http://git-wip-us.apache.org/repos/asf/commons-math/blob/b4669aad/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateOptimizer.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateOptimizer.java b/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateOptimizer.java deleted file mode 100644 index 8af7c47..0000000 --- a/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateOptimizer.java +++ /dev/null @@ -1,318 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.commons.math4.optimization.direct; - -import org.apache.commons.math4.analysis.MultivariateFunction; -import org.apache.commons.math4.exception.DimensionMismatchException; -import org.apache.commons.math4.exception.MaxCountExceededException; -import org.apache.commons.math4.exception.NumberIsTooLargeException; -import org.apache.commons.math4.exception.NumberIsTooSmallException; -import org.apache.commons.math4.exception.TooManyEvaluationsException; -import org.apache.commons.math4.optimization.BaseMultivariateOptimizer; -import org.apache.commons.math4.optimization.ConvergenceChecker; -import org.apache.commons.math4.optimization.GoalType; -import org.apache.commons.math4.optimization.InitialGuess; -import org.apache.commons.math4.optimization.OptimizationData; -import org.apache.commons.math4.optimization.PointValuePair; -import org.apache.commons.math4.optimization.SimpleBounds; -import org.apache.commons.math4.optimization.SimpleValueChecker; -import org.apache.commons.math4.util.Incrementor; - -/** - * Base class for implementing optimizers for multivariate scalar functions. - * This base class handles the boiler-plate methods associated to thresholds, - * evaluations counting, initial guess and simple bounds settings. - * - * @param <FUNC> Type of the objective function to be optimized. - * - * @deprecated As of 3.1 (to be removed in 4.0). - * @since 2.2 - */ -@Deprecated -public abstract class BaseAbstractMultivariateOptimizer<FUNC extends MultivariateFunction> - implements BaseMultivariateOptimizer<FUNC> { - /** Evaluations counter. */ - protected final Incrementor evaluations = new Incrementor(); - /** Convergence checker. */ - private ConvergenceChecker<PointValuePair> checker; - /** Type of optimization. */ - private GoalType goal; - /** Initial guess. */ - private double[] start; - /** Lower bounds. */ - private double[] lowerBound; - /** Upper bounds. */ - private double[] upperBound; - /** Objective function. */ - private MultivariateFunction function; - - /** - * Simple constructor with default settings. - * The convergence check is set to a {@link SimpleValueChecker}. - * @deprecated See {@link SimpleValueChecker#SimpleValueChecker()} - */ - @Deprecated - protected BaseAbstractMultivariateOptimizer() { - this(new SimpleValueChecker()); - } - /** - * @param checker Convergence checker. - */ - protected BaseAbstractMultivariateOptimizer(ConvergenceChecker<PointValuePair> checker) { - this.checker = checker; - } - - /** {@inheritDoc} */ - public int getMaxEvaluations() { - return evaluations.getMaximalCount(); - } - - /** {@inheritDoc} */ - public int getEvaluations() { - return evaluations.getCount(); - } - - /** {@inheritDoc} */ - public ConvergenceChecker<PointValuePair> getConvergenceChecker() { - return checker; - } - - /** - * Compute the objective function value. - * - * @param point Point at which the objective function must be evaluated. - * @return the objective function value at the specified point. - * @throws TooManyEvaluationsException if the maximal number of - * evaluations is exceeded. - */ - protected double computeObjectiveValue(double[] point) { - try { - evaluations.incrementCount(); - } catch (MaxCountExceededException e) { - throw new TooManyEvaluationsException(e.getMax()); - } - return function.value(point); - } - - /** - * {@inheritDoc} - * - * @deprecated As of 3.1. Please use - * {@link #optimize(int,MultivariateFunction,GoalType,OptimizationData[])} - * instead. - */ - @Deprecated - public PointValuePair optimize(int maxEval, FUNC f, GoalType goalType, - double[] startPoint) { - return optimizeInternal(maxEval, f, goalType, new InitialGuess(startPoint)); - } - - /** - * Optimize an objective function. - * - * @param maxEval Allowed number of evaluations of the objective function. - * @param f Objective function. - * @param goalType Optimization type. - * @param optData Optimization data. The following data will be looked for: - * <ul> - * <li>{@link InitialGuess}</li> - * <li>{@link SimpleBounds}</li> - * </ul> - * @return the point/value pair giving the optimal value of the objective - * function. - * @since 3.1 - */ - public PointValuePair optimize(int maxEval, - FUNC f, - GoalType goalType, - OptimizationData... optData) { - return optimizeInternal(maxEval, f, goalType, optData); - } - - /** - * Optimize an objective function. - * - * @param f Objective function. - * @param goalType Type of optimization goal: either - * {@link GoalType#MAXIMIZE} or {@link GoalType#MINIMIZE}. - * @param startPoint Start point for optimization. - * @param maxEval Maximum number of function evaluations. - * @return the point/value pair giving the optimal value for objective - * function. - * @throws org.apache.commons.math4.exception.DimensionMismatchException - * if the start point dimension is wrong. - * @throws org.apache.commons.math4.exception.TooManyEvaluationsException - * if the maximal number of evaluations is exceeded. - * @throws org.apache.commons.math4.exception.NullArgumentException if - * any argument is {@code null}. - * @deprecated As of 3.1. Please use - * {@link #optimize(int,MultivariateFunction,GoalType,OptimizationData[])} - * instead. - */ - @Deprecated - protected PointValuePair optimizeInternal(int maxEval, FUNC f, GoalType goalType, - double[] startPoint) { - return optimizeInternal(maxEval, f, goalType, new InitialGuess(startPoint)); - } - - /** - * Optimize an objective function. - * - * @param maxEval Allowed number of evaluations of the objective function. - * @param f Objective function. - * @param goalType Optimization type. - * @param optData Optimization data. The following data will be looked for: - * <ul> - * <li>{@link InitialGuess}</li> - * <li>{@link SimpleBounds}</li> - * </ul> - * @return the point/value pair giving the optimal value of the objective - * function. - * @throws TooManyEvaluationsException if the maximal number of - * evaluations is exceeded. - * @since 3.1 - */ - protected PointValuePair optimizeInternal(int maxEval, - FUNC f, - GoalType goalType, - OptimizationData... optData) - throws TooManyEvaluationsException { - // Set internal state. - evaluations.setMaximalCount(maxEval); - evaluations.resetCount(); - function = f; - goal = goalType; - // Retrieve other settings. - parseOptimizationData(optData); - // Check input consistency. - checkParameters(); - // Perform computation. - return doOptimize(); - } - - /** - * Scans the list of (required and optional) optimization data that - * characterize the problem. - * - * @param optData Optimization data. The following data will be looked for: - * <ul> - * <li>{@link InitialGuess}</li> - * <li>{@link SimpleBounds}</li> - * </ul> - */ - private void parseOptimizationData(OptimizationData... optData) { - // The existing values (as set by the previous call) are reused if - // not provided in the argument list. - for (OptimizationData data : optData) { - if (data instanceof InitialGuess) { - start = ((InitialGuess) data).getInitialGuess(); - continue; - } - if (data instanceof SimpleBounds) { - final SimpleBounds bounds = (SimpleBounds) data; - lowerBound = bounds.getLower(); - upperBound = bounds.getUpper(); - continue; - } - } - } - - /** - * @return the optimization type. - */ - public GoalType getGoalType() { - return goal; - } - - /** - * @return the initial guess. - */ - public double[] getStartPoint() { - return start == null ? null : start.clone(); - } - /** - * @return the lower bounds. - * @since 3.1 - */ - public double[] getLowerBound() { - return lowerBound == null ? null : lowerBound.clone(); - } - /** - * @return the upper bounds. - * @since 3.1 - */ - public double[] getUpperBound() { - return upperBound == null ? null : upperBound.clone(); - } - - /** - * Perform the bulk of the optimization algorithm. - * - * @return the point/value pair giving the optimal value of the - * objective function. - */ - protected abstract PointValuePair doOptimize(); - - /** - * Check parameters consistency. - */ - private void checkParameters() { - if (start != null) { - final int dim = start.length; - if (lowerBound != null) { - if (lowerBound.length != dim) { - throw new DimensionMismatchException(lowerBound.length, dim); - } - for (int i = 0; i < dim; i++) { - final double v = start[i]; - final double lo = lowerBound[i]; - if (v < lo) { - throw new NumberIsTooSmallException(v, lo, true); - } - } - } - if (upperBound != null) { - if (upperBound.length != dim) { - throw new DimensionMismatchException(upperBound.length, dim); - } - for (int i = 0; i < dim; i++) { - final double v = start[i]; - final double hi = upperBound[i]; - if (v > hi) { - throw new NumberIsTooLargeException(v, hi, true); - } - } - } - - // If the bounds were not specified, the allowed interval is - // assumed to be [-inf, +inf]. - if (lowerBound == null) { - lowerBound = new double[dim]; - for (int i = 0; i < dim; i++) { - lowerBound[i] = Double.NEGATIVE_INFINITY; - } - } - if (upperBound == null) { - upperBound = new double[dim]; - for (int i = 0; i < dim; i++) { - upperBound[i] = Double.POSITIVE_INFINITY; - } - } - } - } -}
http://git-wip-us.apache.org/repos/asf/commons-math/blob/b4669aad/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateSimpleBoundsOptimizer.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateSimpleBoundsOptimizer.java b/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateSimpleBoundsOptimizer.java deleted file mode 100644 index d179202..0000000 --- a/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateSimpleBoundsOptimizer.java +++ /dev/null @@ -1,82 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.commons.math4.optimization.direct; - -import org.apache.commons.math4.analysis.MultivariateFunction; -import org.apache.commons.math4.optimization.BaseMultivariateOptimizer; -import org.apache.commons.math4.optimization.BaseMultivariateSimpleBoundsOptimizer; -import org.apache.commons.math4.optimization.ConvergenceChecker; -import org.apache.commons.math4.optimization.GoalType; -import org.apache.commons.math4.optimization.InitialGuess; -import org.apache.commons.math4.optimization.PointValuePair; -import org.apache.commons.math4.optimization.SimpleBounds; - -/** - * Base class for implementing optimizers for multivariate scalar functions, - * subject to simple bounds: The valid range of the parameters is an interval. - * The interval can possibly be infinite (in one or both directions). - * This base class handles the boiler-plate methods associated to thresholds - * settings, iterations and evaluations counting. - * - * @param <FUNC> Type of the objective function to be optimized. - * - * @deprecated As of 3.1 (to be removed in 4.0). - * @since 3.0 - * @deprecated As of 3.1 since the {@link BaseAbstractMultivariateOptimizer - * base class} contains similar functionality. - */ -@Deprecated -public abstract class BaseAbstractMultivariateSimpleBoundsOptimizer<FUNC extends MultivariateFunction> - extends BaseAbstractMultivariateOptimizer<FUNC> - implements BaseMultivariateOptimizer<FUNC>, - BaseMultivariateSimpleBoundsOptimizer<FUNC> { - /** - * Simple constructor with default settings. - * The convergence checker is set to a - * {@link org.apache.commons.math4.optimization.SimpleValueChecker}. - * - * @see BaseAbstractMultivariateOptimizer#BaseAbstractMultivariateOptimizer() - * @deprecated See {@link org.apache.commons.math4.optimization.SimpleValueChecker#SimpleValueChecker()} - */ - @Deprecated - protected BaseAbstractMultivariateSimpleBoundsOptimizer() {} - - /** - * @param checker Convergence checker. - */ - protected BaseAbstractMultivariateSimpleBoundsOptimizer(ConvergenceChecker<PointValuePair> checker) { - super(checker); - } - - /** {@inheritDoc} */ - @Override - public PointValuePair optimize(int maxEval, FUNC f, GoalType goalType, - double[] startPoint) { - return super.optimizeInternal(maxEval, f, goalType, - new InitialGuess(startPoint)); - } - - /** {@inheritDoc} */ - public PointValuePair optimize(int maxEval, FUNC f, GoalType goalType, - double[] startPoint, - double[] lower, double[] upper) { - return super.optimizeInternal(maxEval, f, goalType, - new InitialGuess(startPoint), - new SimpleBounds(lower, upper)); - } -} http://git-wip-us.apache.org/repos/asf/commons-math/blob/b4669aad/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateVectorOptimizer.java ---------------------------------------------------------------------- diff --git a/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateVectorOptimizer.java b/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateVectorOptimizer.java deleted file mode 100644 index ccca86e..0000000 --- a/src/main/java/org/apache/commons/math4/optimization/direct/BaseAbstractMultivariateVectorOptimizer.java +++ /dev/null @@ -1,370 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.commons.math4.optimization.direct; - -import org.apache.commons.math4.analysis.MultivariateVectorFunction; -import org.apache.commons.math4.exception.DimensionMismatchException; -import org.apache.commons.math4.exception.MaxCountExceededException; -import org.apache.commons.math4.exception.NullArgumentException; -import org.apache.commons.math4.exception.TooManyEvaluationsException; -import org.apache.commons.math4.linear.RealMatrix; -import org.apache.commons.math4.optimization.BaseMultivariateVectorOptimizer; -import org.apache.commons.math4.optimization.ConvergenceChecker; -import org.apache.commons.math4.optimization.InitialGuess; -import org.apache.commons.math4.optimization.OptimizationData; -import org.apache.commons.math4.optimization.PointVectorValuePair; -import org.apache.commons.math4.optimization.SimpleVectorValueChecker; -import org.apache.commons.math4.optimization.Target; -import org.apache.commons.math4.optimization.Weight; -import org.apache.commons.math4.util.Incrementor; - -/** - * Base class for implementing optimizers for multivariate scalar functions. - * This base class handles the boiler-plate methods associated to thresholds - * settings, iterations and evaluations counting. - * - * @param <FUNC> the type of the objective function to be optimized - * - * @deprecated As of 3.1 (to be removed in 4.0). - * @since 3.0 - */ -@Deprecated -public abstract class BaseAbstractMultivariateVectorOptimizer<FUNC extends MultivariateVectorFunction> - implements BaseMultivariateVectorOptimizer<FUNC> { - /** Evaluations counter. */ - protected final Incrementor evaluations = new Incrementor(); - /** Convergence checker. */ - private ConvergenceChecker<PointVectorValuePair> checker; - /** Target value for the objective functions at optimum. */ - private double[] target; - /** Weight matrix. */ - private RealMatrix weightMatrix; - /** Weight for the least squares cost computation. - * @deprecated - */ - @Deprecated - private double[] weight; - /** Initial guess. */ - private double[] start; - /** Objective function. */ - private FUNC function; - - /** - * Simple constructor with default settings. - * The convergence check is set to a {@link SimpleVectorValueChecker}. - * @deprecated See {@link SimpleVectorValueChecker#SimpleVectorValueChecker()} - */ - @Deprecated - protected BaseAbstractMultivariateVectorOptimizer() { - this(new SimpleVectorValueChecker()); - } - /** - * @param checker Convergence checker. - */ - protected BaseAbstractMultivariateVectorOptimizer(ConvergenceChecker<PointVectorValuePair> checker) { - this.checker = checker; - } - - /** {@inheritDoc} */ - public int getMaxEvaluations() { - return evaluations.getMaximalCount(); - } - - /** {@inheritDoc} */ - public int getEvaluations() { - return evaluations.getCount(); - } - - /** {@inheritDoc} */ - public ConvergenceChecker<PointVectorValuePair> getConvergenceChecker() { - return checker; - } - - /** - * Compute the objective function value. - * - * @param point Point at which the objective function must be evaluated. - * @return the objective function value at the specified point. - * @throws TooManyEvaluationsException if the maximal number of evaluations is - * exceeded. - */ - protected double[] computeObjectiveValue(double[] point) { - try { - evaluations.incrementCount(); - } catch (MaxCountExceededException e) { - throw new TooManyEvaluationsException(e.getMax()); - } - return function.value(point); - } - - /** {@inheritDoc} - * - * @deprecated As of 3.1. Please use - * {@link #optimize(int,MultivariateVectorFunction,OptimizationData[])} - * instead. - */ - @Deprecated - public PointVectorValuePair optimize(int maxEval, FUNC f, double[] t, double[] w, - double[] startPoint) { - return optimizeInternal(maxEval, f, t, w, startPoint); - } - - /** - * Optimize an objective function. - * - * @param maxEval Allowed number of evaluations of the objective function. - * @param f Objective function. - * @param optData Optimization data. The following data will be looked for: - * <ul> - * <li>{@link Target}</li> - * <li>{@link Weight}</li> - * <li>{@link InitialGuess}</li> - * </ul> - * @return the point/value pair giving the optimal value of the objective - * function. - * @throws TooManyEvaluationsException if the maximal number of - * evaluations is exceeded. - * @throws DimensionMismatchException if the initial guess, target, and weight - * arguments have inconsistent dimensions. - * - * @since 3.1 - */ - protected PointVectorValuePair optimize(int maxEval, - FUNC f, - OptimizationData... optData) - throws TooManyEvaluationsException, - DimensionMismatchException { - return optimizeInternal(maxEval, f, optData); - } - - /** - * Optimize an objective function. - * Optimization is considered to be a weighted least-squares minimization. - * The cost function to be minimized is - * <code>∑weight<sub>i</sub>(objective<sub>i</sub> - target<sub>i</sub>)<sup>2</sup></code> - * - * @param f Objective function. - * @param t Target value for the objective functions at optimum. - * @param w Weights for the least squares cost computation. - * @param startPoint Start point for optimization. - * @return the point/value pair giving the optimal value for objective - * function. - * @param maxEval Maximum number of function evaluations. - * @throws org.apache.commons.math4.exception.DimensionMismatchException - * if the start point dimension is wrong. - * @throws org.apache.commons.math4.exception.TooManyEvaluationsException - * if the maximal number of evaluations is exceeded. - * @throws org.apache.commons.math4.exception.NullArgumentException if - * any argument is {@code null}. - * @deprecated As of 3.1. Please use - * {@link #optimizeInternal(int,MultivariateVectorFunction,OptimizationData[])} - * instead. - */ - @Deprecated - protected PointVectorValuePair optimizeInternal(final int maxEval, final FUNC f, - final double[] t, final double[] w, - final double[] startPoint) { - // Checks. - if (f == null) { - throw new NullArgumentException(); - } - if (t == null) { - throw new NullArgumentException(); - } - if (w == null) { - throw new NullArgumentException(); - } - if (startPoint == null) { - throw new NullArgumentException(); - } - if (t.length != w.length) { - throw new DimensionMismatchException(t.length, w.length); - } - - return optimizeInternal(maxEval, f, - new Target(t), - new Weight(w), - new InitialGuess(startPoint)); - } - - /** - * Optimize an objective function. - * - * @param maxEval Allowed number of evaluations of the objective function. - * @param f Objective function. - * @param optData Optimization data. The following data will be looked for: - * <ul> - * <li>{@link Target}</li> - * <li>{@link Weight}</li> - * <li>{@link InitialGuess}</li> - * </ul> - * @return the point/value pair giving the optimal value of the objective - * function. - * @throws TooManyEvaluationsException if the maximal number of - * evaluations is exceeded. - * @throws DimensionMismatchException if the initial guess, target, and weight - * arguments have inconsistent dimensions. - * - * @since 3.1 - */ - protected PointVectorValuePair optimizeInternal(int maxEval, - FUNC f, - OptimizationData... optData) - throws TooManyEvaluationsException, - DimensionMismatchException { - // Set internal state. - evaluations.setMaximalCount(maxEval); - evaluations.resetCount(); - function = f; - // Retrieve other settings. - parseOptimizationData(optData); - // Check input consistency. - checkParameters(); - // Allow subclasses to reset their own internal state. - setUp(); - // Perform computation. - return doOptimize(); - } - - /** - * Gets the initial values of the optimized parameters. - * - * @return the initial guess. - */ - public double[] getStartPoint() { - return start.clone(); - } - - /** - * Gets the weight matrix of the observations. - * - * @return the weight matrix. - * @since 3.1 - */ - public RealMatrix getWeight() { - return weightMatrix.copy(); - } - /** - * Gets the observed values to be matched by the objective vector - * function. - * - * @return the target values. - * @since 3.1 - */ - public double[] getTarget() { - return target.clone(); - } - - /** - * Gets the objective vector function. - * Note that this access bypasses the evaluation counter. - * - * @return the objective vector function. - * @since 3.1 - */ - protected FUNC getObjectiveFunction() { - return function; - } - - /** - * Perform the bulk of the optimization algorithm. - * - * @return the point/value pair giving the optimal value for the - * objective function. - */ - protected abstract PointVectorValuePair doOptimize(); - - /** - * @return a reference to the {@link #target array}. - * @deprecated As of 3.1. - */ - @Deprecated - protected double[] getTargetRef() { - return target; - } - /** - * @return a reference to the {@link #weight array}. - * @deprecated As of 3.1. - */ - @Deprecated - protected double[] getWeightRef() { - return weight; - } - - /** - * Method which a subclass <em>must</em> override whenever its internal - * state depend on the {@link OptimizationData input} parsed by this base - * class. - * It will be called after the parsing step performed in the - * {@link #optimize(int,MultivariateVectorFunction,OptimizationData[]) - * optimize} method and just before {@link #doOptimize()}. - * - * @since 3.1 - */ - protected void setUp() { - // XXX Temporary code until the new internal data is used everywhere. - final int dim = target.length; - weight = new double[dim]; - for (int i = 0; i < dim; i++) { - weight[i] = weightMatrix.getEntry(i, i); - } - } - - /** - * Scans the list of (required and optional) optimization data that - * characterize the problem. - * - * @param optData Optimization data. The following data will be looked for: - * <ul> - * <li>{@link Target}</li> - * <li>{@link Weight}</li> - * <li>{@link InitialGuess}</li> - * </ul> - */ - private void parseOptimizationData(OptimizationData... optData) { - // The existing values (as set by the previous call) are reused if - // not provided in the argument list. - for (OptimizationData data : optData) { - if (data instanceof Target) { - target = ((Target) data).getTarget(); - continue; - } - if (data instanceof Weight) { - weightMatrix = ((Weight) data).getWeight(); - continue; - } - if (data instanceof InitialGuess) { - start = ((InitialGuess) data).getInitialGuess(); - continue; - } - } - } - - /** - * Check parameters consistency. - * - * @throws DimensionMismatchException if {@link #target} and - * {@link #weightMatrix} have inconsistent dimensions. - */ - private void checkParameters() { - if (target.length != weightMatrix.getColumnDimension()) { - throw new DimensionMismatchException(target.length, - weightMatrix.getColumnDimension()); - } - } -}
