/** {@inheritDoc} * @deprecated As of 3.1. Please use * {@link BaseAbstractMultivariateVectorOptimizer#optimize(int, * org.apache.commons.math3.analysis.MultivariateVectorFunction,OptimizationData[]) * optimize(int,MultivariateDifferentiableVectorFunction,OptimizationData...)} * instead. */ @Override @Deprecated public PointVectorValuePair optimize(int maxEval, final DifferentiableMultivariateVectorFunction f, final double[] target, final double[] weights, final double[] startPoint) { return optimizeInternal(maxEval, FunctionUtils.toMultivariateDifferentiableVectorFunction(f), new Target(target), new Weight(weights), new InitialGuess(startPoint)); }
/** {@inheritDoc} */ @Override protected void setUp() { super.setUp(); // Reset counter. jacobianEvaluations = 0; // Square-root of the weight matrix. weightMatrixSqrt = squareRoot(getWeight()); // Store least squares problem characteristics. // XXX The conversion won't be necessary when the generic argument of // the base class becomes "MultivariateDifferentiableVectorFunction". // XXX "jF" is not strictly necessary anymore but is currently more // efficient than converting the value returned from "getObjectiveFunction()" // every time it is used. jF = FunctionUtils.toMultivariateDifferentiableVectorFunction((DifferentiableMultivariateVectorFunction) getObjectiveFunction()); // Arrays shared with "private" and "protected" methods. point = getStartPoint(); rows = getTarget().length; cols = point.length; }
/** {@inheritDoc} * @deprecated As of 3.1. Please use * {@link BaseAbstractMultivariateVectorOptimizer#optimize(int, * org.apache.commons.math3.analysis.MultivariateVectorFunction,OptimizationData[]) * optimize(int,MultivariateDifferentiableVectorFunction,OptimizationData...)} * instead. */ @Override @Deprecated public PointVectorValuePair optimize(int maxEval, final DifferentiableMultivariateVectorFunction f, final double[] target, final double[] weights, final double[] startPoint) { return optimizeInternal(maxEval, FunctionUtils.toMultivariateDifferentiableVectorFunction(f), new Target(target), new Weight(weights), new InitialGuess(startPoint)); }
/** {@inheritDoc} */ @Override protected void setUp() { super.setUp(); // Reset counter. jacobianEvaluations = 0; // Square-root of the weight matrix. weightMatrixSqrt = squareRoot(getWeight()); // Store least squares problem characteristics. // XXX The conversion won't be necessary when the generic argument of // the base class becomes "MultivariateDifferentiableVectorFunction". // XXX "jF" is not strictly necessary anymore but is currently more // efficient than converting the value returned from "getObjectiveFunction()" // every time it is used. jF = FunctionUtils.toMultivariateDifferentiableVectorFunction((DifferentiableMultivariateVectorFunction) getObjectiveFunction()); // Arrays shared with "private" and "protected" methods. point = getStartPoint(); rows = getTarget().length; cols = point.length; }