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Java example source code file (LeastSquaresBuilder.java)

This example Java source code file (LeastSquaresBuilder.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

arrayrealvector, convergencechecker, leastsquaresbuilder, leastsquaresproblem, multivariatejacobianfunction, multivariatematrixfunction, multivariatevectorfunction, parametervalidator, realmatrix, realvector

The LeastSquaresBuilder.java Java example source code

/*
 * 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.math3.fitting.leastsquares;

import org.apache.commons.math3.analysis.MultivariateMatrixFunction;
import org.apache.commons.math3.analysis.MultivariateVectorFunction;
import org.apache.commons.math3.fitting.leastsquares.LeastSquaresProblem.Evaluation;
import org.apache.commons.math3.linear.ArrayRealVector;
import org.apache.commons.math3.linear.RealMatrix;
import org.apache.commons.math3.linear.RealVector;
import org.apache.commons.math3.optim.ConvergenceChecker;
import org.apache.commons.math3.optim.PointVectorValuePair;

/**
 * A mutable builder for {@link LeastSquaresProblem}s.
 *
 * @see LeastSquaresFactory
 * @since 3.3
 */
public class LeastSquaresBuilder {

    /** max evaluations */
    private int maxEvaluations;
    /** max iterations */
    private int maxIterations;
    /** convergence checker */
    private ConvergenceChecker<Evaluation> checker;
    /** model function */
    private MultivariateJacobianFunction model;
    /** observed values */
    private RealVector target;
    /** initial guess */
    private RealVector start;
    /** weight matrix */
    private RealMatrix weight;
    /**
     * Lazy evaluation.
     *
     * @since 3.4
     */
    private boolean lazyEvaluation;
    /** Validator.
     *
     * @since 3.4
     */
    private ParameterValidator paramValidator;


    /**
     * Construct a {@link LeastSquaresProblem} from the data in this builder.
     *
     * @return a new {@link LeastSquaresProblem}.
     */
    public LeastSquaresProblem build() {
        return LeastSquaresFactory.create(model,
                                          target,
                                          start,
                                          weight,
                                          checker,
                                          maxEvaluations,
                                          maxIterations,
                                          lazyEvaluation,
                                          paramValidator);
    }

    /**
     * Configure the max evaluations.
     *
     * @param newMaxEvaluations the maximum number of evaluations permitted.
     * @return this
     */
    public LeastSquaresBuilder maxEvaluations(final int newMaxEvaluations) {
        this.maxEvaluations = newMaxEvaluations;
        return this;
    }

    /**
     * Configure the max iterations.
     *
     * @param newMaxIterations the maximum number of iterations permitted.
     * @return this
     */
    public LeastSquaresBuilder maxIterations(final int newMaxIterations) {
        this.maxIterations = newMaxIterations;
        return this;
    }

    /**
     * Configure the convergence checker.
     *
     * @param newChecker the convergence checker.
     * @return this
     */
    public LeastSquaresBuilder checker(final ConvergenceChecker<Evaluation> newChecker) {
        this.checker = newChecker;
        return this;
    }

    /**
     * Configure the convergence checker.
     * <p/>
     * This function is an overloaded version of {@link #checker(ConvergenceChecker)}.
     *
     * @param newChecker the convergence checker.
     * @return this
     */
    public LeastSquaresBuilder checkerPair(final ConvergenceChecker<PointVectorValuePair> newChecker) {
        return this.checker(LeastSquaresFactory.evaluationChecker(newChecker));
    }

    /**
     * Configure the model function.
     *
     * @param value the model function value
     * @param jacobian the Jacobian of {@code value}
     * @return this
     */
    public LeastSquaresBuilder model(final MultivariateVectorFunction value,
                                     final MultivariateMatrixFunction jacobian) {
        return model(LeastSquaresFactory.model(value, jacobian));
    }

    /**
     * Configure the model function.
     *
     * @param newModel the model function value and Jacobian
     * @return this
     */
    public LeastSquaresBuilder model(final MultivariateJacobianFunction newModel) {
        this.model = newModel;
        return this;
    }

    /**
     * Configure the observed data.
     *
     * @param newTarget the observed data.
     * @return this
     */
    public LeastSquaresBuilder target(final RealVector newTarget) {
        this.target = newTarget;
        return this;
    }

    /**
     * Configure the observed data.
     *
     * @param newTarget the observed data.
     * @return this
     */
    public LeastSquaresBuilder target(final double[] newTarget) {
        return target(new ArrayRealVector(newTarget, false));
    }

    /**
     * Configure the initial guess.
     *
     * @param newStart the initial guess.
     * @return this
     */
    public LeastSquaresBuilder start(final RealVector newStart) {
        this.start = newStart;
        return this;
    }

    /**
     * Configure the initial guess.
     *
     * @param newStart the initial guess.
     * @return this
     */
    public LeastSquaresBuilder start(final double[] newStart) {
        return start(new ArrayRealVector(newStart, false));
    }

    /**
     * Configure the weight matrix.
     *
     * @param newWeight the weight matrix
     * @return this
     */
    public LeastSquaresBuilder weight(final RealMatrix newWeight) {
        this.weight = newWeight;
        return this;
    }

    /**
     * Configure whether evaluation will be lazy or not.
     *
     * @param newValue Whether to perform lazy evaluation.
     * @return this object.
     *
     * @since 3.4
     */
    public LeastSquaresBuilder lazyEvaluation(final boolean newValue) {
        lazyEvaluation = newValue;
        return this;
    }

    /**
     * Configure the validator of the model parameters.
     *
     * @param newValidator Parameter validator.
     * @return this object.
     *
     * @since 3.4
     */
    public LeastSquaresBuilder parameterValidator(final ParameterValidator newValidator) {
        paramValidator = newValidator;
        return this;
    }
}

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