Mercurial > hg > de.mpg.mpiwg.itgroup.digilib.plugin
view libs/commons-math-2.1/docs/apidocs/src-html/org/apache/commons/math/optimization/fitting/CurveFitter.html @ 13:cbf34dd4d7e6
commons-math-2.1 added
| author | dwinter |
|---|---|
| date | Tue, 04 Jan 2011 10:02:07 +0100 |
| parents | |
| children |
line wrap: on
line source
<HTML> <BODY BGCOLOR="white"> <PRE> <FONT color="green">001</FONT> /*<a name="line.1"></a> <FONT color="green">002</FONT> * Licensed to the Apache Software Foundation (ASF) under one or more<a name="line.2"></a> <FONT color="green">003</FONT> * contributor license agreements. See the NOTICE file distributed with<a name="line.3"></a> <FONT color="green">004</FONT> * this work for additional information regarding copyright ownership.<a name="line.4"></a> <FONT color="green">005</FONT> * The ASF licenses this file to You under the Apache License, Version 2.0<a name="line.5"></a> <FONT color="green">006</FONT> * (the "License"); you may not use this file except in compliance with<a name="line.6"></a> <FONT color="green">007</FONT> * the License. You may obtain a copy of the License at<a name="line.7"></a> <FONT color="green">008</FONT> *<a name="line.8"></a> <FONT color="green">009</FONT> * http://www.apache.org/licenses/LICENSE-2.0<a name="line.9"></a> <FONT color="green">010</FONT> *<a name="line.10"></a> <FONT color="green">011</FONT> * Unless required by applicable law or agreed to in writing, software<a name="line.11"></a> <FONT color="green">012</FONT> * distributed under the License is distributed on an "AS IS" BASIS,<a name="line.12"></a> <FONT color="green">013</FONT> * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.<a name="line.13"></a> <FONT color="green">014</FONT> * See the License for the specific language governing permissions and<a name="line.14"></a> <FONT color="green">015</FONT> * limitations under the License.<a name="line.15"></a> <FONT color="green">016</FONT> */<a name="line.16"></a> <FONT color="green">017</FONT> <a name="line.17"></a> <FONT color="green">018</FONT> package org.apache.commons.math.optimization.fitting;<a name="line.18"></a> <FONT color="green">019</FONT> <a name="line.19"></a> <FONT color="green">020</FONT> import java.util.ArrayList;<a name="line.20"></a> <FONT color="green">021</FONT> import java.util.List;<a name="line.21"></a> <FONT color="green">022</FONT> <a name="line.22"></a> <FONT color="green">023</FONT> import org.apache.commons.math.FunctionEvaluationException;<a name="line.23"></a> <FONT color="green">024</FONT> import org.apache.commons.math.analysis.DifferentiableMultivariateVectorialFunction;<a name="line.24"></a> <FONT color="green">025</FONT> import org.apache.commons.math.analysis.MultivariateMatrixFunction;<a name="line.25"></a> <FONT color="green">026</FONT> import org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer;<a name="line.26"></a> <FONT color="green">027</FONT> import org.apache.commons.math.optimization.OptimizationException;<a name="line.27"></a> <FONT color="green">028</FONT> import org.apache.commons.math.optimization.VectorialPointValuePair;<a name="line.28"></a> <FONT color="green">029</FONT> <a name="line.29"></a> <FONT color="green">030</FONT> /** Fitter for parametric univariate real functions y = f(x).<a name="line.30"></a> <FONT color="green">031</FONT> * <p>When a univariate real function y = f(x) does depend on some<a name="line.31"></a> <FONT color="green">032</FONT> * unknown parameters p<sub>0</sub>, p<sub>1</sub> ... p<sub>n-1</sub>,<a name="line.32"></a> <FONT color="green">033</FONT> * this class can be used to find these parameters. It does this<a name="line.33"></a> <FONT color="green">034</FONT> * by <em>fitting</em> the curve so it remains very close to a set of<a name="line.34"></a> <FONT color="green">035</FONT> * observed points (x<sub>0</sub>, y<sub>0</sub>), (x<sub>1</sub>,<a name="line.35"></a> <FONT color="green">036</FONT> * y<sub>1</sub>) ... (x<sub>k-1</sub>, y<sub>k-1</sub>). This fitting<a name="line.36"></a> <FONT color="green">037</FONT> * is done by finding the parameters values that minimizes the objective<a name="line.37"></a> <FONT color="green">038</FONT> * function &sum;(y<sub>i</sub>-f(x<sub>i</sub>))<sup>2</sup>. This is<a name="line.38"></a> <FONT color="green">039</FONT> * really a least squares problem.</p><a name="line.39"></a> <FONT color="green">040</FONT> * @version $Revision: 927009 $ $Date: 2010-03-24 07:14:07 -0400 (Wed, 24 Mar 2010) $<a name="line.40"></a> <FONT color="green">041</FONT> * @since 2.0<a name="line.41"></a> <FONT color="green">042</FONT> */<a name="line.42"></a> <FONT color="green">043</FONT> public class CurveFitter {<a name="line.43"></a> <FONT color="green">044</FONT> <a name="line.44"></a> <FONT color="green">045</FONT> /** Optimizer to use for the fitting. */<a name="line.45"></a> <FONT color="green">046</FONT> private final DifferentiableMultivariateVectorialOptimizer optimizer;<a name="line.46"></a> <FONT color="green">047</FONT> <a name="line.47"></a> <FONT color="green">048</FONT> /** Observed points. */<a name="line.48"></a> <FONT color="green">049</FONT> private final List<WeightedObservedPoint> observations;<a name="line.49"></a> <FONT color="green">050</FONT> <a name="line.50"></a> <FONT color="green">051</FONT> /** Simple constructor.<a name="line.51"></a> <FONT color="green">052</FONT> * @param optimizer optimizer to use for the fitting<a name="line.52"></a> <FONT color="green">053</FONT> */<a name="line.53"></a> <FONT color="green">054</FONT> public CurveFitter(final DifferentiableMultivariateVectorialOptimizer optimizer) {<a name="line.54"></a> <FONT color="green">055</FONT> this.optimizer = optimizer;<a name="line.55"></a> <FONT color="green">056</FONT> observations = new ArrayList<WeightedObservedPoint>();<a name="line.56"></a> <FONT color="green">057</FONT> }<a name="line.57"></a> <FONT color="green">058</FONT> <a name="line.58"></a> <FONT color="green">059</FONT> /** Add an observed (x,y) point to the sample with unit weight.<a name="line.59"></a> <FONT color="green">060</FONT> * <p>Calling this method is equivalent to call<a name="line.60"></a> <FONT color="green">061</FONT> * <code>addObservedPoint(1.0, x, y)</code>.</p><a name="line.61"></a> <FONT color="green">062</FONT> * @param x abscissa of the point<a name="line.62"></a> <FONT color="green">063</FONT> * @param y observed value of the point at x, after fitting we should<a name="line.63"></a> <FONT color="green">064</FONT> * have f(x) as close as possible to this value<a name="line.64"></a> <FONT color="green">065</FONT> * @see #addObservedPoint(double, double, double)<a name="line.65"></a> <FONT color="green">066</FONT> * @see #addObservedPoint(WeightedObservedPoint)<a name="line.66"></a> <FONT color="green">067</FONT> * @see #getObservations()<a name="line.67"></a> <FONT color="green">068</FONT> */<a name="line.68"></a> <FONT color="green">069</FONT> public void addObservedPoint(double x, double y) {<a name="line.69"></a> <FONT color="green">070</FONT> addObservedPoint(1.0, x, y);<a name="line.70"></a> <FONT color="green">071</FONT> }<a name="line.71"></a> <FONT color="green">072</FONT> <a name="line.72"></a> <FONT color="green">073</FONT> /** Add an observed weighted (x,y) point to the sample.<a name="line.73"></a> <FONT color="green">074</FONT> * @param weight weight of the observed point in the fit<a name="line.74"></a> <FONT color="green">075</FONT> * @param x abscissa of the point<a name="line.75"></a> <FONT color="green">076</FONT> * @param y observed value of the point at x, after fitting we should<a name="line.76"></a> <FONT color="green">077</FONT> * have f(x) as close as possible to this value<a name="line.77"></a> <FONT color="green">078</FONT> * @see #addObservedPoint(double, double)<a name="line.78"></a> <FONT color="green">079</FONT> * @see #addObservedPoint(WeightedObservedPoint)<a name="line.79"></a> <FONT color="green">080</FONT> * @see #getObservations()<a name="line.80"></a> <FONT color="green">081</FONT> */<a name="line.81"></a> <FONT color="green">082</FONT> public void addObservedPoint(double weight, double x, double y) {<a name="line.82"></a> <FONT color="green">083</FONT> observations.add(new WeightedObservedPoint(weight, x, y));<a name="line.83"></a> <FONT color="green">084</FONT> }<a name="line.84"></a> <FONT color="green">085</FONT> <a name="line.85"></a> <FONT color="green">086</FONT> /** Add an observed weighted (x,y) point to the sample.<a name="line.86"></a> <FONT color="green">087</FONT> * @param observed observed point to add<a name="line.87"></a> <FONT color="green">088</FONT> * @see #addObservedPoint(double, double)<a name="line.88"></a> <FONT color="green">089</FONT> * @see #addObservedPoint(double, double, double)<a name="line.89"></a> <FONT color="green">090</FONT> * @see #getObservations()<a name="line.90"></a> <FONT color="green">091</FONT> */<a name="line.91"></a> <FONT color="green">092</FONT> public void addObservedPoint(WeightedObservedPoint observed) {<a name="line.92"></a> <FONT color="green">093</FONT> observations.add(observed);<a name="line.93"></a> <FONT color="green">094</FONT> }<a name="line.94"></a> <FONT color="green">095</FONT> <a name="line.95"></a> <FONT color="green">096</FONT> /** Get the observed points.<a name="line.96"></a> <FONT color="green">097</FONT> * @return observed points<a name="line.97"></a> <FONT color="green">098</FONT> * @see #addObservedPoint(double, double)<a name="line.98"></a> <FONT color="green">099</FONT> * @see #addObservedPoint(double, double, double)<a name="line.99"></a> <FONT color="green">100</FONT> * @see #addObservedPoint(WeightedObservedPoint)<a name="line.100"></a> <FONT color="green">101</FONT> */<a name="line.101"></a> <FONT color="green">102</FONT> public WeightedObservedPoint[] getObservations() {<a name="line.102"></a> <FONT color="green">103</FONT> return observations.toArray(new WeightedObservedPoint[observations.size()]);<a name="line.103"></a> <FONT color="green">104</FONT> }<a name="line.104"></a> <FONT color="green">105</FONT> <a name="line.105"></a> <FONT color="green">106</FONT> /**<a name="line.106"></a> <FONT color="green">107</FONT> * Remove all observations.<a name="line.107"></a> <FONT color="green">108</FONT> */<a name="line.108"></a> <FONT color="green">109</FONT> public void clearObservations() {<a name="line.109"></a> <FONT color="green">110</FONT> observations.clear();<a name="line.110"></a> <FONT color="green">111</FONT> }<a name="line.111"></a> <FONT color="green">112</FONT> <a name="line.112"></a> <FONT color="green">113</FONT> /** Fit a curve.<a name="line.113"></a> <FONT color="green">114</FONT> * <p>This method compute the coefficients of the curve that best<a name="line.114"></a> <FONT color="green">115</FONT> * fit the sample of observed points previously given through calls<a name="line.115"></a> <FONT color="green">116</FONT> * to the {@link #addObservedPoint(WeightedObservedPoint)<a name="line.116"></a> <FONT color="green">117</FONT> * addObservedPoint} method.</p><a name="line.117"></a> <FONT color="green">118</FONT> * @param f parametric function to fit<a name="line.118"></a> <FONT color="green">119</FONT> * @param initialGuess first guess of the function parameters<a name="line.119"></a> <FONT color="green">120</FONT> * @return fitted parameters<a name="line.120"></a> <FONT color="green">121</FONT> * @exception FunctionEvaluationException if the objective function throws one during<a name="line.121"></a> <FONT color="green">122</FONT> * the search<a name="line.122"></a> <FONT color="green">123</FONT> * @exception OptimizationException if the algorithm failed to converge<a name="line.123"></a> <FONT color="green">124</FONT> * @exception IllegalArgumentException if the start point dimension is wrong<a name="line.124"></a> <FONT color="green">125</FONT> */<a name="line.125"></a> <FONT color="green">126</FONT> public double[] fit(final ParametricRealFunction f,<a name="line.126"></a> <FONT color="green">127</FONT> final double[] initialGuess)<a name="line.127"></a> <FONT color="green">128</FONT> throws FunctionEvaluationException, OptimizationException, IllegalArgumentException {<a name="line.128"></a> <FONT color="green">129</FONT> <a name="line.129"></a> <FONT color="green">130</FONT> // prepare least squares problem<a name="line.130"></a> <FONT color="green">131</FONT> double[] target = new double[observations.size()];<a name="line.131"></a> <FONT color="green">132</FONT> double[] weights = new double[observations.size()];<a name="line.132"></a> <FONT color="green">133</FONT> int i = 0;<a name="line.133"></a> <FONT color="green">134</FONT> for (WeightedObservedPoint point : observations) {<a name="line.134"></a> <FONT color="green">135</FONT> target[i] = point.getY();<a name="line.135"></a> <FONT color="green">136</FONT> weights[i] = point.getWeight();<a name="line.136"></a> <FONT color="green">137</FONT> ++i;<a name="line.137"></a> <FONT color="green">138</FONT> }<a name="line.138"></a> <FONT color="green">139</FONT> <a name="line.139"></a> <FONT color="green">140</FONT> // perform the fit<a name="line.140"></a> <FONT color="green">141</FONT> VectorialPointValuePair optimum =<a name="line.141"></a> <FONT color="green">142</FONT> optimizer.optimize(new TheoreticalValuesFunction(f), target, weights, initialGuess);<a name="line.142"></a> <FONT color="green">143</FONT> <a name="line.143"></a> <FONT color="green">144</FONT> // extract the coefficients<a name="line.144"></a> <FONT color="green">145</FONT> return optimum.getPointRef();<a name="line.145"></a> <FONT color="green">146</FONT> <a name="line.146"></a> <FONT color="green">147</FONT> }<a name="line.147"></a> <FONT color="green">148</FONT> <a name="line.148"></a> <FONT color="green">149</FONT> /** Vectorial function computing function theoretical values. */<a name="line.149"></a> <FONT color="green">150</FONT> private class TheoreticalValuesFunction<a name="line.150"></a> <FONT color="green">151</FONT> implements DifferentiableMultivariateVectorialFunction {<a name="line.151"></a> <FONT color="green">152</FONT> <a name="line.152"></a> <FONT color="green">153</FONT> /** Function to fit. */<a name="line.153"></a> <FONT color="green">154</FONT> private final ParametricRealFunction f;<a name="line.154"></a> <FONT color="green">155</FONT> <a name="line.155"></a> <FONT color="green">156</FONT> /** Simple constructor.<a name="line.156"></a> <FONT color="green">157</FONT> * @param f function to fit.<a name="line.157"></a> <FONT color="green">158</FONT> */<a name="line.158"></a> <FONT color="green">159</FONT> public TheoreticalValuesFunction(final ParametricRealFunction f) {<a name="line.159"></a> <FONT color="green">160</FONT> this.f = f;<a name="line.160"></a> <FONT color="green">161</FONT> }<a name="line.161"></a> <FONT color="green">162</FONT> <a name="line.162"></a> <FONT color="green">163</FONT> /** {@inheritDoc} */<a name="line.163"></a> <FONT color="green">164</FONT> public MultivariateMatrixFunction jacobian() {<a name="line.164"></a> <FONT color="green">165</FONT> return new MultivariateMatrixFunction() {<a name="line.165"></a> <FONT color="green">166</FONT> public double[][] value(double[] point)<a name="line.166"></a> <FONT color="green">167</FONT> throws FunctionEvaluationException, IllegalArgumentException {<a name="line.167"></a> <FONT color="green">168</FONT> <a name="line.168"></a> <FONT color="green">169</FONT> final double[][] jacobian = new double[observations.size()][];<a name="line.169"></a> <FONT color="green">170</FONT> <a name="line.170"></a> <FONT color="green">171</FONT> int i = 0;<a name="line.171"></a> <FONT color="green">172</FONT> for (WeightedObservedPoint observed : observations) {<a name="line.172"></a> <FONT color="green">173</FONT> jacobian[i++] = f.gradient(observed.getX(), point);<a name="line.173"></a> <FONT color="green">174</FONT> }<a name="line.174"></a> <FONT color="green">175</FONT> <a name="line.175"></a> <FONT color="green">176</FONT> return jacobian;<a name="line.176"></a> <FONT color="green">177</FONT> <a name="line.177"></a> <FONT color="green">178</FONT> }<a name="line.178"></a> <FONT color="green">179</FONT> };<a name="line.179"></a> <FONT color="green">180</FONT> }<a name="line.180"></a> <FONT color="green">181</FONT> <a name="line.181"></a> <FONT color="green">182</FONT> /** {@inheritDoc} */<a name="line.182"></a> <FONT color="green">183</FONT> public double[] value(double[] point)<a name="line.183"></a> <FONT color="green">184</FONT> throws FunctionEvaluationException, IllegalArgumentException {<a name="line.184"></a> <FONT color="green">185</FONT> <a name="line.185"></a> <FONT color="green">186</FONT> // compute the residuals<a name="line.186"></a> <FONT color="green">187</FONT> final double[] values = new double[observations.size()];<a name="line.187"></a> <FONT color="green">188</FONT> int i = 0;<a name="line.188"></a> <FONT color="green">189</FONT> for (WeightedObservedPoint observed : observations) {<a name="line.189"></a> <FONT color="green">190</FONT> values[i++] = f.value(observed.getX(), point);<a name="line.190"></a> <FONT color="green">191</FONT> }<a name="line.191"></a> <FONT color="green">192</FONT> <a name="line.192"></a> <FONT color="green">193</FONT> return values;<a name="line.193"></a> <FONT color="green">194</FONT> <a name="line.194"></a> <FONT color="green">195</FONT> }<a name="line.195"></a> <FONT color="green">196</FONT> <a name="line.196"></a> <FONT color="green">197</FONT> }<a name="line.197"></a> <FONT color="green">198</FONT> <a name="line.198"></a> <FONT color="green">199</FONT> }<a name="line.199"></a> </PRE> </BODY> </HTML>