MATH-1092
Added parameter in "LineSearch" and "NonLinearConjugateGradientOptimizer". git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1573316 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Gilles Sadowski
parent
e2dc384d7b
commit
b95cfc9b57
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@ -54,6 +54,11 @@ public class LineSearch {
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* Automatic bracketing.
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*/
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private final BracketFinder bracket = new BracketFinder();
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/**
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* Extent of the initial interval used to find an interval that
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* brackets the optimum.
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*/
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private final double initialBracketingRange;
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/**
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* Optimizer on behalf of which the line search must be performed.
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*/
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@ -70,23 +75,33 @@ public class LineSearch {
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* @param optimizer Optimizer on behalf of which the line search
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* be performed.
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* Its {@link MultivariateOptimizer#computeObjectiveValue(double[])
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* computeObjectiveValue} method will be called by this class's
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* computeObjectiveValue} method will be called by the
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* {@link #search(double[],double[]) search} method.
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* @param relativeTolerance Relative threshold.
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* @param absoluteTolerance Absolute threshold.
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* @param relativeTolerance Search will stop when the function relative
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* difference between successive iterations is smaller than this value.
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* @param absoluteTolerance Search will stop when the function absolute
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* difference between successive iterations is smaller than this value.
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* @param initialBracketingRange Extent of the initial interval used to
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* find an interval that brackets the optimum.
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* If the optimized function varies a lot in the vicinity of the optimum,
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* it may be necessary to provide a value lower than the distance between
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* successive local minima.
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*/
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public LineSearch(MultivariateOptimizer optimizer,
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double relativeTolerance,
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double absoluteTolerance) {
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double absoluteTolerance,
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double initialBracketingRange) {
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mainOptimizer = optimizer;
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lineOptimizer = new BrentOptimizer(REL_TOL_UNUSED,
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ABS_TOL_UNUSED,
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new SimpleUnivariateValueChecker(relativeTolerance,
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absoluteTolerance));
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this.initialBracketingRange = initialBracketingRange;
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}
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/**
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* Find the minimum of the function {@code f(p + alpha * d)}.
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* Finds the number {@code alpha} that optimizes
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* {@code f(startPoint + alpha * direction)}.
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*
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* @param startPoint Starting point.
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* @param direction Search direction.
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@ -109,7 +124,7 @@ public class LineSearch {
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};
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final GoalType goal = mainOptimizer.getGoalType();
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bracket.search(f, goal, 0, 1);
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bracket.search(f, goal, 0, initialBracketingRange);
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// Passing "MAX_VALUE" as a dummy value because it is the enclosing
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// class that counts the number of evaluations (and will eventually
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// generate the exception).
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@ -86,7 +86,9 @@ public class NonLinearConjugateGradientOptimizer
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* search.
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*
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* @since 3.1
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* @deprecated As of v3.3, class is not used anymore.
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* @deprecated As of v3.3, this class is not used anymore.
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* This setting is replaced by the {@code initialBracketingRange}
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* argument to the new constructors.
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*/
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@Deprecated
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public static class BracketingStep implements OptimizationData {
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@ -125,6 +127,7 @@ public class NonLinearConjugateGradientOptimizer
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checker,
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1e-8,
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1e-8,
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1e-8,
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new IdentityPreconditioner());
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}
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@ -137,7 +140,7 @@ public class NonLinearConjugateGradientOptimizer
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* @param checker Convergence checker.
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* @param lineSearchSolver Solver to use during line search.
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* @deprecated as of 3.3. Please use
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* {@link #NonLinearConjugateGradientOptimizer(Formula,ConvergenceChecker,double,double)} instead.
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* {@link #NonLinearConjugateGradientOptimizer(Formula,ConvergenceChecker,double,double,double)} instead.
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*/
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@Deprecated
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public NonLinearConjugateGradientOptimizer(final Formula updateFormula,
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@ -158,17 +161,23 @@ public class NonLinearConjugateGradientOptimizer
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* @param checker Convergence checker.
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* @param relativeTolerance Relative threshold for line search.
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* @param absoluteTolerance Absolute threshold for line search.
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* @param initialBracketingRange Extent of the initial interval used to
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* find an interval that brackets the optimum in order to perform the
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* line search.
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*
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* @see LineSearch#LineSearch(MultivariateOptimizer,double,double)
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* @see LineSearch#LineSearch(MultivariateOptimizer,double,double,double)
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* @since 3.3
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*/
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public NonLinearConjugateGradientOptimizer(final Formula updateFormula,
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ConvergenceChecker<PointValuePair> checker,
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double relativeTolerance,
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double absoluteTolerance) {
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double absoluteTolerance,
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double initialBracketingRange) {
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this(updateFormula,
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checker,
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relativeTolerance,
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absoluteTolerance,
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initialBracketingRange,
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new IdentityPreconditioner());
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}
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@ -180,7 +189,7 @@ public class NonLinearConjugateGradientOptimizer
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* @param lineSearchSolver Solver to use during line search.
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* @param preconditioner Preconditioner.
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* @deprecated as of 3.3. Please use
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* {@link #NonLinearConjugateGradientOptimizer(Formula,ConvergenceChecker,double,double,Preconditioner)} instead.
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* {@link #NonLinearConjugateGradientOptimizer(Formula,ConvergenceChecker,double,double,double,Preconditioner)} instead.
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*/
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@Deprecated
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public NonLinearConjugateGradientOptimizer(final Formula updateFormula,
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@ -191,6 +200,7 @@ public class NonLinearConjugateGradientOptimizer
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checker,
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lineSearchSolver.getRelativeAccuracy(),
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lineSearchSolver.getAbsoluteAccuracy(),
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lineSearchSolver.getAbsoluteAccuracy(),
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preconditioner);
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}
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@ -202,13 +212,18 @@ public class NonLinearConjugateGradientOptimizer
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* @param preconditioner Preconditioner.
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* @param relativeTolerance Relative threshold for line search.
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* @param absoluteTolerance Absolute threshold for line search.
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* @param initialBracketingRange Extent of the initial interval used to
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* find an interval that brackets the optimum in order to perform the
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* line search.
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*
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* @see LineSearch#LineSearch(MultivariateOptimizer,double,double)
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* @see LineSearch#LineSearch(MultivariateOptimizer,double,double,double)
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* @since 3.3
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*/
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public NonLinearConjugateGradientOptimizer(final Formula updateFormula,
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ConvergenceChecker<PointValuePair> checker,
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double relativeTolerance,
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double absoluteTolerance,
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double initialBracketingRange,
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final Preconditioner preconditioner) {
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super(checker);
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@ -216,7 +231,8 @@ public class NonLinearConjugateGradientOptimizer
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this.preconditioner = preconditioner;
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line = new LineSearch(this,
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relativeTolerance,
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absoluteTolerance);
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absoluteTolerance,
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initialBracketingRange);
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}
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/**
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@ -127,7 +127,8 @@ public class PowellOptimizer
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// Create the line search optimizer.
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line = new LineSearch(this,
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lineRel,
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lineAbs);
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lineAbs,
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1d);
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}
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/**
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@ -110,7 +110,10 @@ public class BracketFinder {
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* @throws TooManyEvaluationsException if the maximum number of evaluations
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* is exceeded.
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*/
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public void search(UnivariateFunction func, GoalType goal, double xA, double xB) {
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public void search(UnivariateFunction func,
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GoalType goal,
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double xA,
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double xB) {
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evaluations.resetCount();
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final boolean isMinim = goal == GoalType.MINIMIZE;
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@ -105,7 +105,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-6, 1e-6),
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1e-3, 1e-3);
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1e-3, 1e-3, 1);
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optimizer.optimize(new MaxEval(100),
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problem.getObjectiveFunction(),
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problem.getObjectiveFunctionGradient(),
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@ -122,7 +122,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-6, 1e-6),
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1e-3, 1e-3);
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1e-3, 1e-3, 1);
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PointValuePair optimum
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= optimizer.optimize(new MaxEval(100),
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problem.getObjectiveFunction(),
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@ -145,7 +145,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-6, 1e-6),
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1e-3, 1e-3);
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1e-3, 1e-3, 1);
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PointValuePair optimum
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= optimizer.optimize(new MaxEval(100),
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problem.getObjectiveFunction(),
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@ -171,7 +171,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-6, 1e-6),
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1e-3, 1e-3);
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1e-3, 1e-3, 1);
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PointValuePair optimum
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= optimizer.optimize(new MaxEval(100),
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problem.getObjectiveFunction(),
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@ -193,7 +193,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-6, 1e-6),
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1e-3, 1e-3);
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1e-3, 1e-3, 1);
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PointValuePair optimum
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= optimizer.optimize(new MaxEval(100),
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problem.getObjectiveFunction(),
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@ -235,7 +235,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-13, 1e-13),
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1e-7, 1e-7,
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1e-7, 1e-7, 1,
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preconditioner);
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PointValuePair optimum
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@ -267,7 +267,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-6, 1e-6),
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1e-3, 1e-3);
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1e-3, 1e-3, 1);
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PointValuePair optimum
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= optimizer.optimize(new MaxEval(100),
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problem.getObjectiveFunction(),
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@ -288,7 +288,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-13, 1e-13),
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1e-15, 1e-15);
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1e-15, 1e-15, 1);
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PointValuePair optimum1
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= optimizer.optimize(new MaxEval(200),
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problem1.getObjectiveFunction(),
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@ -333,7 +333,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-6, 1e-6),
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1e-3, 1e-3);
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1e-3, 1e-3, 1);
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PointValuePair optimum
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= optimizer.optimize(new MaxEval(100),
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problem.getObjectiveFunction(),
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@ -356,7 +356,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-6, 1e-6),
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1e-3, 1e-3);
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1e-3, 1e-3, 1);
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PointValuePair optimum
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= optimizer.optimize(new MaxEval(100),
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problem.getObjectiveFunction(),
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@ -377,7 +377,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-6, 1e-6),
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1e-3, 1e-3);
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1e-3, 1e-3, 1);
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PointValuePair optimum
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= optimizer.optimize(new MaxEval(100),
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problem.getObjectiveFunction(),
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@ -400,7 +400,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-6, 1e-6),
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1e-3, 1e-3);
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1e-3, 1e-3, 1);
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PointValuePair optimum
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= optimizer.optimize(new MaxEval(100),
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problem.getObjectiveFunction(),
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@ -422,7 +422,7 @@ public class NonLinearConjugateGradientOptimizerTest {
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NonLinearConjugateGradientOptimizer optimizer
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= new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
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new SimpleValueChecker(1e-30, 1e-30),
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1e-15, 1e-13);
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1e-15, 1e-13, 1);
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PointValuePair optimum
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= optimizer.optimize(new MaxEval(100),
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problem.getObjectiveFunction(),
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