| /* |
| * 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.math.optimization.fitting; |
| |
| import org.apache.commons.math.FunctionEvaluationException; |
| import org.apache.commons.math.analysis.polynomials.PolynomialFunction; |
| import org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer; |
| import org.apache.commons.math.optimization.OptimizationException; |
| |
| /** This class implements a curve fitting specialized for polynomials. |
| * <p>Polynomial fitting is a very simple case of curve fitting. The |
| * estimated coefficients are the polynomial coefficients. They are |
| * searched by a least square estimator.</p> |
| * @version $Revision: 1073270 $ $Date: 2011-02-22 10:19:27 +0100 (mar. 22 févr. 2011) $ |
| * @since 2.0 |
| */ |
| |
| public class PolynomialFitter { |
| |
| /** Fitter for the coefficients. */ |
| private final CurveFitter fitter; |
| |
| /** Polynomial degree. */ |
| private final int degree; |
| |
| /** Simple constructor. |
| * <p>The polynomial fitter built this way are complete polynomials, |
| * ie. a n-degree polynomial has n+1 coefficients.</p> |
| * @param degree maximal degree of the polynomial |
| * @param optimizer optimizer to use for the fitting |
| */ |
| public PolynomialFitter(int degree, final DifferentiableMultivariateVectorialOptimizer optimizer) { |
| this.fitter = new CurveFitter(optimizer); |
| this.degree = degree; |
| } |
| |
| /** Add an observed weighted (x,y) point to the sample. |
| * @param weight weight of the observed point in the fit |
| * @param x abscissa of the point |
| * @param y observed value of the point at x, after fitting we should |
| * have P(x) as close as possible to this value |
| */ |
| public void addObservedPoint(double weight, double x, double y) { |
| fitter.addObservedPoint(weight, x, y); |
| } |
| |
| /** |
| * Remove all observations. |
| * @since 2.2 |
| */ |
| public void clearObservations() { |
| fitter.clearObservations(); |
| } |
| |
| /** Get the polynomial fitting the weighted (x, y) points. |
| * @return polynomial function best fitting the observed points |
| * @exception OptimizationException if the algorithm failed to converge |
| */ |
| public PolynomialFunction fit() throws OptimizationException { |
| try { |
| return new PolynomialFunction(fitter.fit(new ParametricPolynomial(), new double[degree + 1])); |
| } catch (FunctionEvaluationException fee) { |
| // should never happen |
| throw new RuntimeException(fee); |
| } |
| } |
| |
| /** Dedicated parametric polynomial class. */ |
| private static class ParametricPolynomial implements ParametricRealFunction { |
| |
| /** {@inheritDoc} */ |
| public double[] gradient(double x, double[] parameters) { |
| final double[] gradient = new double[parameters.length]; |
| double xn = 1.0; |
| for (int i = 0; i < parameters.length; ++i) { |
| gradient[i] = xn; |
| xn *= x; |
| } |
| return gradient; |
| } |
| |
| /** {@inheritDoc} */ |
| public double value(final double x, final double[] parameters) { |
| double y = 0; |
| for (int i = parameters.length - 1; i >= 0; --i) { |
| y = y * x + parameters[i]; |
| } |
| return y; |
| } |
| |
| } |
| |
| } |