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Diffstat (limited to 'src/main/java/org/apache/commons/math/optimization/fitting/PolynomialFitter.java')
-rw-r--r-- | src/main/java/org/apache/commons/math/optimization/fitting/PolynomialFitter.java | 108 |
1 files changed, 108 insertions, 0 deletions
diff --git a/src/main/java/org/apache/commons/math/optimization/fitting/PolynomialFitter.java b/src/main/java/org/apache/commons/math/optimization/fitting/PolynomialFitter.java new file mode 100644 index 0000000..3e8e62a --- /dev/null +++ b/src/main/java/org/apache/commons/math/optimization/fitting/PolynomialFitter.java @@ -0,0 +1,108 @@ +/* + * 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; + } + + } + +} |