cct.math
Class LinearSearch

java.lang.Object
  cct.math.LinearSearch

public class LinearSearch
extends java.lang.Object

Title:

Description:

Adapted from the Numerical Recipes in C

Copyright: Copyright (c) 2006

Company: ANU

Field Summary

(package private) double	ALF
(package private) boolean	debug
(package private) float	fMin
(package private) double	TOLX

Constructor Summary

LinearSearch()

Method Summary

float	getFMin()
boolean	lnsrch(int n, float[] xold, float fold, float[] g, float[] p, float[] x, float stpmax, MinimizedFunctionInterface func) Given an n-dimensional point xold[1..n], the value of the function and gradient there, fold and g[1..n], and a direction p[1..n], finds a new point x[1..n] along the direction p from xold where the function func has decreased “sufficiently.” The new function value is returned in f.
static void	main(java.lang.String[] args)

Methods inherited from class java.lang.Object

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

Field Detail

ALF

double ALF

TOLX

double TOLX

fMin

float fMin

debug

boolean debug

Constructor Detail

LinearSearch

public LinearSearch()

Method Detail

lnsrch

public boolean lnsrch(int n,
                      float[] xold,
                      float fold,
                      float[] g,
                      float[] p,
                      float[] x,
                      float stpmax,
                      MinimizedFunctionInterface func)

Given an n-dimensional point xold[1..n], the value of the function and gradient there, fold and g[1..n], and a direction p[1..n], finds a new point x[1..n] along the direction p from xold where the function func has decreased “sufficiently.” The new function value is returned in f. stpmax is an input quantity that limits the length of the steps so that you do not try to evaluate the function in regions where it is undefined or subject to overflow. p is usually the Newton direction. The output quantity check is false (0) on a normal exit. It is true (1) when x is too close to xold. In a minimization algorithm, this usually signals convergence and can be ignored. However, in a zero-finding algorithm the calling program should check whether the convergence is spurious. Some “difficult” problems may require double precision in this routine.

Type Parameters:

any - float

Parameters:

n - int

xold - float[]

fold - float

g - float[]

p - float[]

x - float[]

getFMin

public float getFMin()

main

public static void main(java.lang.String[] args)