public class DefaultUncminOptimizer
extends java.lang.Object
| Constructor and Description |
|---|
DefaultUncminOptimizer() |
DefaultUncminOptimizer(boolean verbose) |
DefaultUncminOptimizer(int messageLevel) |
| Modifier and Type | Method and Description |
|---|---|
void |
addUncminStatusListener(UncminStatusListener listener) |
double |
getFunctionValue() |
double[] |
getGradient() |
double[][] |
getHessian() |
double[] |
getParameters() |
int |
getTerminationCode()
ITRMCD = 0: Optimal solution found
ITRMCD = 1: Terminated with gradientAt small,
xpls is probably optimal
ITRMCD = 2: Terminated with stepsize small,
xpls is probably optimal
ITRMCD = 3: Lower point cannot be found,
xpls is probably optimal
ITRMCD = 4: Iteration limit (150) exceeded
ITRMCD = 5: Too many large steps,
function may be unbounded
|
java.lang.String |
getTerminationMessage() |
void |
minimize(Uncmin_methods minclass,
double[] initialValue)
This wrapper will use the same configuration as Uncmin_f77.optif0_f77.
|
void |
minimize(Uncmin_methods minclass,
double[] initialValue,
boolean analyticGradient,
boolean analyticHessian,
int maxIter,
double maxStep)
Wrapper for calling in Uncmin_f77.optif9_f77.
|
public DefaultUncminOptimizer()
public DefaultUncminOptimizer(int messageLevel)
public DefaultUncminOptimizer(boolean verbose)
public void addUncminStatusListener(UncminStatusListener listener)
public void minimize(Uncmin_methods minclass, double[] initialValue) throws UncminException
minclass - a class that implements Uncmin_methods to provide the value of the objective funciton, gradientAt, and hessian.initialValue - initial value for the prameters. It should be an array of teh same size as the number of parameters.UncminExceptionpublic void minimize(Uncmin_methods minclass, double[] initialValue, boolean analyticGradient, boolean analyticHessian, int maxIter, double maxStep) throws UncminException
minclass - a class that implements Uncmin_methods to provide the value of the objective funciton, gradientAt, and hessian.initialValue - initial value for the prameters. It should be an array of teh same size as the number of parameters.analyticGradient - true if analytic gradientAt is provided in minClass. False otherwise and will compute gradientAt numerically.analyticHessian - true if analytic Hessian is provided in minClass. False otherwise and will compute Hessian numerically.maxIter - maximum number of iterations.UncminExceptionpublic double getFunctionValue()
public double[] getParameters()
public double[] getGradient()
public double[][] getHessian()
public int getTerminationCode()
public java.lang.String getTerminationMessage()