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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.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);
}
}
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