Apache Commons Math 3.6.1 · org.apache.commons.math3.optim.nonlinear.vector.MultivariateVectorOptimizer

Modifier and Type	Field and Description
private MultivariateVectorFunction	model Model function.
private double[]	target Target values for the model function at optimum.
private RealMatrix	weightMatrix Weight matrix.

Access	Constructor and Description
protected	MultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> Convergence checker. checker)

Method Summary

Modifier and Type	Method and Description
private void	checkParameters() Hides org.apache.commons.math3.optim.BaseMultivariateOptimizer.checkParameters. Check parameters consistency.
protected double[]	Returns: the objective function value at the specified point. computeObjectiveValue(double[] Point at which the objective function must be evaluated. params) Computes the objective function value.
public double[]	Returns: the target values. getTarget() Gets the observed values to be matched by the objective vector function.
public int	Returns: the length of the target vector. getTargetSize() Gets the number of observed values.
public RealMatrix	Returns: the weight matrix. getWeight() Gets the weight matrix of the observations.
public PointVectorValuePair	Returns: a point/value pair that satisfies the convergence criteria. optimize(OptimizationData... Optimization data. In addition to those documented in `BaseMultivariateOptimizer`, this method will register the following data: `Target` `Weight` `ModelFunction` optData) Overrides org.apache.commons.math3.optim.BaseMultivariateOptimizer.optimize. Stores data and performs the optimization.
protected void	parseOptimizationData(OptimizationData... Optimization data. The following data will be looked for: `Target` `Weight` `ModelFunction` optData) Overrides org.apache.commons.math3.optim.BaseMultivariateOptimizer.parseOptimizationData. Scans the list of (required and optional) optimization data that characterize the problem.

Inherited from org.apache.commons.math3.optim.BaseMultivariateOptimizer:: getLowerBound getStartPoint getUpperBound

model	back to summary
private MultivariateVectorFunction model Model function.

target	back to summary
private double[] target Target values for the model function at optimum.

weightMatrix	back to summary
private RealMatrix weightMatrix Weight matrix.

MultivariateVectorOptimizer	back to summary
protected MultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker) Parameters checker:ConvergenceChecker<PointVectorValuePair> Convergence checker.

Method Detail

checkParameters back to summary

checkParameters	back to summary
private void checkParameters() Hides org.apache.commons.math3.optim.BaseMultivariateOptimizer.checkParameters. Check parameters consistency. Exceptions DimensionMismatchException: if `target` and `weightMatrix` have inconsistent dimensions.

private void checkParameters()

Hides org.apache.commons.math3.optim.BaseMultivariateOptimizer.checkParameters.

Check parameters consistency.

Exceptions

DimensionMismatchException:: if target and weightMatrix have inconsistent dimensions.

computeObjectiveValue	back to summary
protected double[] computeObjectiveValue(double[] params) Computes the objective function value. This method must be called by subclasses to enforce the evaluation counter limit. Parameters params:double[] Point at which the objective function must be evaluated. Returns:double[] the objective function value at the specified point. Exceptions TooManyEvaluationsException: if the maximal number of evaluations (of the model vector function) is exceeded.

computeObjectiveValue

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protected double[] computeObjectiveValue(double[] params)

Computes the objective function value. This method must be called by subclasses to enforce the evaluation counter limit.

Parameters

params:double[]: Point at which the objective function must be evaluated.

Returns:double[]

the objective function value at the specified point.

Exceptions

TooManyEvaluationsException:: if the maximal number of evaluations (of the model vector function) is exceeded.

getTarget	back to summary
public double[] getTarget() Gets the observed values to be matched by the objective vector function. Returns:double[] the target values.

getTarget

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public double[] getTarget()

Gets the observed values to be matched by the objective vector function.

Returns:double[]: the target values.

getTargetSize	back to summary
public int getTargetSize() Gets the number of observed values. Returns:int the length of the target vector.

getTargetSize

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public int getTargetSize()

Gets the number of observed values.

Returns:int: the length of the target vector.

getWeight	back to summary
public RealMatrix getWeight() Gets the weight matrix of the observations. Returns:RealMatrix the weight matrix.

getWeight

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public RealMatrix getWeight()

Gets the weight matrix of the observations.

Returns:RealMatrix: the weight matrix.

optimize back to summary

optimize	back to summary
public PointVectorValuePair optimize(OptimizationData... optData) throws TooManyEvaluationsException, DimensionMismatchException Overrides org.apache.commons.math3.optim.BaseMultivariateOptimizer.optimize. Doc from org.apache.commons.math3.optim.BaseMultivariateOptimizer.optimize. Stores data and performs the optimization. The list of parameters is open-ended so that sub-classes can extend it with arguments specific to their concrete implementations. When the method is called multiple times, instance data is overwritten only when actually present in the list of arguments: when not specified, data set in a previous call is retained (and thus is optional in subsequent calls). Important Note Subclasses must override `parseOptimizationData(OptimizationData[])` if they need to register their own options; but then, they must also call `super.parseOptimizationData(optData)` within that method. Parameters optData:OptimizationData[] Optimization data. In addition to those documented in `BaseMultivariateOptimizer`, this method will register the following data: `Target` `Weight` `ModelFunction` Returns:PointVectorValuePair a point/value pair that satisfies the convergence criteria. Annotations @Override Exceptions TooManyEvaluationsException: if the maximal number of evaluations is exceeded. DimensionMismatchException: if the initial guess, target, and weight arguments have inconsistent dimensions.

public PointVectorValuePair optimize(OptimizationData... optData) throws TooManyEvaluationsException, DimensionMismatchException

Overrides org.apache.commons.math3.optim.BaseMultivariateOptimizer.optimize.

Doc from org.apache.commons.math3.optim.BaseMultivariateOptimizer.optimize.

Stores data and performs the optimization.

The list of parameters is open-ended so that sub-classes can extend it with arguments specific to their concrete implementations.

When the method is called multiple times, instance data is overwritten only when actually present in the list of arguments: when not specified, data set in a previous call is retained (and thus is optional in subsequent calls).

Important Note

Subclasses must override parseOptimizationData(OptimizationData[]) if they need to register their own options; but then, they must also call super.parseOptimizationData(optData) within that method.

Parameters

optData:OptimizationData[]

Optimization data. In addition to those documented in BaseMultivariateOptimizer, this method will register the following data:

Returns:PointVectorValuePair

a point/value pair that satisfies the convergence criteria.

Annotations

@Override

Exceptions

TooManyEvaluationsException:: if the maximal number of evaluations is exceeded.
DimensionMismatchException:: if the initial guess, target, and weight arguments have inconsistent dimensions.

parseOptimizationData back to summary

parseOptimizationData	back to summary
protected void parseOptimizationData(OptimizationData... optData) Overrides org.apache.commons.math3.optim.BaseMultivariateOptimizer.parseOptimizationData. Scans the list of (required and optional) optimization data that characterize the problem. Parameters optData:OptimizationData[] Optimization data. The following data will be looked for: `Target` `Weight` `ModelFunction` Annotations @Override

protected void parseOptimizationData(OptimizationData... optData)

Overrides org.apache.commons.math3.optim.BaseMultivariateOptimizer.parseOptimizationData.

Scans the list of (required and optional) optimization data that characterize the problem.

Parameters

optData:OptimizationData[]

Optimization data. The following data will be looked for:

Annotations

@Override

public abstract Class MultivariateVectorOptimizer

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