1 /* 2 * Licensed to the Apache Software Foundation (ASF) under one or more 3 * contributor license agreements. See the NOTICE file distributed with 4 * this work for additional information regarding copyright ownership. 5 * The ASF licenses this file to You under the Apache License, Version 2.0 6 * (the "License"); you may not use this file except in compliance with 7 * the License. You may obtain a copy of the License at 8 * 9 * http://www.apache.org/licenses/LICENSE-2.0 10 * 11 * Unless required by applicable law or agreed to in writing, software 12 * distributed under the License is distributed on an "AS IS" BASIS, 13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 * See the License for the specific language governing permissions and 15 * limitations under the License. 16 */ 17 18 package org.apache.commons.math.optimization.fitting; 19 20 import org.apache.commons.math.FunctionEvaluationException; 21 import org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer; 22 import org.apache.commons.math.optimization.OptimizationException; 23 import org.apache.commons.math.optimization.fitting.CurveFitter; 24 import org.apache.commons.math.optimization.fitting.WeightedObservedPoint; 25 26 /** 27 * Fits points to a Gaussian function (that is, a {@link GaussianFunction}). 28 * <p> 29 * Usage example: 30 * <pre> 31 * GaussianFitter fitter = new GaussianFitter( 32 * new LevenbergMarquardtOptimizer()); 33 * fitter.addObservedPoint(4.0254623, 531026.0); 34 * fitter.addObservedPoint(4.03128248, 984167.0); 35 * fitter.addObservedPoint(4.03839603, 1887233.0); 36 * fitter.addObservedPoint(4.04421621, 2687152.0); 37 * fitter.addObservedPoint(4.05132976, 3461228.0); 38 * fitter.addObservedPoint(4.05326982, 3580526.0); 39 * fitter.addObservedPoint(4.05779662, 3439750.0); 40 * fitter.addObservedPoint(4.0636168, 2877648.0); 41 * fitter.addObservedPoint(4.06943698, 2175960.0); 42 * fitter.addObservedPoint(4.07525716, 1447024.0); 43 * fitter.addObservedPoint(4.08237071, 717104.0); 44 * fitter.addObservedPoint(4.08366408, 620014.0); 45 * GaussianFunction fitFunction = fitter.fit(); 46 * </pre> 47 * 48 * @see ParametricGaussianFunction 49 * @since 2.2 50 * @version $Revision: 1073158 $ $Date: 2011-02-21 22:46:52 +0100 (lun. 21 fvr. 2011) $ 51 */ 52 public class GaussianFitter { 53 54 /** Fitter used for fitting. */ 55 private final CurveFitter fitter; 56 57 /** 58 * Constructs an instance using the specified optimizer. 59 * 60 * @param optimizer optimizer to use for the fitting 61 */ 62 public GaussianFitter(DifferentiableMultivariateVectorialOptimizer optimizer) { 63 fitter = new CurveFitter(optimizer); 64 } 65 66 /** 67 * Adds point (<code>x</code>, <code>y</code>) to list of observed points 68 * with a weight of 1.0. 69 * 70 * @param x <tt>x</tt> point value 71 * @param y <tt>y</tt> point value 72 */ 73 public void addObservedPoint(double x, double y) { 74 addObservedPoint(1.0, x, y); 75 } 76 77 /** 78 * Adds point (<code>x</code>, <code>y</code>) to list of observed points 79 * with a weight of <code>weight</code>. 80 * 81 * @param weight weight assigned to point 82 * @param x <tt>x</tt> point value 83 * @param y <tt>y</tt> point value 84 */ 85 public void addObservedPoint(double weight, double x, double y) { 86 fitter.addObservedPoint(weight, x, y); 87 } 88 89 /** 90 * Fits Gaussian function to the observed points. 91 * 92 * @return Gaussian function best fitting the observed points 93 * 94 * @throws FunctionEvaluationException if <code>CurveFitter.fit</code> throws it 95 * @throws OptimizationException if <code>CurveFitter.fit</code> throws it 96 * @throws IllegalArgumentException if <code>CurveFitter.fit</code> throws it 97 * 98 * @see CurveFitter 99 */ 100 public GaussianFunction fit() throws FunctionEvaluationException, OptimizationException { 101 return new GaussianFunction(fitter.fit(new ParametricGaussianFunction(), 102 createParametersGuesser(fitter.getObservations()).guess())); 103 } 104 105 /** 106 * Factory method to create a <code>GaussianParametersGuesser</code> 107 * instance initialized with the specified observations. 108 * 109 * @param observations points used to initialize the created 110 * <code>GaussianParametersGuesser</code> instance 111 * 112 * @return new <code>GaussianParametersGuesser</code> instance 113 */ 114 protected GaussianParametersGuesser createParametersGuesser(WeightedObservedPoint[] observations) { 115 return new GaussianParametersGuesser(observations); 116 } 117 } 118
