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The Apache Commons Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.
/*
* 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);
}
}