de.jstacs.algorithms.optimization.termination
Class SmallStepCondition

java.lang.Object
  de.jstacs.algorithms.optimization.termination.SmallStepCondition

All Implemented Interfaces:

TerminationCondition

public class SmallStepCondition
extends Object
implements TerminationCondition

This class implements a TerminationCondition that allows no further iteration in an optimization if the scalar product of the current and the last values of x will be small, i.e., .

Author:

Jens Keilwagen

Constructor Summary

SmallStepCondition(double epsilon)
This constructor creates an instance that allows no further iteration in an optimization if the scalar product of the current and the last values of x is smaller than epsilon.

Method Summary

boolean

doNextIteration(int iteration, double f_last, double f_current, double[] gradient, double[] direction, double alpha, Time t) This method allows to decide whether to do another iteration in an optimization or not.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

SmallStepCondition

public SmallStepCondition(double epsilon)

This constructor creates an instance that allows no further iteration in an optimization if the scalar product of the current and the last values of x is smaller than epsilon.

Parameters:

epsilon - the threshold for stopping, has to be non-negative

Method Detail

doNextIteration

public boolean doNextIteration(int iteration,
                               double f_last,
                               double f_current,
                               double[] gradient,
                               double[] direction,
                               double alpha,
                               Time t)

Description copied from interface: TerminationCondition

This method allows to decide whether to do another iteration in an optimization or not.

Specified by:

doNextIteration in interface TerminationCondition

Parameters:

iteration - the number of performed iterations

f_last - last value of the function

f_current - current value of the function

gradient - the gradient of the function

direction - the last direction of the optimization

alpha - the last step size

t - a time object measuring the time that has been elapsed in the optimization

Returns:

true if another iteration should be done