Class JacobianMultivariateVectorOptimizer
java.lang.Object
org.apache.commons.math3.optim.BaseOptimizer<PointVectorValuePair>
org.apache.commons.math3.optim.BaseMultivariateOptimizer<PointVectorValuePair>
org.apache.commons.math3.optim.nonlinear.vector.MultivariateVectorOptimizer
org.apache.commons.math3.optim.nonlinear.vector.JacobianMultivariateVectorOptimizer
- Direct Known Subclasses:
AbstractLeastSquaresOptimizer
@Deprecated
public abstract class JacobianMultivariateVectorOptimizer
extends MultivariateVectorOptimizer
Deprecated.
Base class for implementing optimizers for multivariate vector
differentiable functions.
It contains boiler-plate code for dealing with Jacobian evaluation.
It assumes that the rows of the Jacobian matrix iterate on the model
functions while the columns iterate on the parameters; thus, the numbers
of rows is equal to the dimension of the
Target while the
number of columns is equal to the dimension of the
InitialGuess.- Since:
- 3.1
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Field Summary
Fields inherited from class org.apache.commons.math3.optim.BaseOptimizer
evaluations, iterations -
Constructor Summary
ConstructorsModifierConstructorDescriptionprotectedDeprecated. -
Method Summary
Modifier and TypeMethodDescriptionprotected double[][]computeJacobian(double[] params) Deprecated.Computes the Jacobian matrix.optimize(OptimizationData... optData) Deprecated.Stores data and performs the optimization.protected voidparseOptimizationData(OptimizationData... optData) Deprecated.Scans the list of (required and optional) optimization data that characterize the problem.Methods inherited from class org.apache.commons.math3.optim.nonlinear.vector.MultivariateVectorOptimizer
computeObjectiveValue, getTarget, getTargetSize, getWeightMethods inherited from class org.apache.commons.math3.optim.BaseMultivariateOptimizer
getLowerBound, getStartPoint, getUpperBoundMethods inherited from class org.apache.commons.math3.optim.BaseOptimizer
doOptimize, getConvergenceChecker, getEvaluations, getIterations, getMaxEvaluations, getMaxIterations, incrementEvaluationCount, incrementIterationCount, optimize
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Constructor Details
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JacobianMultivariateVectorOptimizer
Deprecated.- Parameters:
checker- Convergence checker.
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Method Details
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computeJacobian
protected double[][] computeJacobian(double[] params) Deprecated.Computes the Jacobian matrix.- Parameters:
params- Point at which the Jacobian must be evaluated.- Returns:
- the Jacobian at the specified point.
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optimize
public PointVectorValuePair optimize(OptimizationData... optData) throws TooManyEvaluationsException, DimensionMismatchException Deprecated.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
BaseOptimizer.parseOptimizationData(OptimizationData[])if they need to register their own options; but then, they must also callsuper.parseOptimizationData(optData)within that method.- Overrides:
optimizein classMultivariateVectorOptimizer- Parameters:
optData- Optimization data. In addition to those documented inMultivariateVectorOptimizer.optimize(OptimizationData...)MultivariateOptimizer}, this method will register the following data:- Returns:
- a point/value pair that satisfies the convergence criteria.
- Throws:
TooManyEvaluationsException- if the maximal number of evaluations is exceeded.DimensionMismatchException- if the initial guess, target, and weight arguments have inconsistent dimensions.
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parseOptimizationData
Deprecated.Scans the list of (required and optional) optimization data that characterize the problem.- Overrides:
parseOptimizationDatain classMultivariateVectorOptimizer- Parameters:
optData- Optimization data. The following data will be looked for:
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org.apache.commons.math3.fitting.leastsquarespackage (cf. MATH-1008).