```001/*
002 * Licensed to the Apache Software Foundation (ASF) under one or more
003 * contributor license agreements.  See the NOTICE file distributed with
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 *
010 *
011 * Unless required by applicable law or agreed to in writing, software
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 */
017package org.apache.commons.math3.fitting;
018
019import org.apache.commons.math3.analysis.polynomials.PolynomialFunction;
020import 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 * @since 2.0
030 */
031@Deprecated
032public class PolynomialFitter extends CurveFitter<PolynomialFunction.Parametric> {
033    /**
034     * Simple constructor.
035     *
036     * @param optimizer Optimizer to use for the fitting.
037     */
038    public PolynomialFitter(MultivariateVectorOptimizer optimizer) {
039        super(optimizer);
040    }
041
042    /**
043     * Get the coefficients of the polynomial fitting the weighted data points.
044     * The degree of the fitting polynomial is {@code guess.length - 1}.
045     *
046     * @param guess First guess for the coefficients. They must be sorted in
047     * increasing order of the polynomial's degree.
048     * @param maxEval Maximum number of evaluations of the polynomial.
049     * @return the coefficients of the polynomial that best fits the observed points.
050     * @throws org.apache.commons.math3.exception.TooManyEvaluationsException if
051     * the number of evaluations exceeds {@code maxEval}.
052     * @throws org.apache.commons.math3.exception.ConvergenceException
053     * if the algorithm failed to converge.
054     */
055    public double[] fit(int maxEval, double[] guess) {
056        return fit(maxEval, new PolynomialFunction.Parametric(), guess);
057    }
058
059    /**
060     * Get the coefficients of the polynomial fitting the weighted data points.
061     * The degree of the fitting polynomial is {@code guess.length - 1}.
062     *
063     * @param guess First guess for the coefficients. They must be sorted in
064     * increasing order of the polynomial's degree.
065     * @return the coefficients of the polynomial that best fits the observed points.
066     * @throws org.apache.commons.math3.exception.ConvergenceException
067     * if the algorithm failed to converge.
068     */
069    public double[] fit(double[] guess) {
070        return fit(new PolynomialFunction.Parametric(), guess);
071    }
072}

```