java.lang.Object
- pal.math.MultivariateMinimum
- - pal.math.OrthogonalSearch

```
public class OrthogonalSearch
extends MultivariateMinimum
```
minimization of a real-valued function of several variables without using derivatives, using the simple strategy of optimizing variables one by one.

Author:

Korbinian Strimmer, Matthew Goode

Nested Class Summary

Nested Classes
Modifier and Type Class Description

protected static interface OrthogonalSearch.RoundOptimiser
- Nested classes/interfaces inherited from class pal.math.MultivariateMinimum
  MultivariateMinimum.Factory

Field Summary
- Fields inherited from class pal.math.MultivariateMinimum
  maxFun, numFun, numFuncStops

Constructor Summary

Constructors
Constructor	Description
`OrthogonalSearch()`	Initialization
`OrthogonalSearch(boolean shuffle)`	Initialization
`OrthogonalSearch(OrderEnumerator.OEFactory orderingFactory)`	Initialization

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`protected void`	`debug(java.lang.Object output)`
`static MultivariateMinimum.Factory`	`generateFactory(boolean shuffle)`	Generate a MultivariateMinimum.Factory for an OrthogonalSearch
`protected OrthogonalSearch.RoundOptimiser`	`generateOrthogonalRoundOptimiser(MultivariateFunction mf)`
`protected UnivariateMinimum`	`generateUnivariateMinimum()`
`protected boolean`	`isDebug()`
`protected boolean`	`isFrequentMonitoring()`
`protected boolean`	`isIgnoreNonMinimalUnivariateMinimisations()`	Should we ignore new minisations that are not as minimal as the current one?
`protected boolean`	`isUseCurrentInUnivariateMinimisation()`
`void`	`optimize(MultivariateFunction f, double[] xvec, double tolfx, double tolx)`	The actual optimization routine (needs to be implemented in a subclass of MultivariateMinimum).
`void`	`optimize(MultivariateFunction f, double[] xvec, double tolfx, double tolx, MinimiserMonitor monitor)`	The actual optimization routine It finds a minimum close to vector x when the absolute tolerance for each parameter is specified.
`void`	`setIgnoreNonMinimalUnivariateMinimisations(boolean value)`	Should we ignore new minisations that are not as minimal as the current one?
`void`	`setUseCurrentInUnivariateMinimisation(boolean value)`

Methods inherited from class pal.math.MultivariateMinimum
copy, findMinimum, findMinimum, findMinimum, stopCondition

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

- Constructor Detail
  - OrthogonalSearch
```
public OrthogonalSearch()
```
    Initialization
  - OrthogonalSearch
```
public OrthogonalSearch(boolean shuffle)
```
    Initialization
    
    Parameters:
    
    shuffle - If true uses shuffling, else uses ascending order, when choosing next parameter to optimse (true means equivalent to old StochasticOSearch)
  - OrthogonalSearch
```
public OrthogonalSearch(OrderEnumerator.OEFactory orderingFactory)
```
    Initialization
- Method Detail
  - setUseCurrentInUnivariateMinimisation
```
public void setUseCurrentInUnivariateMinimisation(boolean value)
```
  - setIgnoreNonMinimalUnivariateMinimisations
```
public void setIgnoreNonMinimalUnivariateMinimisations(boolean value)
```
    Should we ignore new minisations that are not as minimal as the current one?
  - optimize
```
public void optimize(MultivariateFunction f,
                     double[] xvec,
                     double tolfx,
                     double tolx)
```
    Description copied from class: MultivariateMinimum
    
    The actual optimization routine (needs to be implemented in a subclass of MultivariateMinimum). It finds a minimum close to vector x when the absolute tolerance for each parameter is specified.
    
    Specified by:
    
    optimize in class MultivariateMinimum
    
    Parameters:
    
    f - multivariate function
    
    xvec - initial guesses for the minimum (contains the location of the minimum on return)
    
    tolfx - absolute tolerance of function value
    
    tolx - absolute tolerance of each parameter
  - optimize
```
public void optimize(MultivariateFunction f,
                     double[] xvec,
                     double tolfx,
                     double tolx,
                     MinimiserMonitor monitor)
```
    Description copied from class: MultivariateMinimum
    
    The actual optimization routine It finds a minimum close to vector x when the absolute tolerance for each parameter is specified.
    
    Overrides:
    
    optimize in class MultivariateMinimum
    
    Parameters:
    
    f - multivariate function
    
    xvec - initial guesses for the minimum (contains the location of the minimum on return)
    
    tolfx - absolute tolerance of function value
    
    tolx - absolute tolerance of each parameter
    
    monitor - A monitor object that receives information about the minimising process (for display purposes)
  - generateFactory
```
public static final MultivariateMinimum.Factory generateFactory(boolean shuffle)
```
    Generate a MultivariateMinimum.Factory for an OrthogonalSearch
    
    Parameters:
    
    shuffle - if true shuffles order for each round (see OrthogonalSearch constructors)
  - generateUnivariateMinimum
```
protected UnivariateMinimum generateUnivariateMinimum()
```
  - isFrequentMonitoring
```
protected boolean isFrequentMonitoring()
```
  - generateOrthogonalRoundOptimiser
```
protected OrthogonalSearch.RoundOptimiser generateOrthogonalRoundOptimiser(MultivariateFunction mf)
```
  - isUseCurrentInUnivariateMinimisation
```
protected final boolean isUseCurrentInUnivariateMinimisation()
```
  - isIgnoreNonMinimalUnivariateMinimisations
```
protected final boolean isIgnoreNonMinimalUnivariateMinimisations()
```
    Should we ignore new minisations that are not as minimal as the current one?
  - debug
```
protected void debug(java.lang.Object output)
```
  - isDebug
```
protected boolean isDebug()
```

Class OrthogonalSearch

Nested Class Summary

Nested classes/interfaces inherited from class pal.math.MultivariateMinimum

Field Summary

Fields inherited from class pal.math.MultivariateMinimum

Constructor Summary

Method Summary

Methods inherited from class pal.math.MultivariateMinimum

Methods inherited from class java.lang.Object

Constructor Detail

OrthogonalSearch

OrthogonalSearch

OrthogonalSearch

Method Detail

setUseCurrentInUnivariateMinimisation

setIgnoreNonMinimalUnivariateMinimisations

optimize

optimize

generateFactory

generateUnivariateMinimum

isFrequentMonitoring

generateOrthogonalRoundOptimiser

isUseCurrentInUnivariateMinimisation

isIgnoreNonMinimalUnivariateMinimisations

debug

isDebug