Package gov.sandia.cognition.learning.algorithm.minimization.line.interpolator

Provides line (scalar) interpolation/extrapolation algorithms that fit an algebraic function to a (small) collection of data points.

See:
          Description

Interface Summary
LineBracketInterpolator<EvaluatorType extends Evaluator<Double,Double>> Definition of an interpolator/extrapolator for a LineBracket.
 

Class Summary
AbstractLineBracketInterpolator<EvaluatorType extends Evaluator<Double,Double>> Partial implementation of LinearBracketInterpolator
AbstractLineBracketInterpolatorPolynomial<EvaluatorType extends Evaluator<Double,Double>> Partial implementation of a LineBracketInterpolator based on a closed-form polynomial function.
LineBracketInterpolatorBrent Implements Brent's method of function interpolation to find a minimum.
LineBracketInterpolatorGoldenSection Interpolates between the two bound points of a LineBracket using the golden-section step rule, if that step fails, then the interpolator uses a linear (secant) interpolation.
LineBracketInterpolatorHermiteCubic Interpolates using a cubic with two points, both of which must have slope information.
LineBracketInterpolatorHermiteParabola Interpolates using a parabola with two points, at least one of which must have slope information.
LineBracketInterpolatorLinear Interpolates using a linear (stright-line) curve between two points, neither of which need slope information.
LineBracketInterpolatorParabola Interpolates using a parabola based on three points without slope information.
 

Package gov.sandia.cognition.learning.algorithm.minimization.line.interpolator Description

Provides line (scalar) interpolation/extrapolation algorithms that fit an algebraic function to a (small) collection of data points. These algorithms are primarily used as a subroutine in line-search algorithms.

Since:
2.1
Author:
Kevin R. Dixon