithm.- Returns:
- maximal number of iterations
-
getIterations
int getIterations()Get the number of iterations realized by the algorithm.- Returns:
- number of iterations
-
setMaxEvaluations
void setMaxEvaluations(int maxEvaluations) Set the maximal number of functions evaluations.- Parameters:
maxEvaluations
- maximal number of function evaluations
-
getMaxEvaluations
int getMaxEvaluations()Get the maximal number of functions evaluations.- Returns:
- maximal number of functions evaluations
-
getEvaluations
int getEvaluations()Get the number of evaluations of the objective function.The number of evaluation correspond to the last call to the
optimize
method. It is 0 if the method has not been called yet.- Returns:
- number of evaluations of the objective function
-
getJacobianEvaluations
int getJacobianEvaluations()Get the number of evaluations of the objective function jacobian .The number of evaluation correspond to the last call to the
optimize
method. It is 0 if the method has not been called yet.- Returns:
- number of evaluations of the objective function jacobian
-
setConvergenceChecker
Set the convergence checker.- Parameters:
checker
- object to use to check for convergence
-
getConvergenceChecker
VectorialConvergenceChecker getConvergenceChecker()Get the convergence checker.- Returns:
- object used to check for convergence
-
optimize
VectorialPointValuePair optimize(DifferentiableMultivariateVectorialFunction f, double[] target, double[] weights, double[] startPoint) throws FunctionEvaluationException, OptimizationException, IllegalArgumentException Optimizes an objective function.Optimization is considered to be a weighted least-squares minimization. The cost function to be minimized is ∑weighti(objectivei-targeti)2
- Parameters:
f
- objective functiontarget
- target value for the objective functions at optimumweights
- weight for the least squares cost computationstartPoint
- the start point for optimization- Returns:
- the point/value pair giving the optimal value for objective function
- Throws:
FunctionEvaluationException
- if the objective function throws one during the searchOptimizationException
- if the algorithm failed to convergeIllegalArgumentException
- if the start point dimension is wrong
-