java.lang.Object

org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer

All Implemented Interfaces:: DifferentiableMultivariateVectorialOptimizer

Direct Known Subclasses:: GaussNewtonOptimizer, LevenbergMarquardtOptimizer

public abstract class AbstractLeastSquaresOptimizer extends Object implements DifferentiableMultivariateVectorialOptimizer

Base class for implementing least squares optimizers.

This base class handles the boilerplate methods associated to thresholds settings, jacobian and error estimation.

Since:: 1.2
Version:: $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 févr. 2011) $

Field Summary

Fields

Modifier and Type

Field

Description

protected VectorialConvergenceChecker

checker

Convergence checker.

protected int

cols

Number of columns of the jacobian matrix.

protected double

cost

Cost value (square root of the sum of the residuals).

static final int

DEFAULT_MAX_ITERATIONS

Default maximal number of iterations allowed.

protected double[][]

jacobian

Jacobian matrix.

protected double[]

objective

Current objective function value.

protected double[]

point

Current point.

protected double[]

residuals

Current residuals.

protected double[]

residualsWeights

Weight for the least squares cost computation.

protected int

rows

Number of rows of the jacobian matrix.

protected double[]

targetValues

Target value for the objective functions at optimum.

protected double[][]

wjacobian

Weighted Jacobian

protected double[]

wresiduals

Weighted residuals
Constructor Summary

Constructors

Modifier

Constructor

Description

protected

AbstractLeastSquaresOptimizer()

Simple constructor with default settings.
Method Summary

Modifier and Type

Method

Description

protected abstract VectorialPointValuePair

doOptimize()

Perform the bulk of optimization algorithm.

double

getChiSquare()

Get a Chi-Square-like value assuming the N residuals follow N distinct normal distributions centered on 0 and whose variances are the reciprocal of the weights.

VectorialConvergenceChecker

getConvergenceChecker()

Get the convergence checker.

double[][]

getCovariances()

Get the covariance matrix of optimized parameters.

int

getEvaluations()

Get the number of evaluations of the objective function.

int

getIterations()

Get the number of iterations realized by the algorithm.

int

getJacobianEvaluations()

Get the number of evaluations of the objective function jacobian .

int

getMaxEvaluations()

Get the maximal number of functions evaluations.

int

getMaxIterations()

Get the maximal number of iterations of the algorithm.

double

getRMS()

Get the Root Mean Square value.

double[]

guessParametersErrors()

Guess the errors in optimized parameters.

protected void

incrementIterationsCounter()

Increment the iterations counter by 1.

VectorialPointValuePair

optimize(DifferentiableMultivariateVectorialFunction f, double[] target, double[] weights, double[] startPoint)

Optimizes an objective function.

void

setConvergenceChecker(VectorialConvergenceChecker convergenceChecker)

Set the convergence checker.

void

setMaxEvaluations(int maxEvaluations)

Set the maximal number of functions evaluations.

void

setMaxIterations(int maxIterations)

Set the maximal number of iterations of the algorithm.

protected void

updateJacobian()

Update the jacobian matrix.

protected void

updateResidualsAndCost()

Update the residuals array and cost function value.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details
- DEFAULT_MAX_ITERATIONS
  
  public static final int DEFAULT_MAX_ITERATIONS
  
  Default maximal number of iterations allowed.
  See Also:
  
  Constant Field Values
- checker
  
  protected VectorialConvergenceChecker checker
  
  Convergence checker.
- jacobian
  
  protected double[][] jacobian
  
  Jacobian matrix.
  This matrix is in canonical form just after the calls to updateJacobian(), but may be modified by the solver in the derived class (the Levenberg-Marquardt optimizer does this).
- cols
  
  protected int cols
  
  Number of columns of the jacobian matrix.
- rows
  
  protected int rows
  
  Number of rows of the jacobian matrix.
- targetValues
  
  protected double[] targetValues
  
  Target value for the objective functions at optimum.
  
  Since:
  
  2.1
- residualsWeights
  
  protected double[] residualsWeights
  
  Weight for the least squares cost computation.
  
  Since:
  
  2.1
- point
  
  protected double[] point
  
  Current point.
- objective
  
  protected double[] objective
  
  Current objective function value.
- residuals
  
  protected double[] residuals
  
  Current residuals.
- wjacobian
  
  protected double[][] wjacobian
  
  Weighted Jacobian
- wresiduals
  
  protected double[] wresiduals
  
  Weighted residuals
- cost
  
  protected double cost
  
  Cost value (square root of the sum of the residuals).
Constructor Details
- AbstractLeastSquaresOptimizer
  
  protected AbstractLeastSquaresOptimizer()
  
  Simple constructor with default settings.
  The convergence check is set to a SimpleVectorialValueChecker and the maximal number of evaluation is set to its default value.
Method Details
- setMaxIterations
  
  public void setMaxIterations(int maxIterations)
  
  Set the maximal number of iterations of the algorithm.
  
  Specified by:
  
  setMaxIterations in interface DifferentiableMultivariateVectorialOptimizer
  
  Parameters:
  
  maxIterations - maximal number of function calls .
- getMaxIterations
  
  public int getMaxIterations()
  
  Get the maximal number of iterations of the algorithm.
  
  Specified by:
  
  getMaxIterations in interface DifferentiableMultivariateVectorialOptimizer
  
  Returns:
  
  maximal number of iterations
- getIterations
  
  public int getIterations()
  
  Get the number of iterations realized by the algorithm.
  
  Specified by:
  
  getIterations in interface DifferentiableMultivariateVectorialOptimizer
  
  Returns:
  
  number of iterations
- setMaxEvaluations
  
  public void setMaxEvaluations(int maxEvaluations)
  
  Set the maximal number of functions evaluations.
  
  Specified by:
  
  setMaxEvaluations in interface DifferentiableMultivariateVectorialOptimizer
  
  Parameters:
  
  maxEvaluations - maximal number of function evaluations
- getMaxEvaluations
  
  public int getMaxEvaluations()
  
  Get the maximal number of functions evaluations.
  
  Specified by:
  
  getMaxEvaluations in interface DifferentiableMultivariateVectorialOptimizer
  
  Returns:
  
  maximal number of functions evaluations
- getEvaluations
  
  public int getEvaluations()
  
  Get the number of evaluations of the objective function.
  The number of evaluation correspond to the last call to the optimize method. It is 0 if the method has not been called yet.
  
  Specified by:
  
  getEvaluations in interface DifferentiableMultivariateVectorialOptimizer
  
  Returns:
  
  number of evaluations of the objective function
- getJacobianEvaluations
  
  public int getJacobianEvaluations()
  
  Get the number of evaluations of the objective function jacobian .
  The number of evaluation correspond to the last call to the optimize method. It is 0 if the method has not been called yet.
  
  Specified by:
  
  getJacobianEvaluations in interface DifferentiableMultivariateVectorialOptimizer
  
  Returns:
  
  number of evaluations of the objective function jacobian
- setConvergenceChecker
  
  public void setConvergenceChecker(VectorialConvergenceChecker convergenceChecker)
  
  Set the convergence checker.
  
  Specified by:
  
  setConvergenceChecker in interface DifferentiableMultivariateVectorialOptimizer
  
  Parameters:
  
  convergenceChecker - object to use to check for convergence
- getConvergenceChecker
  
  public VectorialConvergenceChecker getConvergenceChecker()
  
  Get the convergence checker.
  
  Specified by:
  
  getConvergenceChecker in interface DifferentiableMultivariateVectorialOptimizer
  
  Returns:
  
  object used to check for convergence
- incrementIterationsCounter
  
  protected void incrementIterationsCounter() throws OptimizationException
  
  Increment the iterations counter by 1.
  
  Throws:
  
  OptimizationException - if the maximal number of iterations is exceeded
- updateJacobian
  
  protected void updateJacobian() throws FunctionEvaluationException
  
  Update the jacobian matrix.
  
  Throws:
  
  FunctionEvaluationException - if the function jacobian cannot be evaluated or its dimension doesn't match problem dimension
- updateResidualsAndCost
  
  protected void updateResidualsAndCost() throws FunctionEvaluationException
  
  Update the residuals array and cost function value.
  
  Throws:
  
  FunctionEvaluationException - if the function cannot be evaluated or its dimension doesn't match problem dimension or maximal number of of evaluations is exceeded
- getRMS
  
  public double getRMS()
  
  Get the Root Mean Square value. Get the Root Mean Square value, i.e. the root of the arithmetic mean of the square of all weighted residuals. This is related to the criterion that is minimized by the optimizer as follows: if c if the criterion, and n is the number of measurements, then the RMS is sqrt (c/n).
  
  Returns:
  
  RMS value
- getChiSquare
  
  public double getChiSquare()
  
  Get a Chi-Square-like value assuming the N residuals follow N distinct normal distributions centered on 0 and whose variances are the reciprocal of the weights.
  
  Returns:
  
  chi-square value
- getCovariances
  
  public double[][] getCovariances() throws FunctionEvaluationException, OptimizationException
  
  Get the covariance matrix of optimized parameters.
  
  Returns:
  
  covariance matrix
  
  Throws:
  
  FunctionEvaluationException - if the function jacobian cannot be evaluated
  
  OptimizationException - if the covariance matrix cannot be computed (singular problem)
- guessParametersErrors
  
  public double[] guessParametersErrors() throws FunctionEvaluationException, OptimizationException
  
  Guess the errors in optimized parameters.
  Guessing is covariance-based, it only gives rough order of magnitude.
  
  Returns:
  
  errors in optimized parameters
  
  Throws:
  
  FunctionEvaluationException - if the function jacobian cannot b evaluated
  
  OptimizationException - if the covariances matrix cannot be computed or the number of degrees of freedom is not positive (number of measurements lesser or equal to number of parameters)
- optimize
  
  public VectorialPointValuePair optimize(DifferentiableMultivariateVectorialFunction f, double[] target, double[] weights, double[] startPoint) throws FunctionEvaluationException, OptimizationException, IllegalArgumentException
  
  Optimizes an objective function.
  Optimization is considered to be a weighted least-squares minimization. The cost function to be minimized is ∑weight_i(objective_i-target_i)²
  
  Specified by:
  
  optimize in interface DifferentiableMultivariateVectorialOptimizer
  
  Parameters:
  
  f - objective function
  
  target - target value for the objective functions at optimum
  
  weights - weight for the least squares cost computation
  
  startPoint - the start point for optimization
  
  Returns:
  
  the point/value pair giving the optimal value for objective function
  
  Throws:
  
  FunctionEvaluationException - if the objective function throws one during the search
  
  OptimizationException - if the algorithm failed to converge
  
  IllegalArgumentException - if the start point dimension is wrong
- doOptimize
  
  protected abstract VectorialPointValuePair doOptimize() throws FunctionEvaluationException, OptimizationException, IllegalArgumentException
  
  Perform the bulk of optimization algorithm.
  
  Returns:
  
  the point/value pair giving the optimal value for objective function
  
  Throws:
  
  FunctionEvaluationException - if the objective function throws one during the search
  
  OptimizationException - if the algorithm failed to converge
  
  IllegalArgumentException - if the start point dimension is wrong

Class AbstractLeastSquaresOptimizer

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Details

DEFAULT_MAX_ITERATIONS

checker

jacobian

cols

rows

targetValues

residualsWeights

point

objective

residuals

wjacobian

wresiduals

cost

Constructor Details

AbstractLeastSquaresOptimizer

Method Details

setMaxIterations

getMaxIterations

getIterations

setMaxEvaluations

getMaxEvaluations

getEvaluations

getJacobianEvaluations

setConvergenceChecker

getConvergenceChecker

incrementIterationsCounter

updateJacobian

updateResidualsAndCost

getRMS

getChiSquare

getCovariances

guessParametersErrors

optimize

doOptimize