public class QNMinimizer.QNInfo
extends java.lang.Object
| Modifier and Type | Field and Description |
|---|---|
double[] |
d |
QNMinimizer.eScaling |
scaleOpt |
| Constructor and Description |
|---|
QNInfo() |
QNInfo(int size) |
QNInfo(java.util.List<double[]> sList,
java.util.List<double[]> yList) |
| Modifier and Type | Method and Description |
|---|---|
double[] |
applyInitialHessian(double[] x) |
void |
clear() |
void |
free() |
double |
getRho(int ind) |
double[] |
getS(int ind) |
double[] |
getY(int ind) |
void |
setHistory(java.util.List<double[]> sList,
java.util.List<double[]> yList) |
int |
size() |
int |
update(double[] newX,
double[] x,
double[] newGrad,
double[] grad,
double step) |
int |
update(double[] newS,
double[] newY,
double yy,
double sy,
double sg,
double step) |
void |
useDiagonalScaling() |
void |
useScalarScaling() |
public double[] d
public QNMinimizer.eScaling scaleOpt
public QNInfo(int size)
public QNInfo()
public QNInfo(java.util.List<double[]> sList,
java.util.List<double[]> yList)
public int size()
public double getRho(int ind)
public double[] getS(int ind)
public double[] getY(int ind)
public void useDiagonalScaling()
public void useScalarScaling()
public void free()
public void clear()
public void setHistory(java.util.List<double[]> sList,
java.util.List<double[]> yList)
public double[] applyInitialHessian(double[] x)
public int update(double[] newX,
double[] x,
double[] newGrad,
double[] grad,
double step)
throws QNMinimizer.SurpriseConvergence
QNMinimizer.SurpriseConvergencepublic int update(double[] newS,
double[] newY,
double yy,
double sy,
double sg,
double step)