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Description
Interface Summary  

LineMinimizer<EvaluatorType extends Evaluator<Double,Double>>  Defines the functionality of a lineminimization algorithm, often called a "line search" algorithm. 
Class Summary  

AbstractAnytimeLineMinimizer<EvaluatorType extends Evaluator<Double,Double>>  Partial AnytimeAlgorithm implementation of a LineMinimizer. 
DirectionalVectorToDifferentiableScalarFunction  Creates a truly differentiable scalar function from a differentiable Vector function, instead of using a forwarddifferences approximation to the derivative like DirectionalVectorToScalarFunction does. 
DirectionalVectorToScalarFunction  Maps a vector function onto a scalar one by using a directional vector and vector offset, and the parameter to the function is a scalar value along the direction from the startpoint offset. 
InputOutputSlopeTriplet  Stores an InputOutputPair with corresponding slope (gradient) information 
LineBracket  Class that defines a bracket for a scalar function. 
LineMinimizerBacktracking  Implementation of the backtracking lineminimization algorithm. 
LineMinimizerDerivativeBased  This is an implementation of a lineminimization algorithm proposed by Fletcher that makes extensive use of firstorder derivative information. 
LineMinimizerDerivativeFree  This is an implementation of a LineMinimizer that does not require derivative information. 
WolfeConditions  The Wolfe conditions define a set of sufficient conditions for "sufficient decrease" in inexact line search. 
Provides line (scalar) minimization algorithms. These algorithms are primarily used as a subroutine in multivariate minimization algorithms.


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