| /* |
| * 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); |
| } |
| } |