Package org.ddogleg.optimization.wrap

Class QuasiNewtonBFGS_to_UnconstrainedMinimization

java.lang.Object

org.ddogleg.optimization.wrap.QuasiNewtonBFGS_to_UnconstrainedMinimization

All Implemented Interfaces:

Serializable, IterativeOptimization, UnconstrainedMinimization

public class QuasiNewtonBFGS_to_UnconstrainedMinimization
extends Object
implements UnconstrainedMinimization

Wrapper around QuasiNewtonBFGS for UnconstrainedMinimization. For a description of what the line parameters mean see LineSearchMore94.

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
QuasiNewtonBFGS_to_UnconstrainedMinimization(QuasiNewtonBFGS alg)

Method Summary

Modifier and Type	Method	Description
double	getFunctionValue()	Returns the value of the objective function being evaluated at the current parameters value.
double[]	getParameters()	After each iteration this function can be called to get the current best set of parameters.
void	initialize(double[] initial, double ftol, double gtol)	Specify the initial set of parameters from which to start from.
boolean	isConverged()	Indicates if iteration stopped due to convergence or not.
boolean	isUpdated()	True if the parameter(s) being optimized have been updated
boolean	iterate()	Updates the search.
void	setFunction(FunctionNtoS function, FunctionNtoN gradient, double minFunctionValue)	Specifies the function being optimized.
void	setVerbose(@Nullable PrintStream verbose, int level)	If set to a non-null output then extra information will be printed to the specified stream.

Methods inherited from class java.lang.Object

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

Constructor Details

QuasiNewtonBFGS_to_UnconstrainedMinimization

public QuasiNewtonBFGS_to_UnconstrainedMinimization(QuasiNewtonBFGS alg)

Method Details

setFunction

public void setFunction(FunctionNtoS function,
 FunctionNtoN gradient,
 double minFunctionValue)

Description copied from interface: UnconstrainedMinimization

Specifies the function being optimized. A numerical Jacobian will be computed if null is passed in.

Specified by:

setFunction in interface UnconstrainedMinimization

Parameters:

function - Function being optimized.

gradient - Partial derivative for each input in the function. If null a numerical gradient will be computed.

minFunctionValue - Minimum possible value that 'function' can have. E.g. for least squares problems this value should be set to zero.

initialize

public void initialize(double[] initial,
 double ftol,
 double gtol)

Description copied from interface: UnconstrainedMinimization

Specify the initial set of parameters from which to start from. Call after UnconstrainedMinimization.setFunction(org.ddogleg.optimization.functions.FunctionNtoS, org.ddogleg.optimization.functions.FunctionNtoN, double) has been called.

Specified by:

initialize in interface UnconstrainedMinimization

Parameters:

initial - Initial parameters or guess.

ftol - Relative convergence test based on function value. 0 disables test. 0 ≤ ftol < 1, Try 1e-12

gtol - Absolute convergence test based on gradient. 0 disables test. 0 ≤ gtol. Try 1e-12

getParameters

public double[] getParameters()

Description copied from interface: UnconstrainedMinimization

After each iteration this function can be called to get the current best set of parameters.

Specified by:

getParameters in interface UnconstrainedMinimization

iterate

public boolean iterate()
                throws OptimizationException

Description copied from interface: IterativeOptimization

Updates the search. If the search has terminated true is returned. After the search has terminated invoke IterativeOptimization.isConverged() to see if a solution has been converged to or if it stopped for some other reason.

NOTE: The optimization parameters might not be modified after iterate() is called. An internal book keeping step might have been done. To see if parameters have changed call IterativeOptimization.isUpdated().

Specified by:

iterate in interface IterativeOptimization

Returns:

true if it has converged or that no more progress can be made.

Throws:

OptimizationException

isConverged

public boolean isConverged()

Description copied from interface: IterativeOptimization

Indicates if iteration stopped due to convergence or not.

Specified by:

isConverged in interface IterativeOptimization

Returns:

True if iteration stopped because it converged.

setVerbose

public void setVerbose(@Nullable
 @Nullable PrintStream verbose,
 int level)

Description copied from interface: IterativeOptimization

If set to a non-null output then extra information will be printed to the specified stream.

Specified by:

setVerbose in interface IterativeOptimization

Parameters:

verbose - Stream that is printed to. Set to null to disable

level - (Future use) Parameter which can be used to specify level of verbose output. Set to zero for now.

getFunctionValue

public double getFunctionValue()

Description copied from interface: UnconstrainedMinimization

Returns the value of the objective function being evaluated at the current parameters value. If not supported then an exception is thrown.

Specified by:

getFunctionValue in interface UnconstrainedMinimization

Returns:

Objective function's value.

isUpdated

public boolean isUpdated()

Description copied from interface: IterativeOptimization

True if the parameter(s) being optimized have been updated

Specified by:

isUpdated in interface IterativeOptimization

Returns:

True if parameters have been updated