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/*
 * 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.optimization.fitting;

import org.apache.commons.math3.analysis.polynomials.PolynomialFunction;
import org.apache.commons.math3.optimization.DifferentiableMultivariateVectorOptimizer;

/**
 * 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).
 *
 * @deprecated As of 3.1 (to be removed in 4.0).
 * @since 2.0
 */
@Deprecated
public class PolynomialFitter extends CurveFitter {
    /** Polynomial degree.
     * @deprecated
     */
    @Deprecated
    private final int degree;

    /**
     * Simple constructor.
     * 

The polynomial fitter built this way are complete polynomials, * ie. a n-degree polynomial has n+1 coefficients.

* * @param degree Maximal degree of the polynomial. * @param optimizer Optimizer to use for the fitting. * @deprecated Since 3.1 (to be removed in 4.0). Please use * {@link #PolynomialFitter(DifferentiableMultivariateVectorOptimizer)} instead. */ @Deprecated public PolynomialFitter(int degree, final DifferentiableMultivariateVectorOptimizer optimizer) { super(optimizer); this.degree = degree; } /** * Simple constructor. * * @param optimizer Optimizer to use for the fitting. * @since 3.1 */ public PolynomialFitter(DifferentiableMultivariateVectorOptimizer optimizer) { super(optimizer); degree = -1; // To avoid compilation error until the instance variable is removed. } /** * Get the polynomial fitting the weighted (x, y) points. * * @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. * @deprecated Since 3.1 (to be removed in 4.0). Please use {@link #fit(double[])} instead. */ @Deprecated public double[] fit() { return fit(new PolynomialFunction.Parametric(), new double[degree + 1]); } /** * 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. * @since 3.1 */ 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. * @since 3.1 */ public double[] fit(double[] guess) { return fit(new PolynomialFunction.Parametric(), guess); } }




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