| /* |
| * 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.Collection; |
| |
| import org.apache.commons.math4.analysis.polynomials.PolynomialFunction; |
| import org.apache.commons.math4.exception.MathInternalError; |
| import org.apache.commons.math4.fitting.leastsquares.LeastSquaresBuilder; |
| import org.apache.commons.math4.fitting.leastsquares.LeastSquaresProblem; |
| import org.apache.commons.math4.linear.DiagonalMatrix; |
| |
| /** |
| * Fits points to a {@link |
| * org.apache.commons.math4.analysis.polynomials.PolynomialFunction.Parametric polynomial} |
| * function. |
| * <br> |
| * The size of the {@link #withStartPoint(double[]) initial guess} array defines the |
| * degree of the polynomial to be fitted. |
| * They must be sorted in increasing order of the polynomial's degree. |
| * The optimal values of the coefficients will be returned in the same order. |
| * |
| * @since 3.3 |
| */ |
| public class PolynomialCurveFitter extends AbstractCurveFitter { |
| /** Parametric function to be fitted. */ |
| private static final PolynomialFunction.Parametric FUNCTION = new PolynomialFunction.Parametric(); |
| /** Initial guess. */ |
| private final double[] initialGuess; |
| /** Maximum number of iterations of the optimization algorithm. */ |
| private final int maxIter; |
| |
| /** |
| * Constructor used by the factory methods. |
| * |
| * @param initialGuess Initial guess. |
| * @param maxIter Maximum number of iterations of the optimization algorithm. |
| * @throws MathInternalError if {@code initialGuess} is {@code null}. |
| */ |
| private PolynomialCurveFitter(double[] initialGuess, |
| int maxIter) { |
| this.initialGuess = initialGuess; |
| this.maxIter = maxIter; |
| } |
| |
| /** |
| * Creates a default curve fitter. |
| * Zero will be used as initial guess for the coefficients, and the maximum |
| * number of iterations of the optimization algorithm is set to |
| * {@link Integer#MAX_VALUE}. |
| * |
| * @param degree Degree of the polynomial to be fitted. |
| * @return a curve fitter. |
| * |
| * @see #withStartPoint(double[]) |
| * @see #withMaxIterations(int) |
| */ |
| public static PolynomialCurveFitter create(int degree) { |
| return new PolynomialCurveFitter(new double[degree + 1], Integer.MAX_VALUE); |
| } |
| |
| /** |
| * Configure the start point (initial guess). |
| * @param newStart new start point (initial guess) |
| * @return a new instance. |
| */ |
| public PolynomialCurveFitter withStartPoint(double[] newStart) { |
| return new PolynomialCurveFitter(newStart.clone(), |
| maxIter); |
| } |
| |
| /** |
| * Configure the maximum number of iterations. |
| * @param newMaxIter maximum number of iterations |
| * @return a new instance. |
| */ |
| public PolynomialCurveFitter withMaxIterations(int newMaxIter) { |
| return new PolynomialCurveFitter(initialGuess, |
| newMaxIter); |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| protected LeastSquaresProblem getProblem(Collection<WeightedObservedPoint> observations) { |
| // Prepare least-squares problem. |
| final int len = observations.size(); |
| final double[] target = new double[len]; |
| final double[] weights = new double[len]; |
| |
| int i = 0; |
| for (WeightedObservedPoint obs : observations) { |
| target[i] = obs.getY(); |
| weights[i] = obs.getWeight(); |
| ++i; |
| } |
| |
| final AbstractCurveFitter.TheoreticalValuesFunction model = |
| new AbstractCurveFitter.TheoreticalValuesFunction(FUNCTION, observations); |
| |
| if (initialGuess == null) { |
| throw new MathInternalError(); |
| } |
| |
| // Return a new least squares problem set up to fit a polynomial curve to the |
| // observed points. |
| return new LeastSquaresBuilder(). |
| maxEvaluations(Integer.MAX_VALUE). |
| maxIterations(maxIter). |
| start(initialGuess). |
| target(target). |
| weight(new DiagonalMatrix(weights)). |
| model(model.getModelFunction(), model.getModelFunctionJacobian()). |
| build(); |
| |
| } |
| |
| } |