/* * 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 org.apache.commons.math3.analysis.polynomials.PolynomialFunction; import org.apache.commons.math3.optim.nonlinear.vector.MultivariateVectorOptimizer; /** * Polynomial fitting is a very simple case of {@link CurveFitter curve fitting}. * The estimated coefficients are the polynomial coefficients (see the * {@link #fit(double[]) fit} method). * * @since 2.0 * @deprecated As of 3.3. Please use {@link PolynomialCurveFitter} and * {@link WeightedObservedPoints} instead. */ @Deprecated public class PolynomialFitter extends CurveFitter<PolynomialFunction.Parametric> { /** * Simple constructor. * * @param optimizer Optimizer to use for the fitting. */ public PolynomialFitter(MultivariateVectorOptimizer optimizer) { super(optimizer); } /** * Get the coefficients of the polynomial fitting the weighted data points. * The degree of the fitting polynomial is {@code guess.length - 1}. * * @param guess First guess for the coefficients. They must be sorted in * increasing order of the polynomial's degree. * @param maxEval Maximum number of evaluations of the polynomial. * @return the coefficients of the polynomial that best fits the observed points. * @throws org.apache.commons.math3.exception.TooManyEvaluationsException if * the number of evaluations exceeds {@code maxEval}. * @throws org.apache.commons.math3.exception.ConvergenceException * if the algorithm failed to converge. */ public double[] fit(int maxEval, double[] guess) { return fit(maxEval, new PolynomialFunction.Parametric(), guess); } /** * Get the coefficients of the polynomial fitting the weighted data points. * The degree of the fitting polynomial is {@code guess.length - 1}. * * @param guess First guess for the coefficients. They must be sorted in * increasing order of the polynomial's degree. * @return the coefficients of the polynomial that best fits the observed points. * @throws org.apache.commons.math3.exception.ConvergenceException * if the algorithm failed to converge. */ public double[] fit(double[] guess) { return fit(new PolynomialFunction.Parametric(), guess); } }