Uses of Interface
de.torstennahm.integrate.sparse.index.Index

Packages that use Index

de.torstennahm.integrate.sparse	This package provides routines for multi-dimensional integration using the sparse grid algorithm and its adaptive version.
de.torstennahm.integrate.sparse.evaluateindex	Provides routines for the evaluation of indexes form the adaptive sparse integration index set.
de.torstennahm.integrate.sparse.index	Provides an implementation of mathematical multi-indices.
de.torstennahm.integrate.sparse.visualize	Contains visualization classes specific to the sparse grid integrators.

Uses of Index in de.torstennahm.integrate.sparse

Fields in de.torstennahm.integrate.sparse declared as Index

protected Index

EstimateIntegrator.zeroIndex

Fields in de.torstennahm.integrate.sparse with type parameters of type Index

protected java.util.Map<Index,EstimateIntegrator.EstimateData>	EstimateIntegrator.InternalIntegrator.indexMap
protected java.util.Map<Index,EvaluateIntegrator.EvalData>	EvaluateIntegrator.InternalIntegrator.indexMap

Methods in de.torstennahm.integrate.sparse with parameters of type Index

protected double	EstimateIntegrator.InternalIntegrator.calcEstimate(Index index)
boolean	ProductWeightIntegrator.canIntegrate(Index index) Returns whether integration is possible with the given index.
double	ProductWeightIntegrator.integrateWithIndex(de.torstennahm.math.Function function, Index index) Integrates the function at the specified index by using the tensor product of one-dimensional quadrature formulas.
int	ProductWeightIntegrator.neededEvaluations(Index index) Returns the number of evaluations of the function needed for evaluation of the specified index.

Constructors in de.torstennahm.integrate.sparse with parameters of type Index

CouldNotEvaluateInfo(Evaluator evaluator, Index index)

Uses of Index in de.torstennahm.integrate.sparse.evaluateindex

Methods in de.torstennahm.integrate.sparse.evaluateindex with parameters of type Index

boolean	Evaluator.canEvaluate(Index index) Returns whether the index evaluator can evaluate the given index.
boolean	DeltaWeightEvaluator.canEvaluate(Index index)
double	Evaluator.deltaEvaluate(Index index) Evaluates the integration function for the given integration index.
double	DeltaWeightEvaluator.deltaEvaluate(Index index)
int	Evaluator.pointsForIndex(Index index) Returns the number of points the function needs to be evaluated at for this index.
int	DeltaWeightEvaluator.pointsForIndex(Index index)

Uses of Index in de.torstennahm.integrate.sparse.index

Classes in de.torstennahm.integrate.sparse.index that implement Index

class	FastIndex Implements Index.
class	StackedIndex Implements Index.

Methods in de.torstennahm.integrate.sparse.index that return Index

Index	FastIndex.add(int entryNum, int add)
Index	StackedIndex.add(int entryNum, int increment)
Index	Index.add(int entryNum, int increment) Returns a new index with the specified increment at the specified entry.
Index	FlatIndexGenerator.next()
Index	WeightedIndexGenerator.next()
Index	FastIndex.set(int entryNum, int value)
Index	StackedIndex.set(int entryNum, int value)
Index	Index.set(int entryNum, int value) Returns a new index with the specified new value at the specified entry.

Constructors in de.torstennahm.integrate.sparse.index with parameters of type Index

FastIndex(Index index)
Creates an new FastIndex from any Index.

Uses of Index in de.torstennahm.integrate.sparse.visualize

Fields in de.torstennahm.integrate.sparse.visualize declared as Index

Index

IndexVisualizerData.index

Constructors in de.torstennahm.integrate.sparse.visualize with parameters of type Index

IndexContribution(Index index, double contribution)

IndexContributionEstimate(Index index, double estimate)

IndexStatus(Index index, java.lang.String status)

IndexVisualizerData(Index index)