    001    /*
    002     * Licensed to the Apache Software Foundation (ASF) under one or more
    003     * contributor license agreements.  See the NOTICE file distributed with
    004     * this work for additional information regarding copyright ownership.
    005     * The ASF licenses this file to You under the Apache License, Version 2.0
    006     * (the "License"); you may not use this file except in compliance with
    007     * the License.  You may obtain a copy of the License at
    008     *
    009     *      http://www.apache.org/licenses/LICENSE-2.0
    010     *
    011     * Unless required by applicable law or agreed to in writing, software
    012     * distributed under the License is distributed on an "AS IS" BASIS,
    013     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    014     * See the License for the specific language governing permissions and
    015     * limitations under the License.
    016     */
    017    package org.apache.commons.math3.fitting;
    018
    019    import org.apache.commons.math3.analysis.polynomials.PolynomialFunction;
    020    import org.apache.commons.math3.optim.nonlinear.vector.MultivariateVectorOptimizer;
    021
    022    /**
    023     * Polynomial fitting is a very simple case of {@link CurveFitter curve fitting}.
    024     * The estimated coefficients are the polynomial coefficients (see the
    025     * {@link #fit(double[]) fit} method).
    026     *
    027     * @version $Id: PolynomialFitter.java 1416643 2012-12-03 19:37:14Z tn $
    028     * @since 2.0
    029     */
    030    public class PolynomialFitter extends CurveFitter<PolynomialFunction.Parametric> {
    031        /**
    032         * Simple constructor.
    033         *
    034         * @param optimizer Optimizer to use for the fitting.
    035         */
    036        public PolynomialFitter(MultivariateVectorOptimizer optimizer) {
    037            super(optimizer);
    038        }
    039
    040        /**
    041         * Get the coefficients of the polynomial fitting the weighted data points.
    042         * The degree of the fitting polynomial is {@code guess.length - 1}.
    043         *
    044         * @param guess First guess for the coefficients. They must be sorted in
    045         * increasing order of the polynomial's degree.
    046         * @param maxEval Maximum number of evaluations of the polynomial.
    047         * @return the coefficients of the polynomial that best fits the observed points.
    048         * @throws org.apache.commons.math3.exception.TooManyEvaluationsException if
    049         * the number of evaluations exceeds {@code maxEval}.
    050         * @throws org.apache.commons.math3.exception.ConvergenceException
    051         * if the algorithm failed to converge.
    052         */
    053        public double[] fit(int maxEval, double[] guess) {
    054            return fit(maxEval, new PolynomialFunction.Parametric(), guess);
    055        }
    056
    057        /**
    058         * Get the coefficients of the polynomial fitting the weighted data points.
    059         * The degree of the fitting polynomial is {@code guess.length - 1}.
    060         *
    061         * @param guess First guess for the coefficients. They must be sorted in
    062         * increasing order of the polynomial's degree.
    063         * @return the coefficients of the polynomial that best fits the observed points.
    064         * @throws org.apache.commons.math3.exception.ConvergenceException
    065         * if the algorithm failed to converge.
    066         */
    067        public double[] fit(double[] guess) {
    068            return fit(new PolynomialFunction.Parametric(), guess);
    069        }
    070    }