- checker(ConvergenceChecker<LeastSquaresProblem.Evaluation>) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder
-
Configure the convergence checker.
- checkerPair(ConvergenceChecker<PointVectorValuePair>) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder
-
Configure the convergence checker.
- clear() - Method in class org.hipparchus.optim.BaseMultiStartMultivariateOptimizer
-
Method that will called in order to clear all stored optima.
- clear() - Method in class org.hipparchus.optim.nonlinear.scalar.MultiStartMultivariateOptimizer
-
Method that will called in order to clear all stored optima.
- CMAESOptimizer - Class in org.hipparchus.optim.nonlinear.scalar.noderiv
-
An implementation of the active Covariance Matrix Adaptation Evolution Strategy (CMA-ES)
for non-linear, non-convex, non-smooth, global function minimization.
- CMAESOptimizer(int, double, boolean, int, int, RandomGenerator, boolean, ConvergenceChecker<PointValuePair>) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.CMAESOptimizer
-
- CMAESOptimizer.PopulationSize - Class in org.hipparchus.optim.nonlinear.scalar.noderiv
-
Population size.
- CMAESOptimizer.Sigma - Class in org.hipparchus.optim.nonlinear.scalar.noderiv
-
Input sigma values.
- computeJacobian(double[]) - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.ValueAndJacobianFunction
-
Compute the Jacobian.
- computeObjectiveGradient(double[]) - Method in class org.hipparchus.optim.nonlinear.scalar.GradientMultivariateOptimizer
-
Compute the gradient vector.
- computeObjectiveValue(double[]) - Method in class org.hipparchus.optim.nonlinear.scalar.MultivariateOptimizer
-
Computes the objective function value.
- computeObjectiveValue(double) - Method in class org.hipparchus.optim.univariate.UnivariateOptimizer
-
Computes the objective function value.
- computeValue(double[]) - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.ValueAndJacobianFunction
-
Compute the value.
- converged(int, P, P) - Method in class org.hipparchus.optim.AbstractConvergenceChecker
-
Check if the optimization algorithm has converged.
- converged(int, P, P) - Method in interface org.hipparchus.optim.ConvergenceChecker
-
Check if the optimization algorithm has converged.
- converged(int, P, P) - Method in class org.hipparchus.optim.ConvergenceCheckerAndMultiplexer
-
Check if the optimization algorithm has converged.
- converged(int, P, P) - Method in class org.hipparchus.optim.ConvergenceCheckerOrMultiplexer
-
Check if the optimization algorithm has converged.
- converged(int, LeastSquaresProblem.Evaluation, LeastSquaresProblem.Evaluation) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.EvaluationRmsChecker
-
Check if the optimization algorithm has converged.
- converged(int, P, P) - Method in class org.hipparchus.optim.SimplePointChecker
-
Check if the optimization algorithm has converged considering the
last two points.
- converged(int, PointValuePair, PointValuePair) - Method in class org.hipparchus.optim.SimpleValueChecker
-
Check if the optimization algorithm has converged considering the
last two points.
- converged(int, PointVectorValuePair, PointVectorValuePair) - Method in class org.hipparchus.optim.SimpleVectorValueChecker
-
Check if the optimization algorithm has converged considering the
last two points.
- converged(int, UnivariatePointValuePair, UnivariatePointValuePair) - Method in class org.hipparchus.optim.univariate.SimpleUnivariateValueChecker
-
Check if the optimization algorithm has converged considering the
last two points.
- ConvergenceChecker<P> - Interface in org.hipparchus.optim
-
This interface specifies how to check if an optimization algorithm has
converged.
- ConvergenceCheckerAndMultiplexer<P> - Class in org.hipparchus.optim
-
- ConvergenceCheckerAndMultiplexer(List<ConvergenceChecker<P>>) - Constructor for class org.hipparchus.optim.ConvergenceCheckerAndMultiplexer
-
Simple constructor.
- ConvergenceCheckerOrMultiplexer<P> - Class in org.hipparchus.optim
-
- ConvergenceCheckerOrMultiplexer(List<ConvergenceChecker<P>>) - Constructor for class org.hipparchus.optim.ConvergenceCheckerOrMultiplexer
-
Simple constructor.
- countEvaluations(LeastSquaresProblem, Incrementor) - Static method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresFactory
-
Count the evaluations of a particular problem.
- create(MultivariateJacobianFunction, RealVector, RealVector, RealMatrix, ConvergenceChecker<LeastSquaresProblem.Evaluation>, int, int, boolean, ParameterValidator) - Static method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresFactory
-
- create(MultivariateJacobianFunction, RealVector, RealVector, ConvergenceChecker<LeastSquaresProblem.Evaluation>, int, int) - Static method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresFactory
-
- create(MultivariateJacobianFunction, RealVector, RealVector, RealMatrix, ConvergenceChecker<LeastSquaresProblem.Evaluation>, int, int) - Static method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresFactory
-
- create(MultivariateVectorFunction, MultivariateMatrixFunction, double[], double[], RealMatrix, ConvergenceChecker<LeastSquaresProblem.Evaluation>, int, int) - Static method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresFactory
-
- GaussNewtonOptimizer - Class in org.hipparchus.optim.nonlinear.vector.leastsquares
-
Gauss-Newton least-squares solver.
- GaussNewtonOptimizer() - Constructor for class org.hipparchus.optim.nonlinear.vector.leastsquares.GaussNewtonOptimizer
-
Creates a Gauss Newton optimizer.
- GaussNewtonOptimizer(MatrixDecomposer, boolean) - Constructor for class org.hipparchus.optim.nonlinear.vector.leastsquares.GaussNewtonOptimizer
-
Create a Gauss Newton optimizer that uses the given matrix decomposition algorithm
to solve the normal equations.
- getAbsoluteThreshold() - Method in class org.hipparchus.optim.AbstractConvergenceChecker
-
- getChiSquare() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.AbstractEvaluation
-
Get the sum of the squares of the residuals.
- getChiSquare() - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem.Evaluation
-
Get the sum of the squares of the residuals.
- getCoefficients() - Method in class org.hipparchus.optim.linear.LinearConstraint
-
Gets the coefficients of the constraint (left hand side).
- getCoefficients() - Method in class org.hipparchus.optim.linear.LinearObjectiveFunction
-
Gets the coefficients of the linear equation being optimized.
- getConstantTerm() - Method in class org.hipparchus.optim.linear.LinearObjectiveFunction
-
Gets the constant of the linear equation being optimized.
- getConstraints() - Method in class org.hipparchus.optim.linear.LinearConstraintSet
-
Gets the set of linear constraints.
- getConstraints() - Method in class org.hipparchus.optim.linear.LinearOptimizer
-
- getConvergenceChecker() - Method in class org.hipparchus.optim.AbstractOptimizationProblem
-
Gets the convergence checker.
- getConvergenceChecker() - Method in class org.hipparchus.optim.BaseOptimizer
-
Gets the convergence checker.
- getConvergenceChecker() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresAdapter
-
Gets the convergence checker.
- getConvergenceChecker() - Method in interface org.hipparchus.optim.OptimizationProblem
-
Gets the convergence checker.
- getCost() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.AbstractEvaluation
-
Get the cost.
- getCost() - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem.Evaluation
-
Get the cost.
- getCostRelativeTolerance() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LevenbergMarquardtOptimizer
-
Gets the value of a tuning parameter.
- getCovariances(double) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.AbstractEvaluation
-
Get the covariance matrix of the optimized parameters.
- getCovariances(double) - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem.Evaluation
-
Get the covariance matrix of the optimized parameters.
- getDecomposer() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.GaussNewtonOptimizer
-
Get the matrix decomposition algorithm.
- getDecomposer() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.SequentialGaussNewtonOptimizer
-
Get the matrix decomposition algorithm.
- getDimension() - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.AbstractSimplex
-
Get simplex dimension.
- getEvaluationCounter() - Method in class org.hipparchus.optim.AbstractOptimizationProblem
-
Get a independent Incrementor that counts up to the maximum number of evaluations
and then throws an exception.
- getEvaluationCounter() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresAdapter
-
Get a independent Incrementor that counts up to the maximum number of evaluations
and then throws an exception.
- getEvaluationCounter() - Method in interface org.hipparchus.optim.OptimizationProblem
-
Get a independent Incrementor that counts up to the maximum number of evaluations
and then throws an exception.
- getEvaluations() - Method in class org.hipparchus.optim.BaseMultiStartMultivariateOptimizer
-
Gets the number of evaluations of the objective function.
- getEvaluations() - Method in class org.hipparchus.optim.BaseOptimizer
-
Gets the number of evaluations of the objective function.
- getEvaluations() - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresOptimizer.Optimum
-
Get the number of times the model was evaluated in order to produce this
optimum.
- getEvaluations() - Method in class org.hipparchus.optim.univariate.BracketFinder
-
- getEvaluations() - Method in class org.hipparchus.optim.univariate.MultiStartUnivariateOptimizer
-
Gets the number of evaluations of the objective function.
- getFHi() - Method in class org.hipparchus.optim.univariate.BracketFinder
-
- getFLo() - Method in class org.hipparchus.optim.univariate.BracketFinder
-
- getFMid() - Method in class org.hipparchus.optim.univariate.BracketFinder
-
- getFunction() - Method in class org.hipparchus.optim.linear.LinearOptimizer
-
- getGoalType() - Method in class org.hipparchus.optim.nonlinear.scalar.MultivariateOptimizer
-
- getGoalType() - Method in class org.hipparchus.optim.univariate.UnivariateOptimizer
-
- getHi() - Method in class org.hipparchus.optim.univariate.BracketFinder
-
- getInitialGuess() - Method in class org.hipparchus.optim.InitialGuess
-
Gets the initial guess.
- getInitialStepBoundFactor() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LevenbergMarquardtOptimizer
-
Gets the value of a tuning parameter.
- getIterationCounter() - Method in class org.hipparchus.optim.AbstractOptimizationProblem
-
Get a independent Incrementor that counts up to the maximum number of iterations
and then throws an exception.
- getIterationCounter() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresAdapter
-
Get a independent Incrementor that counts up to the maximum number of iterations
and then throws an exception.
- getIterationCounter() - Method in interface org.hipparchus.optim.OptimizationProblem
-
Get a independent Incrementor that counts up to the maximum number of iterations
and then throws an exception.
- getIterations() - Method in class org.hipparchus.optim.BaseOptimizer
-
Gets the number of iterations performed by the algorithm.
- getIterations() - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresOptimizer.Optimum
-
Get the number of times the algorithm iterated in order to produce this
optimum.
- getJacobian() - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem.Evaluation
-
Get the weighted Jacobian matrix.
- getLo() - Method in class org.hipparchus.optim.univariate.BracketFinder
-
- getLocalizedString(Locale) - Method in enum org.hipparchus.optim.LocalizedOptimFormats
- getLower() - Method in class org.hipparchus.optim.SimpleBounds
-
Gets the lower bounds.
- getLowerBound() - Method in class org.hipparchus.optim.BaseMultivariateOptimizer
-
- getMax() - Method in class org.hipparchus.optim.univariate.SearchInterval
-
Gets the upper bound.
- getMax() - Method in class org.hipparchus.optim.univariate.UnivariateOptimizer
-
- getMaxEval() - Method in class org.hipparchus.optim.MaxEval
-
Gets the maximum number of evaluations.
- getMaxEvaluations() - Method in class org.hipparchus.optim.BaseOptimizer
-
Gets the maximal number of function evaluations.
- getMaxEvaluations() - Method in class org.hipparchus.optim.univariate.BracketFinder
-
- getMaxIter() - Method in class org.hipparchus.optim.MaxIter
-
Gets the maximum number of evaluations.
- getMaxIterations() - Method in class org.hipparchus.optim.BaseOptimizer
-
Gets the maximal number of iterations.
- getMid() - Method in class org.hipparchus.optim.univariate.BracketFinder
-
- getMin() - Method in class org.hipparchus.optim.univariate.SearchInterval
-
Gets the lower bound.
- getMin() - Method in class org.hipparchus.optim.univariate.UnivariateOptimizer
-
- getObjectiveFunction() - Method in class org.hipparchus.optim.nonlinear.scalar.ObjectiveFunction
-
Gets the function to be optimized.
- getObjectiveFunction() - Method in class org.hipparchus.optim.univariate.UnivariateObjectiveFunction
-
Gets the function to be optimized.
- getObjectiveFunctionGradient() - Method in class org.hipparchus.optim.nonlinear.scalar.ObjectiveFunctionGradient
-
Gets the gradient of the function to be optimized.
- getObservationSize() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresAdapter
-
Get the number of observations (rows in the Jacobian) in this problem.
- getObservationSize() - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem
-
Get the number of observations (rows in the Jacobian) in this problem.
- getOldEvaluation() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.SequentialGaussNewtonOptimizer
-
Get the previous evaluation used by the optimizer.
- getOptima() - Method in class org.hipparchus.optim.BaseMultiStartMultivariateOptimizer
-
Gets all the optima found during the last call to optimize.
- getOptima() - Method in class org.hipparchus.optim.nonlinear.scalar.MultiStartMultivariateOptimizer
-
Gets all the optima found during the last call to optimize.
- getOptima() - Method in class org.hipparchus.optim.univariate.MultiStartUnivariateOptimizer
-
Gets all the optima found during the last call to optimize.
- getOrthoTolerance() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LevenbergMarquardtOptimizer
-
Gets the value of a tuning parameter.
- getParameterRelativeTolerance() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LevenbergMarquardtOptimizer
-
Gets the value of a tuning parameter.
- getParameterSize() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresAdapter
-
Get the number of parameters (columns in the Jacobian) in this problem.
- getParameterSize() - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem
-
Get the number of parameters (columns in the Jacobian) in this problem.
- getPoint(int) - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.AbstractSimplex
-
Get the simplex point stored at the requested index.
- getPoint() - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem.Evaluation
-
Get the abscissa (independent variables) of this evaluation.
- getPoint() - Method in class org.hipparchus.optim.PointValuePair
-
Gets the point.
- getPoint() - Method in class org.hipparchus.optim.PointVectorValuePair
-
Gets the point.
- getPoint() - Method in class org.hipparchus.optim.univariate.UnivariatePointValuePair
-
Get the point.
- getPointRef() - Method in class org.hipparchus.optim.PointValuePair
-
Gets a reference to the point.
- getPointRef() - Method in class org.hipparchus.optim.PointVectorValuePair
-
Gets a reference to the point.
- getPoints() - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.AbstractSimplex
-
Get the points of the simplex.
- getPopulationSize() - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.CMAESOptimizer.PopulationSize
-
- getRankingThreshold() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LevenbergMarquardtOptimizer
-
Gets the value of a tuning parameter.
- getReducedChiSquare(int) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.AbstractEvaluation
-
Get the reduced chi-square.
- getReducedChiSquare(int) - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem.Evaluation
-
Get the reduced chi-square.
- getRelationship() - Method in class org.hipparchus.optim.linear.LinearConstraint
-
Gets the relationship between left and right hand sides.
- getRelativeThreshold() - Method in class org.hipparchus.optim.AbstractConvergenceChecker
-
- getResiduals() - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem.Evaluation
-
Get the weighted residuals.
- getRMS() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.AbstractEvaluation
-
Get the normalized cost.
- getRMS() - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem.Evaluation
-
Get the normalized cost.
- getSigma() - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.CMAESOptimizer.Sigma
-
- getSigma(double) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.AbstractEvaluation
-
Get an estimate of the standard deviation of the parameters.
- getSigma(double) - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem.Evaluation
-
Get an estimate of the standard deviation of the parameters.
- getSize() - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.AbstractSimplex
-
Get simplex size.
- getSolution() - Method in class org.hipparchus.optim.linear.SolutionCallback
-
Retrieve the best solution found so far.
- getSourceString() - Method in enum org.hipparchus.optim.LocalizedOptimFormats
- getStart() - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresAdapter
-
Gets the initial guess.
- getStart() - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresProblem
-
Gets the initial guess.
- getStartPoint() - Method in class org.hipparchus.optim.BaseMultivariateOptimizer
-
Gets the initial guess.
- getStartValue() - Method in class org.hipparchus.optim.univariate.SearchInterval
-
Gets the start value.
- getStartValue() - Method in class org.hipparchus.optim.univariate.UnivariateOptimizer
-
- getStatisticsDHistory() - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.CMAESOptimizer
-
- getStatisticsFitnessHistory() - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.CMAESOptimizer
-
- getStatisticsMeanHistory() - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.CMAESOptimizer
-
- getStatisticsSigmaHistory() - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.CMAESOptimizer
-
- getUpper() - Method in class org.hipparchus.optim.SimpleBounds
-
Gets the upper bounds.
- getUpperBound() - Method in class org.hipparchus.optim.BaseMultivariateOptimizer
-
- getValue() - Method in class org.hipparchus.optim.linear.LinearConstraint
-
Gets the value of the constraint (right hand side).
- getValue() - Method in class org.hipparchus.optim.PointVectorValuePair
-
Gets the value of the objective function.
- getValue() - Method in class org.hipparchus.optim.univariate.UnivariatePointValuePair
-
Get the value of the objective function.
- getValueRef() - Method in class org.hipparchus.optim.PointVectorValuePair
-
Gets a reference to the value of the objective function.
- GoalType - Enum in org.hipparchus.optim.nonlinear.scalar
-
Goal type for an optimization problem (minimization or maximization of
a scalar function.
- GradientMultivariateOptimizer - Class in org.hipparchus.optim.nonlinear.scalar
-
Base class for implementing optimizers for multivariate scalar
differentiable functions.
- GradientMultivariateOptimizer(ConvergenceChecker<PointValuePair>) - Constructor for class org.hipparchus.optim.nonlinear.scalar.GradientMultivariateOptimizer
-
- lazyEvaluation(boolean) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder
-
Configure whether evaluation will be lazy or not.
- LeastSquaresAdapter - Class in org.hipparchus.optim.nonlinear.vector.leastsquares
-
- LeastSquaresAdapter(LeastSquaresProblem) - Constructor for class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresAdapter
-
- LeastSquaresBuilder - Class in org.hipparchus.optim.nonlinear.vector.leastsquares
-
- LeastSquaresBuilder() - Constructor for class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder
-
- LeastSquaresConverter - Class in org.hipparchus.optim.nonlinear.scalar
-
- LeastSquaresConverter(MultivariateVectorFunction, double[]) - Constructor for class org.hipparchus.optim.nonlinear.scalar.LeastSquaresConverter
-
Builds a simple converter for uncorrelated residuals with identical
weights.
- LeastSquaresConverter(MultivariateVectorFunction, double[], double[]) - Constructor for class org.hipparchus.optim.nonlinear.scalar.LeastSquaresConverter
-
Builds a simple converter for uncorrelated residuals with the
specified weights.
- LeastSquaresConverter(MultivariateVectorFunction, double[], RealMatrix) - Constructor for class org.hipparchus.optim.nonlinear.scalar.LeastSquaresConverter
-
Builds a simple converter for correlated residuals with the
specified weights.
- LeastSquaresFactory - Class in org.hipparchus.optim.nonlinear.vector.leastsquares
-
- LeastSquaresOptimizer - Interface in org.hipparchus.optim.nonlinear.vector.leastsquares
-
An algorithm that can be applied to a non-linear least squares problem.
- LeastSquaresOptimizer.Optimum - Interface in org.hipparchus.optim.nonlinear.vector.leastsquares
-
The optimum found by the optimizer.
- LeastSquaresProblem - Interface in org.hipparchus.optim.nonlinear.vector.leastsquares
-
The data necessary to define a non-linear least squares problem.
- LeastSquaresProblem.Evaluation - Interface in org.hipparchus.optim.nonlinear.vector.leastsquares
-
- LevenbergMarquardtOptimizer - Class in org.hipparchus.optim.nonlinear.vector.leastsquares
-
This class solves a least-squares problem using the Levenberg-Marquardt
algorithm.
- LevenbergMarquardtOptimizer() - Constructor for class org.hipparchus.optim.nonlinear.vector.leastsquares.LevenbergMarquardtOptimizer
-
Default constructor.
- LevenbergMarquardtOptimizer(double, double, double, double, double) - Constructor for class org.hipparchus.optim.nonlinear.vector.leastsquares.LevenbergMarquardtOptimizer
-
Construct an instance with all parameters specified.
- LinearConstraint - Class in org.hipparchus.optim.linear
-
A linear constraint for a linear optimization problem.
- LinearConstraint(double[], Relationship, double) - Constructor for class org.hipparchus.optim.linear.LinearConstraint
-
Build a constraint involving a single linear equation.
- LinearConstraint(RealVector, Relationship, double) - Constructor for class org.hipparchus.optim.linear.LinearConstraint
-
Build a constraint involving a single linear equation.
- LinearConstraint(double[], double, Relationship, double[], double) - Constructor for class org.hipparchus.optim.linear.LinearConstraint
-
Build a constraint involving two linear equations.
- LinearConstraint(RealVector, double, Relationship, RealVector, double) - Constructor for class org.hipparchus.optim.linear.LinearConstraint
-
Build a constraint involving two linear equations.
- LinearConstraintSet - Class in org.hipparchus.optim.linear
-
- LinearConstraintSet(LinearConstraint...) - Constructor for class org.hipparchus.optim.linear.LinearConstraintSet
-
Creates a set containing the given constraints.
- LinearConstraintSet(Collection<LinearConstraint>) - Constructor for class org.hipparchus.optim.linear.LinearConstraintSet
-
Creates a set containing the given constraints.
- LinearObjectiveFunction - Class in org.hipparchus.optim.linear
-
An objective function for a linear optimization problem.
- LinearObjectiveFunction(double[], double) - Constructor for class org.hipparchus.optim.linear.LinearObjectiveFunction
-
- LinearObjectiveFunction(RealVector, double) - Constructor for class org.hipparchus.optim.linear.LinearObjectiveFunction
-
- LinearOptimizer - Class in org.hipparchus.optim.linear
-
Base class for implementing linear optimizers.
- LinearOptimizer() - Constructor for class org.hipparchus.optim.linear.LinearOptimizer
-
Simple constructor with default settings.
- LineSearch - Class in org.hipparchus.optim.nonlinear.scalar
-
Class for finding the minimum of the objective function along a given
direction.
- LineSearch(MultivariateOptimizer, double, double, double) - Constructor for class org.hipparchus.optim.nonlinear.scalar.LineSearch
-
The BrentOptimizer default stopping criterion uses the
tolerances to check the domain (point) values, not the function
values.
- LocalizedOptimFormats - Enum in org.hipparchus.optim
-
Enumeration for localized messages formats used in exceptions messages.
- MaxEval - Class in org.hipparchus.optim
-
Maximum number of evaluations of the function to be optimized.
- MaxEval(int) - Constructor for class org.hipparchus.optim.MaxEval
-
- maxEvaluations(int) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder
-
Configure the max evaluations.
- MaxIter - Class in org.hipparchus.optim
-
Maximum number of iterations performed by an (iterative) algorithm.
- MaxIter(int) - Constructor for class org.hipparchus.optim.MaxIter
-
- maxIterations(int) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder
-
Configure the max iterations.
- MINIMUM_PROBLEM_DIMENSION - Static variable in class org.hipparchus.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer
-
Minimum dimension of the problem: 2
- model(MultivariateVectorFunction, MultivariateMatrixFunction) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder
-
Configure the model function.
- model(MultivariateJacobianFunction) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder
-
Configure the model function.
- model(MultivariateVectorFunction, MultivariateMatrixFunction) - Static method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresFactory
-
- MultiDirectionalSimplex - Class in org.hipparchus.optim.nonlinear.scalar.noderiv
-
This class implements the multi-directional direct search method.
- MultiDirectionalSimplex(int) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.MultiDirectionalSimplex
-
Build a multi-directional simplex with default coefficients.
- MultiDirectionalSimplex(int, double) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.MultiDirectionalSimplex
-
Build a multi-directional simplex with default coefficients.
- MultiDirectionalSimplex(int, double, double) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.MultiDirectionalSimplex
-
Build a multi-directional simplex with specified coefficients.
- MultiDirectionalSimplex(int, double, double, double) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.MultiDirectionalSimplex
-
Build a multi-directional simplex with specified coefficients.
- MultiDirectionalSimplex(double[]) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.MultiDirectionalSimplex
-
Build a multi-directional simplex with default coefficients.
- MultiDirectionalSimplex(double[], double, double) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.MultiDirectionalSimplex
-
Build a multi-directional simplex with specified coefficients.
- MultiDirectionalSimplex(double[][]) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.MultiDirectionalSimplex
-
Build a multi-directional simplex with default coefficients.
- MultiDirectionalSimplex(double[][], double, double) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.MultiDirectionalSimplex
-
Build a multi-directional simplex with specified coefficients.
- MultiStartMultivariateOptimizer - Class in org.hipparchus.optim.nonlinear.scalar
-
Multi-start optimizer.
- MultiStartMultivariateOptimizer(MultivariateOptimizer, int, RandomVectorGenerator) - Constructor for class org.hipparchus.optim.nonlinear.scalar.MultiStartMultivariateOptimizer
-
Create a multi-start optimizer from a single-start optimizer.
- MultiStartUnivariateOptimizer - Class in org.hipparchus.optim.univariate
-
Special implementation of the
UnivariateOptimizer interface
adding multi-start features to an existing optimizer.
- MultiStartUnivariateOptimizer(UnivariateOptimizer, int, RandomGenerator) - Constructor for class org.hipparchus.optim.univariate.MultiStartUnivariateOptimizer
-
Create a multi-start optimizer from a single-start optimizer.
- MultivariateFunctionMappingAdapter - Class in org.hipparchus.optim.nonlinear.scalar
-
- MultivariateFunctionMappingAdapter(MultivariateFunction, double[], double[]) - Constructor for class org.hipparchus.optim.nonlinear.scalar.MultivariateFunctionMappingAdapter
-
Simple constructor.
- MultivariateFunctionPenaltyAdapter - Class in org.hipparchus.optim.nonlinear.scalar
-
- MultivariateFunctionPenaltyAdapter(MultivariateFunction, double[], double[], double, double[]) - Constructor for class org.hipparchus.optim.nonlinear.scalar.MultivariateFunctionPenaltyAdapter
-
Simple constructor.
- MultivariateJacobianFunction - Interface in org.hipparchus.optim.nonlinear.vector.leastsquares
-
A interface for functions that compute a vector of values and can compute their
derivatives (Jacobian).
- MultivariateOptimizer - Class in org.hipparchus.optim.nonlinear.scalar
-
Base class for a multivariate scalar function optimizer.
- MultivariateOptimizer(ConvergenceChecker<PointValuePair>) - Constructor for class org.hipparchus.optim.nonlinear.scalar.MultivariateOptimizer
-
- ObjectiveFunction - Class in org.hipparchus.optim.nonlinear.scalar
-
Scalar function to be optimized.
- ObjectiveFunction(MultivariateFunction) - Constructor for class org.hipparchus.optim.nonlinear.scalar.ObjectiveFunction
-
- ObjectiveFunctionGradient - Class in org.hipparchus.optim.nonlinear.scalar
-
Gradient of the scalar function to be optimized.
- ObjectiveFunctionGradient(MultivariateVectorFunction) - Constructor for class org.hipparchus.optim.nonlinear.scalar.ObjectiveFunctionGradient
-
- of(LeastSquaresProblem.Evaluation, int, int) - Static method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresOptimizer.Optimum
-
Create a new optimum from an evaluation and the values of the counters.
- oppositeRelationship() - Method in enum org.hipparchus.optim.linear.Relationship
-
Gets the relationship obtained when multiplying all coefficients by -1.
- OptimizationData - Interface in org.hipparchus.optim
-
Marker interface.
- OptimizationProblem<P> - Interface in org.hipparchus.optim
-
Common settings for all optimization problems.
- optimize(OptimizationData...) - Method in class org.hipparchus.optim.BaseMultiStartMultivariateOptimizer
-
Stores data and performs the optimization.
- optimize(OptimizationData...) - Method in class org.hipparchus.optim.BaseMultivariateOptimizer
-
Stores data and performs the optimization.
- optimize(OptimizationData...) - Method in class org.hipparchus.optim.BaseOptimizer
-
Stores data and performs the optimization.
- optimize() - Method in class org.hipparchus.optim.BaseOptimizer
-
Performs the optimization.
- optimize(OptimizationData...) - Method in class org.hipparchus.optim.linear.LinearOptimizer
-
Stores data and performs the optimization.
- optimize(OptimizationData...) - Method in class org.hipparchus.optim.linear.SimplexSolver
-
Stores data and performs the optimization.
- optimize(OptimizationData...) - Method in class org.hipparchus.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer
-
Stores data and performs the optimization.
- optimize(OptimizationData...) - Method in class org.hipparchus.optim.nonlinear.scalar.GradientMultivariateOptimizer
-
Stores data and performs the optimization.
- optimize(OptimizationData...) - Method in class org.hipparchus.optim.nonlinear.scalar.MultivariateOptimizer
-
Stores data and performs the optimization.
- optimize(OptimizationData...) - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.CMAESOptimizer
-
Stores data and performs the optimization.
- optimize(OptimizationData...) - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.SimplexOptimizer
-
Stores data and performs the optimization.
- optimize(LeastSquaresProblem) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.GaussNewtonOptimizer
-
Solve the non-linear least squares problem.
- optimize(LeastSquaresProblem) - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresOptimizer
-
Solve the non-linear least squares problem.
- optimize(LeastSquaresProblem) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LevenbergMarquardtOptimizer
-
Solve the non-linear least squares problem.
- optimize(LeastSquaresProblem) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.SequentialGaussNewtonOptimizer
-
Solve the non-linear least squares problem.
- optimize(OptimizationData...) - Method in class org.hipparchus.optim.univariate.MultiStartUnivariateOptimizer
-
Stores data and performs the optimization.
- optimize(OptimizationData...) - Method in class org.hipparchus.optim.univariate.UnivariateOptimizer
-
Stores data and performs the optimization.
- org.hipparchus.optim - package org.hipparchus.optim
-
- org.hipparchus.optim.linear - package org.hipparchus.optim.linear
-
Optimization algorithms for linear constrained problems.
- org.hipparchus.optim.nonlinear.scalar - package org.hipparchus.optim.nonlinear.scalar
-
Algorithms for optimizing a scalar function.
- org.hipparchus.optim.nonlinear.scalar.gradient - package org.hipparchus.optim.nonlinear.scalar.gradient
-
This package provides optimization algorithms that require derivatives.
- org.hipparchus.optim.nonlinear.scalar.noderiv - package org.hipparchus.optim.nonlinear.scalar.noderiv
-
This package provides optimization algorithms that do not require derivatives.
- org.hipparchus.optim.nonlinear.vector.leastsquares - package org.hipparchus.optim.nonlinear.vector.leastsquares
-
This package provides algorithms that minimize the residuals
between observations and model values.
- org.hipparchus.optim.univariate - package org.hipparchus.optim.univariate
-
One-dimensional optimization algorithms.
- parameterValidator(ParameterValidator) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder
-
Configure the validator of the model parameters.
- ParameterValidator - Interface in org.hipparchus.optim.nonlinear.vector.leastsquares
-
Interface for validating a set of model parameters.
- parseOptimizationData(OptimizationData...) - Method in class org.hipparchus.optim.BaseMultivariateOptimizer
-
Scans the list of (required and optional) optimization data that
characterize the problem.
- parseOptimizationData(OptimizationData...) - Method in class org.hipparchus.optim.BaseOptimizer
-
Scans the list of (required and optional) optimization data that
characterize the problem.
- parseOptimizationData(OptimizationData...) - Method in class org.hipparchus.optim.linear.LinearOptimizer
-
Scans the list of (required and optional) optimization data that
characterize the problem.
- parseOptimizationData(OptimizationData...) - Method in class org.hipparchus.optim.linear.SimplexSolver
-
Scans the list of (required and optional) optimization data that
characterize the problem.
- parseOptimizationData(OptimizationData...) - Method in class org.hipparchus.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer
-
Scans the list of (required and optional) optimization data that
characterize the problem.
- parseOptimizationData(OptimizationData...) - Method in class org.hipparchus.optim.nonlinear.scalar.GradientMultivariateOptimizer
-
Scans the list of (required and optional) optimization data that
characterize the problem.
- parseOptimizationData(OptimizationData...) - Method in class org.hipparchus.optim.nonlinear.scalar.MultivariateOptimizer
-
Scans the list of (required and optional) optimization data that
characterize the problem.
- parseOptimizationData(OptimizationData...) - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.CMAESOptimizer
-
Scans the list of (required and optional) optimization data that
characterize the problem.
- parseOptimizationData(OptimizationData...) - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.SimplexOptimizer
-
Scans the list of (required and optional) optimization data that
characterize the problem.
- parseOptimizationData(OptimizationData...) - Method in class org.hipparchus.optim.univariate.UnivariateOptimizer
-
Scans the list of (required and optional) optimization data that
characterize the problem.
- PivotSelectionRule - Enum in org.hipparchus.optim.linear
-
Pivot selection rule to the use for a Simplex solver.
- PointValuePair - Class in org.hipparchus.optim
-
This class holds a point and the value of an objective function at
that point.
- PointValuePair(double[], double) - Constructor for class org.hipparchus.optim.PointValuePair
-
Builds a point/objective function value pair.
- PointValuePair(double[], double, boolean) - Constructor for class org.hipparchus.optim.PointValuePair
-
Builds a point/objective function value pair.
- PointVectorValuePair - Class in org.hipparchus.optim
-
This class holds a point and the vectorial value of an objective function at
that point.
- PointVectorValuePair(double[], double[]) - Constructor for class org.hipparchus.optim.PointVectorValuePair
-
Builds a point/objective function value pair.
- PointVectorValuePair(double[], double[], boolean) - Constructor for class org.hipparchus.optim.PointVectorValuePair
-
Build a point/objective function value pair.
- PopulationSize(int) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.CMAESOptimizer.PopulationSize
-
- PowellOptimizer - Class in org.hipparchus.optim.nonlinear.scalar.noderiv
-
Powell's algorithm.
- PowellOptimizer(double, double, ConvergenceChecker<PointValuePair>) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.PowellOptimizer
-
This constructor allows to specify a user-defined convergence checker,
in addition to the parameters that control the default convergence
checking procedure.
- PowellOptimizer(double, double, double, double, ConvergenceChecker<PointValuePair>) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.PowellOptimizer
-
This constructor allows to specify a user-defined convergence checker,
in addition to the parameters that control the default convergence
checking procedure and the line search tolerances.
- PowellOptimizer(double, double) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.PowellOptimizer
-
The parameters control the default convergence checking procedure.
- PowellOptimizer(double, double, double, double) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.PowellOptimizer
-
Builds an instance with the default convergence checking procedure.
- precondition(double[], double[]) - Method in class org.hipparchus.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer.IdentityPreconditioner
-
Precondition a search direction.
- precondition(double[], double[]) - Method in interface org.hipparchus.optim.nonlinear.scalar.gradient.Preconditioner
-
Precondition a search direction.
- Preconditioner - Interface in org.hipparchus.optim.nonlinear.scalar.gradient
-
This interface represents a preconditioner for differentiable scalar
objective function optimizers.
- search(double[], double[]) - Method in class org.hipparchus.optim.nonlinear.scalar.LineSearch
-
Finds the number alpha that optimizes
f(startPoint + alpha * direction).
- search(UnivariateFunction, GoalType, double, double) - Method in class org.hipparchus.optim.univariate.BracketFinder
-
Search new points that bracket a local optimum of the function.
- SearchInterval - Class in org.hipparchus.optim.univariate
-
Search interval and (optional) start value.
- SearchInterval(double, double, double) - Constructor for class org.hipparchus.optim.univariate.SearchInterval
-
- SearchInterval(double, double) - Constructor for class org.hipparchus.optim.univariate.SearchInterval
-
- SequentialGaussNewtonOptimizer - Class in org.hipparchus.optim.nonlinear.vector.leastsquares
-
Sequential Gauss-Newton least-squares solver.
- SequentialGaussNewtonOptimizer() - Constructor for class org.hipparchus.optim.nonlinear.vector.leastsquares.SequentialGaussNewtonOptimizer
-
Create a sequential Gauss Newton optimizer.
- SequentialGaussNewtonOptimizer(MatrixDecomposer, boolean, LeastSquaresProblem.Evaluation) - Constructor for class org.hipparchus.optim.nonlinear.vector.leastsquares.SequentialGaussNewtonOptimizer
-
Create a sequential Gauss Newton optimizer that uses the given matrix
decomposition algorithm to solve the normal equations.
- setPoint(int, PointValuePair) - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.AbstractSimplex
-
Store a new point at location index.
- setPoints(PointValuePair[]) - Method in class org.hipparchus.optim.nonlinear.scalar.noderiv.AbstractSimplex
-
Replace all points.
- Sigma(double[]) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.CMAESOptimizer.Sigma
-
- SimpleBounds - Class in org.hipparchus.optim
-
Simple optimization constraints: lower and upper bounds.
- SimpleBounds(double[], double[]) - Constructor for class org.hipparchus.optim.SimpleBounds
-
- SimplePointChecker<P extends Pair<double[],? extends Object>> - Class in org.hipparchus.optim
-
- SimplePointChecker(double, double) - Constructor for class org.hipparchus.optim.SimplePointChecker
-
Build an instance with specified thresholds.
- SimplePointChecker(double, double, int) - Constructor for class org.hipparchus.optim.SimplePointChecker
-
Builds an instance with specified thresholds.
- SimpleUnivariateValueChecker - Class in org.hipparchus.optim.univariate
-
Simple implementation of the
ConvergenceChecker interface
that uses only objective function values.
- SimpleUnivariateValueChecker(double, double) - Constructor for class org.hipparchus.optim.univariate.SimpleUnivariateValueChecker
-
Build an instance with specified thresholds.
- SimpleUnivariateValueChecker(double, double, int) - Constructor for class org.hipparchus.optim.univariate.SimpleUnivariateValueChecker
-
Builds an instance with specified thresholds.
- SimpleValueChecker - Class in org.hipparchus.optim
-
Simple implementation of the
ConvergenceChecker interface using
only objective function values.
- SimpleValueChecker(double, double) - Constructor for class org.hipparchus.optim.SimpleValueChecker
-
Build an instance with specified thresholds.
- SimpleValueChecker(double, double, int) - Constructor for class org.hipparchus.optim.SimpleValueChecker
-
Builds an instance with specified thresholds.
- SimpleVectorValueChecker - Class in org.hipparchus.optim
-
Simple implementation of the
ConvergenceChecker interface using
only objective function values.
- SimpleVectorValueChecker(double, double) - Constructor for class org.hipparchus.optim.SimpleVectorValueChecker
-
Build an instance with specified thresholds.
- SimpleVectorValueChecker(double, double, int) - Constructor for class org.hipparchus.optim.SimpleVectorValueChecker
-
Builds an instance with specified tolerance thresholds and
iteration count.
- SimplexOptimizer - Class in org.hipparchus.optim.nonlinear.scalar.noderiv
-
This class implements simplex-based direct search optimization.
- SimplexOptimizer(ConvergenceChecker<PointValuePair>) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.SimplexOptimizer
-
- SimplexOptimizer(double, double) - Constructor for class org.hipparchus.optim.nonlinear.scalar.noderiv.SimplexOptimizer
-
- SimplexSolver - Class in org.hipparchus.optim.linear
-
Solves a linear problem using the "Two-Phase Simplex" method.
- SimplexSolver() - Constructor for class org.hipparchus.optim.linear.SimplexSolver
-
Builds a simplex solver with default settings.
- SimplexSolver(double) - Constructor for class org.hipparchus.optim.linear.SimplexSolver
-
Builds a simplex solver with a specified accepted amount of error.
- SimplexSolver(double, int) - Constructor for class org.hipparchus.optim.linear.SimplexSolver
-
Builds a simplex solver with a specified accepted amount of error.
- SimplexSolver(double, int, double) - Constructor for class org.hipparchus.optim.linear.SimplexSolver
-
Builds a simplex solver with a specified accepted amount of error.
- SolutionCallback - Class in org.hipparchus.optim.linear
-
A callback object that can be provided to a linear optimizer to keep track
of the best solution found.
- SolutionCallback() - Constructor for class org.hipparchus.optim.linear.SolutionCallback
-
- solvePhase1(SimplexTableau) - Method in class org.hipparchus.optim.linear.SimplexSolver
-
Solves Phase 1 of the Simplex method.
- start(RealVector) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder
-
Configure the initial guess.
- start(double[]) - Method in class org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder
-
Configure the initial guess.
- store(P) - Method in class org.hipparchus.optim.BaseMultiStartMultivariateOptimizer
-
Method that will be called in order to store each found optimum.
- store(PointValuePair) - Method in class org.hipparchus.optim.nonlinear.scalar.MultiStartMultivariateOptimizer
-
Method that will be called in order to store each found optimum.
- validate(RealVector) - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.ParameterValidator
-
Validates the set of parameters.
- value(double[]) - Method in class org.hipparchus.optim.linear.LinearObjectiveFunction
-
Computes the value of the linear equation at the current point.
- value(RealVector) - Method in class org.hipparchus.optim.linear.LinearObjectiveFunction
-
Computes the value of the linear equation at the current point.
- value(double[]) - Method in class org.hipparchus.optim.nonlinear.scalar.LeastSquaresConverter
- value(double[]) - Method in class org.hipparchus.optim.nonlinear.scalar.MultivariateFunctionMappingAdapter
-
Compute the underlying function value from an unbounded point.
- value(double[]) - Method in class org.hipparchus.optim.nonlinear.scalar.MultivariateFunctionPenaltyAdapter
-
Computes the underlying function value from an unbounded point.
- value(RealVector) - Method in interface org.hipparchus.optim.nonlinear.vector.leastsquares.MultivariateJacobianFunction
-
Compute the function value and its Jacobian.
- ValueAndJacobianFunction - Interface in org.hipparchus.optim.nonlinear.vector.leastsquares
-
A interface for functions that compute a vector of values and can compute their
derivatives (Jacobian).
- valueOf(String) - Static method in enum org.hipparchus.optim.linear.PivotSelectionRule
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.hipparchus.optim.linear.Relationship
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.hipparchus.optim.LocalizedOptimFormats
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.hipparchus.optim.nonlinear.scalar.GoalType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.hipparchus.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer.Formula
-
Returns the enum constant of this type with the specified name.
- values() - Static method in enum org.hipparchus.optim.linear.PivotSelectionRule
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.hipparchus.optim.linear.Relationship
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.hipparchus.optim.LocalizedOptimFormats
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.hipparchus.optim.nonlinear.scalar.GoalType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.hipparchus.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer.Formula
-
Returns an array containing the constants of this enum type, in
the order they are declared.