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Java example source code file (SimpleCurveFitterTest.java)

This example Java source code file (SimpleCurveFitterTest.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

parametricunivariatefunction, polynomialfunction, random, realdistribution, simplecurvefittertest, uniformrealdistribution, util, weightedobservedpoints

The SimpleCurveFitterTest.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;

import java.util.Random;

import org.apache.commons.math3.TestUtils;
import org.apache.commons.math3.analysis.ParametricUnivariateFunction;
import org.apache.commons.math3.analysis.polynomials.PolynomialFunction;
import org.apache.commons.math3.distribution.RealDistribution;
import org.apache.commons.math3.distribution.UniformRealDistribution;
import org.junit.Test;

/**
 * Test for class {@link SimpleCurveFitter}.
 */
public class SimpleCurveFitterTest {
    @Test
    public void testPolynomialFit() {
        final Random randomizer = new Random(53882150042L);
        final RealDistribution rng = new UniformRealDistribution(-100, 100);
        rng.reseedRandomGenerator(64925784252L);

        final double[] coeff = { 12.9, -3.4, 2.1 }; // 12.9 - 3.4 x + 2.1 x^2
        final PolynomialFunction f = new PolynomialFunction(coeff);

        // Collect data from a known polynomial.
        final WeightedObservedPoints obs = new WeightedObservedPoints();
        for (int i = 0; i < 100; i++) {
            final double x = rng.sample();
            obs.add(x, f.value(x) + 0.1 * randomizer.nextGaussian());
        }

        final ParametricUnivariateFunction function = new PolynomialFunction.Parametric();
        // Start fit from initial guesses that are far from the optimal values.
        final SimpleCurveFitter fitter
            = SimpleCurveFitter.create(function,
                                       new double[] { -1e20, 3e15, -5e25 });
        final double[] best = fitter.fit(obs.toList());

        TestUtils.assertEquals("best != coeff", coeff, best, 2e-2);
    }
}

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