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Java example source code file (StraightLineProblem.java)

This example Java source code file (StraightLineProblem.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

arraylist, deprecated, derivativestructure, model, multivariatedifferentiablevectorfunction, simpleregression, straightlineproblem, univariatedifferentiablefunction, util

The StraightLineProblem.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.optimization.general;

import java.util.ArrayList;

import org.apache.commons.math3.analysis.differentiation.DerivativeStructure;
import org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction;
import org.apache.commons.math3.analysis.differentiation.UnivariateDifferentiableFunction;
import org.apache.commons.math3.stat.regression.SimpleRegression;

/**
 * Class that models a straight line defined as {@code y = a x + b}.
 * The parameters of problem are:
 * <ul>
 *  <li>{@code a}
 *  <li>{@code b}
 * </ul>
 * The model functions are:
 * <ul>
 *  <li>for each pair (a, b), the y-coordinate of the line.
 * </ul>
 */
@Deprecated
class StraightLineProblem implements MultivariateDifferentiableVectorFunction {
    /** Cloud of points assumed to be fitted by a straight line. */
    private final ArrayList<double[]> points;
    /** Error (on the y-coordinate of the points). */
    private final double sigma;

    /**
     * @param error Assumed error for the y-coordinate.
     */
    public StraightLineProblem(double error) {
        points = new ArrayList<double[]>();
        sigma = error;
    }

    public void addPoint(double px, double py) {
        points.add(new double[] { px, py });
    }

    /**
     * @return the list of x-coordinates.
     */
    public double[] x() {
        final double[] v = new double[points.size()];
        for (int i = 0; i < points.size(); i++) {
            final double[] p = points.get(i);
            v[i] = p[0]; // x-coordinate.
        }

        return v;
    }

    /**
     * @return the list of y-coordinates.
     */
    public double[] y() {
        final double[] v = new double[points.size()];
        for (int i = 0; i < points.size(); i++) {
            final double[] p = points.get(i);
            v[i] = p[1]; // y-coordinate.
        }

        return v;
    }

    public double[] target() {
        return y();
    }

    public double[] weight() {
        final double weight = 1 / (sigma * sigma);
        final double[] w = new double[points.size()];
        for (int i = 0; i < points.size(); i++) {
            w[i] = weight;
        }

        return w;
    }

    public double[] value(double[] params) {
        final Model line = new Model(new DerivativeStructure(0, 0, params[0]),
                                     new DerivativeStructure(0, 0, params[1]));

        final double[] model = new double[points.size()];
        for (int i = 0; i < points.size(); i++) {
            final double[] p = points.get(i);
            model[i] = line.value(p[0]);
        }

        return model;
    }

    public DerivativeStructure[] value(DerivativeStructure[] params) {
        final Model line = new Model(params[0], params[1]);

        final DerivativeStructure[] model = new DerivativeStructure[points.size()];
        for (int i = 0; i < points.size(); i++) {
            final DerivativeStructure p0 = params[0].getField().getZero().add(points.get(i)[0]);
            model[i] = line.value(p0);
        }

        return model;
    }

    /**
     * Directly solve the linear problem, using the {@link SimpleRegression}
     * class.
     */
    public double[] solve() {
        final SimpleRegression regress = new SimpleRegression(true);
        for (double[] d : points) {
            regress.addData(d[0], d[1]);
        }

        final double[] result = { regress.getSlope(), regress.getIntercept() };
        return result;
    }

    /**
     * Linear function.
     */
    public static class Model implements UnivariateDifferentiableFunction {
        final DerivativeStructure a;
        final DerivativeStructure b;

        public Model(DerivativeStructure a,
                     DerivativeStructure b) {
            this.a = a;
            this.b = b;
        }

        public double value(double x) {
            return a.getValue() * x + b.getValue();
        }

        public DerivativeStructure value(DerivativeStructure x) {
            return x.multiply(a).add(b);
        }

    }
}

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