Facemorph
Class Powell

java.lang.Object
  Facemorph.Powell

Direct Known Subclasses:

CAAMPowell, GLGroupwiseImageRegistration, GroupwiseImageRegistration, GroupwiseImageRegistrationLinear, MDL2D

public abstract class Powell
extends java.lang.Object

Implements Powells method, classes should subclass this and implement the func and onIteration methods to use

Field Summary

static double

TINY A very small amount

Constructor Summary

Powell()
Creates a new instance of Powell

Method Summary

abstract double	func(double[] params) Func should be overrided to calculate the error given the parameters params
void	linmin(double[] p, double[] xi, int n, double[] fret) Given an n-dimensional point p[1..n] and an n-dimensional direction xi[1..n], moves and resets p to where the function func(p) takes on a minimum along the direction xi from p, and replaces xi by the actual vector displacement that p was moved.
abstract void	onIteration(double[] params) onIteration is called once per complete itrations to show the best current guess.
void	optimiseGA(double[] p, int samples, double mutationRate, boolean keepBest, int maxIts) Genetic algorith optimisation
void	powell(double[] p, double[][] xi, int n, double ftol, int[] iter, double[] fret, int maxits) Minimization of a function func of n variables.
double	powell(double[] p, double ftol, int[] iter, int maxits) Minimization of a function func of n variables.
void	spsa(double[] p, double a, double c, double A, double alpha, double gamma, double ftol, int maxIts) Implements basic Simultaneous Perturbation Stochastic Approximation (SPSA) algortihm
void	spsa2(double[] p, double a, double c, double A, double alpha, double gamma, double ftol, int maxIts) Implements basic Simultaneous Perturbation Stochastic Approximation (SPSA) algortihm

Methods inherited from class java.lang.Object

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

Field Detail

TINY

public static final double TINY

A very small amount

See Also:

Constant Field Values

Constructor Detail

Powell

public Powell()

Creates a new instance of Powell

Method Detail

func

public abstract double func(double[] params)

Func should be overrided to calculate the error given the parameters params

Parameters:

params - the parameters to evaluate

Returns:

returns the error

onIteration

public abstract void onIteration(double[] params)

onIteration is called once per complete itrations to show the best current guess. It can be implemented with an empty body if not needed

Parameters:

params - the current params of the model

optimiseGA

public void optimiseGA(double[] p,
                       int samples,
                       double mutationRate,
                       boolean keepBest,
                       int maxIts)

Genetic algorith optimisation

Parameters:

p - the initial start point (mutated and bred with itself to form the initial population

samples - number of samples in each generation

mutationRate - mutation rate as fraction

keepBest - keep the optimal from each generation, or not

maxIts - maximum number of iterations

powell

public double powell(double[] p,
                     double ftol,
                     int[] iter,
                     int maxits)
              throws PowellException

Minimization of a function func of n variables. Input consists of an initial starting point p[1..n]; an initial matrix xi[1..n][1..n] is generated initial set of directions(the n unit vectors); and ftol, the fractional tolerance in the function value such that failure to decrease by more than this amount on one iteration signals doneness. On output, p is set to the best point found, xi is the then-current direction set, fret is the returned function value at p, and iter is the number of iterations taken. The routine linmin is used.

Parameters:

p - starting point

iter - number of iterations taken

ftol - the fractional tolerance in the function value

maxits - maximum number of iterations permitted

Returns:

the function evaluated at the final point

Throws:

PowellException - if something goes wrong e.g. max iterations exceeded

powell

public void powell(double[] p,
                   double[][] xi,
                   int n,
                   double ftol,
                   int[] iter,
                   double[] fret,
                   int maxits)
            throws PowellException

Minimization of a function func of n variables. Input consists of an initial starting point p[1..n]; an initial matrix xi[1..n][1..n], whose columns contain the initial set of directions(usually the n unit vectors); and ftol, the fractional tolerance in the function value such that failure to decrease by more than this amount on one iteration signals doneness. On output, p is set to the best point found, xi is the then-current direction set, fret is the returned function value at p, and iter is the number of iterations taken. The routine linmin is used.

Parameters:

p - starting point

n - size of vectors

xi - initial direction set

fret - returned function value at final point

iter - number of iterations taken

ftol - the fractional tolerance in the function value

maxits - maximum number of iterations permitted

Throws:

PowellException - if something goes wrong e.g. max iterations exceeded

spsa

public void spsa(double[] p,
                 double a,
                 double c,
                 double A,
                 double alpha,
                 double gamma,
                 double ftol,
                 int maxIts)

Implements basic Simultaneous Perturbation Stochastic Approximation (SPSA) algortihm

Parameters:

p - the initial guess, will also contain the output estimate

a -

c -

A -

alpha -

gamma -

ftol - termination parameter

maxIts - number of iterations to compute (should be replaced with termination condition)

spsa2

public void spsa2(double[] p,
                  double a,
                  double c,
                  double A,
                  double alpha,
                  double gamma,
                  double ftol,
                  int maxIts)

Implements basic Simultaneous Perturbation Stochastic Approximation (SPSA) algortihm

Parameters:

p - the initial guess, will also contain the output estimate

a -

c -

A -

alpha -

gamma -

ftol - related to the termination condition, change in error should be below this

maxIts - number of iterations to compute (should be replaced with termination condition)

linmin

public void linmin(double[] p,
                   double[] xi,
                   int n,
                   double[] fret)
            throws PowellException

Given an n-dimensional point p[1..n] and an n-dimensional direction xi[1..n], moves and resets p to where the function func(p) takes on a minimum along the direction xi from p, and replaces xi by the actual vector displacement that p was moved. Also returns as fret the value of func at the returned location p. This is actually all accomplished by calling the routines mnbrak and brent.

Parameters:

p - an n-dimensional point, used for output

xi - an n-dimensional direction

n - the dimensions of the search space

fret - returns the value of func at the returned location p

Throws:

PowellException - if there is a problem