| /* |
| * 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.fitting; |
| |
| import java.util.Random; |
| |
| import org.apache.commons.math4.TestUtils; |
| import org.apache.commons.math4.analysis.ParametricUnivariateFunction; |
| import org.apache.commons.math4.analysis.polynomials.PolynomialFunction; |
| import org.apache.commons.statistics.distribution.ContinuousDistribution; |
| import org.apache.commons.statistics.distribution.UniformContinuousDistribution; |
| import org.apache.commons.math4.fitting.SimpleCurveFitter; |
| import org.apache.commons.math4.fitting.WeightedObservedPoints; |
| import org.apache.commons.rng.simple.RandomSource; |
| import org.junit.Test; |
| |
| /** |
| * Test for class {@link SimpleCurveFitter}. |
| */ |
| public class SimpleCurveFitterTest { |
| @Test |
| public void testPolynomialFit() { |
| final Random randomizer = new Random(53882150042L); |
| final ContinuousDistribution.Sampler rng |
| = new UniformContinuousDistribution(-100, 100).createSampler(RandomSource.create(RandomSource.WELL_512_A, |
| 64925784253L)); |
| |
| 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); |
| } |
| } |