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| date | Tue, 04 Jan 2011 10:02:07 +0100 |
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<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.ode.nonstiff;<a name="line.18"></a> <FONT color="green">019</FONT> <a name="line.19"></a> <FONT color="green">020</FONT> import org.apache.commons.math.linear.Array2DRowRealMatrix;<a name="line.20"></a> <FONT color="green">021</FONT> import org.apache.commons.math.ode.DerivativeException;<a name="line.21"></a> <FONT color="green">022</FONT> import org.apache.commons.math.ode.FirstOrderDifferentialEquations;<a name="line.22"></a> <FONT color="green">023</FONT> import org.apache.commons.math.ode.IntegratorException;<a name="line.23"></a> <FONT color="green">024</FONT> import org.apache.commons.math.ode.events.CombinedEventsManager;<a name="line.24"></a> <FONT color="green">025</FONT> import org.apache.commons.math.ode.sampling.NordsieckStepInterpolator;<a name="line.25"></a> <FONT color="green">026</FONT> import org.apache.commons.math.ode.sampling.StepHandler;<a name="line.26"></a> <FONT color="green">027</FONT> <a name="line.27"></a> <FONT color="green">028</FONT> <a name="line.28"></a> <FONT color="green">029</FONT> /**<a name="line.29"></a> <FONT color="green">030</FONT> * This class implements explicit Adams-Bashforth integrators for Ordinary<a name="line.30"></a> <FONT color="green">031</FONT> * Differential Equations.<a name="line.31"></a> <FONT color="green">032</FONT> *<a name="line.32"></a> <FONT color="green">033</FONT> * <p>Adams-Bashforth methods (in fact due to Adams alone) are explicit<a name="line.33"></a> <FONT color="green">034</FONT> * multistep ODE solvers. This implementation is a variation of the classical<a name="line.34"></a> <FONT color="green">035</FONT> * one: it uses adaptive stepsize to implement error control, whereas<a name="line.35"></a> <FONT color="green">036</FONT> * classical implementations are fixed step size. The value of state vector<a name="line.36"></a> <FONT color="green">037</FONT> * at step n+1 is a simple combination of the value at step n and of the<a name="line.37"></a> <FONT color="green">038</FONT> * derivatives at steps n, n-1, n-2 ... Depending on the number k of previous<a name="line.38"></a> <FONT color="green">039</FONT> * steps one wants to use for computing the next value, different formulas<a name="line.39"></a> <FONT color="green">040</FONT> * are available:</p><a name="line.40"></a> <FONT color="green">041</FONT> * <ul><a name="line.41"></a> <FONT color="green">042</FONT> * <li>k = 1: y<sub>n+1</sub> = y<sub>n</sub> + h y'<sub>n</sub></li><a name="line.42"></a> <FONT color="green">043</FONT> * <li>k = 2: y<sub>n+1</sub> = y<sub>n</sub> + h (3y'<sub>n</sub>-y'<sub>n-1</sub>)/2</li><a name="line.43"></a> <FONT color="green">044</FONT> * <li>k = 3: y<sub>n+1</sub> = y<sub>n</sub> + h (23y'<sub>n</sub>-16y'<sub>n-1</sub>+5y'<sub>n-2</sub>)/12</li><a name="line.44"></a> <FONT color="green">045</FONT> * <li>k = 4: y<sub>n+1</sub> = y<sub>n</sub> + h (55y'<sub>n</sub>-59y'<sub>n-1</sub>+37y'<sub>n-2</sub>-9y'<sub>n-3</sub>)/24</li><a name="line.45"></a> <FONT color="green">046</FONT> * <li>...</li><a name="line.46"></a> <FONT color="green">047</FONT> * </ul><a name="line.47"></a> <FONT color="green">048</FONT> *<a name="line.48"></a> <FONT color="green">049</FONT> * <p>A k-steps Adams-Bashforth method is of order k.</p><a name="line.49"></a> <FONT color="green">050</FONT> *<a name="line.50"></a> <FONT color="green">051</FONT> * <h3>Implementation details</h3><a name="line.51"></a> <FONT color="green">052</FONT> *<a name="line.52"></a> <FONT color="green">053</FONT> * <p>We define scaled derivatives s<sub>i</sub>(n) at step n as:<a name="line.53"></a> <FONT color="green">054</FONT> * <pre><a name="line.54"></a> <FONT color="green">055</FONT> * s<sub>1</sub>(n) = h y'<sub>n</sub> for first derivative<a name="line.55"></a> <FONT color="green">056</FONT> * s<sub>2</sub>(n) = h<sup>2</sup>/2 y''<sub>n</sub> for second derivative<a name="line.56"></a> <FONT color="green">057</FONT> * s<sub>3</sub>(n) = h<sup>3</sup>/6 y'''<sub>n</sub> for third derivative<a name="line.57"></a> <FONT color="green">058</FONT> * ...<a name="line.58"></a> <FONT color="green">059</FONT> * s<sub>k</sub>(n) = h<sup>k</sup>/k! y(k)<sub>n</sub> for k<sup>th</sup> derivative<a name="line.59"></a> <FONT color="green">060</FONT> * </pre></p><a name="line.60"></a> <FONT color="green">061</FONT> *<a name="line.61"></a> <FONT color="green">062</FONT> * <p>The definitions above use the classical representation with several previous first<a name="line.62"></a> <FONT color="green">063</FONT> * derivatives. Lets define<a name="line.63"></a> <FONT color="green">064</FONT> * <pre><a name="line.64"></a> <FONT color="green">065</FONT> * q<sub>n</sub> = [ s<sub>1</sub>(n-1) s<sub>1</sub>(n-2) ... s<sub>1</sub>(n-(k-1)) ]<sup>T</sup><a name="line.65"></a> <FONT color="green">066</FONT> * </pre><a name="line.66"></a> <FONT color="green">067</FONT> * (we omit the k index in the notation for clarity). With these definitions,<a name="line.67"></a> <FONT color="green">068</FONT> * Adams-Bashforth methods can be written:<a name="line.68"></a> <FONT color="green">069</FONT> * <ul><a name="line.69"></a> <FONT color="green">070</FONT> * <li>k = 1: y<sub>n+1</sub> = y<sub>n</sub> + s<sub>1</sub>(n)</li><a name="line.70"></a> <FONT color="green">071</FONT> * <li>k = 2: y<sub>n+1</sub> = y<sub>n</sub> + 3/2 s<sub>1</sub>(n) + [ -1/2 ] q<sub>n</sub></li><a name="line.71"></a> <FONT color="green">072</FONT> * <li>k = 3: y<sub>n+1</sub> = y<sub>n</sub> + 23/12 s<sub>1</sub>(n) + [ -16/12 5/12 ] q<sub>n</sub></li><a name="line.72"></a> <FONT color="green">073</FONT> * <li>k = 4: y<sub>n+1</sub> = y<sub>n</sub> + 55/24 s<sub>1</sub>(n) + [ -59/24 37/24 -9/24 ] q<sub>n</sub></li><a name="line.73"></a> <FONT color="green">074</FONT> * <li>...</li><a name="line.74"></a> <FONT color="green">075</FONT> * </ul></p><a name="line.75"></a> <FONT color="green">076</FONT> *<a name="line.76"></a> <FONT color="green">077</FONT> * <p>Instead of using the classical representation with first derivatives only (y<sub>n</sub>,<a name="line.77"></a> <FONT color="green">078</FONT> * s<sub>1</sub>(n) and q<sub>n</sub>), our implementation uses the Nordsieck vector with<a name="line.78"></a> <FONT color="green">079</FONT> * higher degrees scaled derivatives all taken at the same step (y<sub>n</sub>, s<sub>1</sub>(n)<a name="line.79"></a> <FONT color="green">080</FONT> * and r<sub>n</sub>) where r<sub>n</sub> is defined as:<a name="line.80"></a> <FONT color="green">081</FONT> * <pre><a name="line.81"></a> <FONT color="green">082</FONT> * r<sub>n</sub> = [ s<sub>2</sub>(n), s<sub>3</sub>(n) ... s<sub>k</sub>(n) ]<sup>T</sup><a name="line.82"></a> <FONT color="green">083</FONT> * </pre><a name="line.83"></a> <FONT color="green">084</FONT> * (here again we omit the k index in the notation for clarity)<a name="line.84"></a> <FONT color="green">085</FONT> * </p><a name="line.85"></a> <FONT color="green">086</FONT> *<a name="line.86"></a> <FONT color="green">087</FONT> * <p>Taylor series formulas show that for any index offset i, s<sub>1</sub>(n-i) can be<a name="line.87"></a> <FONT color="green">088</FONT> * computed from s<sub>1</sub>(n), s<sub>2</sub>(n) ... s<sub>k</sub>(n), the formula being exact<a name="line.88"></a> <FONT color="green">089</FONT> * for degree k polynomials.<a name="line.89"></a> <FONT color="green">090</FONT> * <pre><a name="line.90"></a> <FONT color="green">091</FONT> * s<sub>1</sub>(n-i) = s<sub>1</sub>(n) + &sum;<sub>j</sub> j (-i)<sup>j-1</sup> s<sub>j</sub>(n)<a name="line.91"></a> <FONT color="green">092</FONT> * </pre><a name="line.92"></a> <FONT color="green">093</FONT> * The previous formula can be used with several values for i to compute the transform between<a name="line.93"></a> <FONT color="green">094</FONT> * classical representation and Nordsieck vector. The transform between r<sub>n</sub><a name="line.94"></a> <FONT color="green">095</FONT> * and q<sub>n</sub> resulting from the Taylor series formulas above is:<a name="line.95"></a> <FONT color="green">096</FONT> * <pre><a name="line.96"></a> <FONT color="green">097</FONT> * q<sub>n</sub> = s<sub>1</sub>(n) u + P r<sub>n</sub><a name="line.97"></a> <FONT color="green">098</FONT> * </pre><a name="line.98"></a> <FONT color="green">099</FONT> * where u is the [ 1 1 ... 1 ]<sup>T</sup> vector and P is the (k-1)&times;(k-1) matrix built<a name="line.99"></a> <FONT color="green">100</FONT> * with the j (-i)<sup>j-1</sup> terms:<a name="line.100"></a> <FONT color="green">101</FONT> * <pre><a name="line.101"></a> <FONT color="green">102</FONT> * [ -2 3 -4 5 ... ]<a name="line.102"></a> <FONT color="green">103</FONT> * [ -4 12 -32 80 ... ]<a name="line.103"></a> <FONT color="green">104</FONT> * P = [ -6 27 -108 405 ... ]<a name="line.104"></a> <FONT color="green">105</FONT> * [ -8 48 -256 1280 ... ]<a name="line.105"></a> <FONT color="green">106</FONT> * [ ... ]<a name="line.106"></a> <FONT color="green">107</FONT> * </pre></p><a name="line.107"></a> <FONT color="green">108</FONT> *<a name="line.108"></a> <FONT color="green">109</FONT> * <p>Using the Nordsieck vector has several advantages:<a name="line.109"></a> <FONT color="green">110</FONT> * <ul><a name="line.110"></a> <FONT color="green">111</FONT> * <li>it greatly simplifies step interpolation as the interpolator mainly applies<a name="line.111"></a> <FONT color="green">112</FONT> * Taylor series formulas,</li><a name="line.112"></a> <FONT color="green">113</FONT> * <li>it simplifies step changes that occur when discrete events that truncate<a name="line.113"></a> <FONT color="green">114</FONT> * the step are triggered,</li><a name="line.114"></a> <FONT color="green">115</FONT> * <li>it allows to extend the methods in order to support adaptive stepsize.</li><a name="line.115"></a> <FONT color="green">116</FONT> * </ul></p><a name="line.116"></a> <FONT color="green">117</FONT> *<a name="line.117"></a> <FONT color="green">118</FONT> * <p>The Nordsieck vector at step n+1 is computed from the Nordsieck vector at step n as follows:<a name="line.118"></a> <FONT color="green">119</FONT> * <ul><a name="line.119"></a> <FONT color="green">120</FONT> * <li>y<sub>n+1</sub> = y<sub>n</sub> + s<sub>1</sub>(n) + u<sup>T</sup> r<sub>n</sub></li><a name="line.120"></a> <FONT color="green">121</FONT> * <li>s<sub>1</sub>(n+1) = h f(t<sub>n+1</sub>, y<sub>n+1</sub>)</li><a name="line.121"></a> <FONT color="green">122</FONT> * <li>r<sub>n+1</sub> = (s<sub>1</sub>(n) - s<sub>1</sub>(n+1)) P<sup>-1</sup> u + P<sup>-1</sup> A P r<sub>n</sub></li><a name="line.122"></a> <FONT color="green">123</FONT> * </ul><a name="line.123"></a> <FONT color="green">124</FONT> * where A is a rows shifting matrix (the lower left part is an identity matrix):<a name="line.124"></a> <FONT color="green">125</FONT> * <pre><a name="line.125"></a> <FONT color="green">126</FONT> * [ 0 0 ... 0 0 | 0 ]<a name="line.126"></a> <FONT color="green">127</FONT> * [ ---------------+---]<a name="line.127"></a> <FONT color="green">128</FONT> * [ 1 0 ... 0 0 | 0 ]<a name="line.128"></a> <FONT color="green">129</FONT> * A = [ 0 1 ... 0 0 | 0 ]<a name="line.129"></a> <FONT color="green">130</FONT> * [ ... | 0 ]<a name="line.130"></a> <FONT color="green">131</FONT> * [ 0 0 ... 1 0 | 0 ]<a name="line.131"></a> <FONT color="green">132</FONT> * [ 0 0 ... 0 1 | 0 ]<a name="line.132"></a> <FONT color="green">133</FONT> * </pre></p><a name="line.133"></a> <FONT color="green">134</FONT> *<a name="line.134"></a> <FONT color="green">135</FONT> * <p>The P<sup>-1</sup>u vector and the P<sup>-1</sup> A P matrix do not depend on the state,<a name="line.135"></a> <FONT color="green">136</FONT> * they only depend on k and therefore are precomputed once for all.</p><a name="line.136"></a> <FONT color="green">137</FONT> *<a name="line.137"></a> <FONT color="green">138</FONT> * @version $Revision: 927202 $ $Date: 2010-03-24 18:11:51 -0400 (Wed, 24 Mar 2010) $<a name="line.138"></a> <FONT color="green">139</FONT> * @since 2.0<a name="line.139"></a> <FONT color="green">140</FONT> */<a name="line.140"></a> <FONT color="green">141</FONT> public class AdamsBashforthIntegrator extends AdamsIntegrator {<a name="line.141"></a> <FONT color="green">142</FONT> <a name="line.142"></a> <FONT color="green">143</FONT> /**<a name="line.143"></a> <FONT color="green">144</FONT> * Build an Adams-Bashforth integrator with the given order and step control parameters.<a name="line.144"></a> <FONT color="green">145</FONT> * @param nSteps number of steps of the method excluding the one being computed<a name="line.145"></a> <FONT color="green">146</FONT> * @param minStep minimal step (must be positive even for backward<a name="line.146"></a> <FONT color="green">147</FONT> * integration), the last step can be smaller than this<a name="line.147"></a> <FONT color="green">148</FONT> * @param maxStep maximal step (must be positive even for backward<a name="line.148"></a> <FONT color="green">149</FONT> * integration)<a name="line.149"></a> <FONT color="green">150</FONT> * @param scalAbsoluteTolerance allowed absolute error<a name="line.150"></a> <FONT color="green">151</FONT> * @param scalRelativeTolerance allowed relative error<a name="line.151"></a> <FONT color="green">152</FONT> * @exception IllegalArgumentException if order is 1 or less<a name="line.152"></a> <FONT color="green">153</FONT> */<a name="line.153"></a> <FONT color="green">154</FONT> public AdamsBashforthIntegrator(final int nSteps,<a name="line.154"></a> <FONT color="green">155</FONT> final double minStep, final double maxStep,<a name="line.155"></a> <FONT color="green">156</FONT> final double scalAbsoluteTolerance,<a name="line.156"></a> <FONT color="green">157</FONT> final double scalRelativeTolerance)<a name="line.157"></a> <FONT color="green">158</FONT> throws IllegalArgumentException {<a name="line.158"></a> <FONT color="green">159</FONT> super("Adams-Bashforth", nSteps, nSteps, minStep, maxStep,<a name="line.159"></a> <FONT color="green">160</FONT> scalAbsoluteTolerance, scalRelativeTolerance);<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> /**<a name="line.163"></a> <FONT color="green">164</FONT> * Build an Adams-Bashforth integrator with the given order and step control parameters.<a name="line.164"></a> <FONT color="green">165</FONT> * @param nSteps number of steps of the method excluding the one being computed<a name="line.165"></a> <FONT color="green">166</FONT> * @param minStep minimal step (must be positive even for backward<a name="line.166"></a> <FONT color="green">167</FONT> * integration), the last step can be smaller than this<a name="line.167"></a> <FONT color="green">168</FONT> * @param maxStep maximal step (must be positive even for backward<a name="line.168"></a> <FONT color="green">169</FONT> * integration)<a name="line.169"></a> <FONT color="green">170</FONT> * @param vecAbsoluteTolerance allowed absolute error<a name="line.170"></a> <FONT color="green">171</FONT> * @param vecRelativeTolerance allowed relative error<a name="line.171"></a> <FONT color="green">172</FONT> * @exception IllegalArgumentException if order is 1 or less<a name="line.172"></a> <FONT color="green">173</FONT> */<a name="line.173"></a> <FONT color="green">174</FONT> public AdamsBashforthIntegrator(final int nSteps,<a name="line.174"></a> <FONT color="green">175</FONT> final double minStep, final double maxStep,<a name="line.175"></a> <FONT color="green">176</FONT> final double[] vecAbsoluteTolerance,<a name="line.176"></a> <FONT color="green">177</FONT> final double[] vecRelativeTolerance)<a name="line.177"></a> <FONT color="green">178</FONT> throws IllegalArgumentException {<a name="line.178"></a> <FONT color="green">179</FONT> super("Adams-Bashforth", nSteps, nSteps, minStep, maxStep,<a name="line.179"></a> <FONT color="green">180</FONT> vecAbsoluteTolerance, vecRelativeTolerance);<a name="line.180"></a> <FONT color="green">181</FONT> }<a name="line.181"></a> <FONT color="green">182</FONT> <a name="line.182"></a> <FONT color="green">183</FONT> /** {@inheritDoc} */<a name="line.183"></a> <FONT color="green">184</FONT> @Override<a name="line.184"></a> <FONT color="green">185</FONT> public double integrate(final FirstOrderDifferentialEquations equations,<a name="line.185"></a> <FONT color="green">186</FONT> final double t0, final double[] y0,<a name="line.186"></a> <FONT color="green">187</FONT> final double t, final double[] y)<a name="line.187"></a> <FONT color="green">188</FONT> throws DerivativeException, IntegratorException {<a name="line.188"></a> <FONT color="green">189</FONT> <a name="line.189"></a> <FONT color="green">190</FONT> final int n = y0.length;<a name="line.190"></a> <FONT color="green">191</FONT> sanityChecks(equations, t0, y0, t, y);<a name="line.191"></a> <FONT color="green">192</FONT> setEquations(equations);<a name="line.192"></a> <FONT color="green">193</FONT> resetEvaluations();<a name="line.193"></a> <FONT color="green">194</FONT> final boolean forward = t > t0;<a name="line.194"></a> <FONT color="green">195</FONT> <a name="line.195"></a> <FONT color="green">196</FONT> // initialize working arrays<a name="line.196"></a> <FONT color="green">197</FONT> if (y != y0) {<a name="line.197"></a> <FONT color="green">198</FONT> System.arraycopy(y0, 0, y, 0, n);<a name="line.198"></a> <FONT color="green">199</FONT> }<a name="line.199"></a> <FONT color="green">200</FONT> final double[] yDot = new double[n];<a name="line.200"></a> <FONT color="green">201</FONT> final double[] yTmp = new double[y0.length];<a name="line.201"></a> <FONT color="green">202</FONT> <a name="line.202"></a> <FONT color="green">203</FONT> // set up an interpolator sharing the integrator arrays<a name="line.203"></a> <FONT color="green">204</FONT> final NordsieckStepInterpolator interpolator = new NordsieckStepInterpolator();<a name="line.204"></a> <FONT color="green">205</FONT> interpolator.reinitialize(y, forward);<a name="line.205"></a> <FONT color="green">206</FONT> final NordsieckStepInterpolator interpolatorTmp = new NordsieckStepInterpolator();<a name="line.206"></a> <FONT color="green">207</FONT> interpolatorTmp.reinitialize(yTmp, forward);<a name="line.207"></a> <FONT color="green">208</FONT> <a name="line.208"></a> <FONT color="green">209</FONT> // set up integration control objects<a name="line.209"></a> <FONT color="green">210</FONT> for (StepHandler handler : stepHandlers) {<a name="line.210"></a> <FONT color="green">211</FONT> handler.reset();<a name="line.211"></a> <FONT color="green">212</FONT> }<a name="line.212"></a> <FONT color="green">213</FONT> CombinedEventsManager manager = addEndTimeChecker(t0, t, eventsHandlersManager);<a name="line.213"></a> <FONT color="green">214</FONT> <a name="line.214"></a> <FONT color="green">215</FONT> // compute the initial Nordsieck vector using the configured starter integrator<a name="line.215"></a> <FONT color="green">216</FONT> start(t0, y, t);<a name="line.216"></a> <FONT color="green">217</FONT> interpolator.reinitialize(stepStart, stepSize, scaled, nordsieck);<a name="line.217"></a> <FONT color="green">218</FONT> interpolator.storeTime(stepStart);<a name="line.218"></a> <FONT color="green">219</FONT> final int lastRow = nordsieck.getRowDimension() - 1;<a name="line.219"></a> <FONT color="green">220</FONT> <a name="line.220"></a> <FONT color="green">221</FONT> // reuse the step that was chosen by the starter integrator<a name="line.221"></a> <FONT color="green">222</FONT> double hNew = stepSize;<a name="line.222"></a> <FONT color="green">223</FONT> interpolator.rescale(hNew);<a name="line.223"></a> <FONT color="green">224</FONT> <a name="line.224"></a> <FONT color="green">225</FONT> boolean lastStep = false;<a name="line.225"></a> <FONT color="green">226</FONT> while (!lastStep) {<a name="line.226"></a> <FONT color="green">227</FONT> <a name="line.227"></a> <FONT color="green">228</FONT> // shift all data<a name="line.228"></a> <FONT color="green">229</FONT> interpolator.shift();<a name="line.229"></a> <FONT color="green">230</FONT> <a name="line.230"></a> <FONT color="green">231</FONT> double error = 0;<a name="line.231"></a> <FONT color="green">232</FONT> for (boolean loop = true; loop;) {<a name="line.232"></a> <FONT color="green">233</FONT> <a name="line.233"></a> <FONT color="green">234</FONT> stepSize = hNew;<a name="line.234"></a> <FONT color="green">235</FONT> <a name="line.235"></a> <FONT color="green">236</FONT> // evaluate error using the last term of the Taylor expansion<a name="line.236"></a> <FONT color="green">237</FONT> error = 0;<a name="line.237"></a> <FONT color="green">238</FONT> for (int i = 0; i < y0.length; ++i) {<a name="line.238"></a> <FONT color="green">239</FONT> final double yScale = Math.abs(y[i]);<a name="line.239"></a> <FONT color="green">240</FONT> final double tol = (vecAbsoluteTolerance == null) ?<a name="line.240"></a> <FONT color="green">241</FONT> (scalAbsoluteTolerance + scalRelativeTolerance * yScale) :<a name="line.241"></a> <FONT color="green">242</FONT> (vecAbsoluteTolerance[i] + vecRelativeTolerance[i] * yScale);<a name="line.242"></a> <FONT color="green">243</FONT> final double ratio = nordsieck.getEntry(lastRow, i) / tol;<a name="line.243"></a> <FONT color="green">244</FONT> error += ratio * ratio;<a name="line.244"></a> <FONT color="green">245</FONT> }<a name="line.245"></a> <FONT color="green">246</FONT> error = Math.sqrt(error / y0.length);<a name="line.246"></a> <FONT color="green">247</FONT> <a name="line.247"></a> <FONT color="green">248</FONT> if (error <= 1.0) {<a name="line.248"></a> <FONT color="green">249</FONT> <a name="line.249"></a> <FONT color="green">250</FONT> // predict a first estimate of the state at step end<a name="line.250"></a> <FONT color="green">251</FONT> final double stepEnd = stepStart + stepSize;<a name="line.251"></a> <FONT color="green">252</FONT> interpolator.setInterpolatedTime(stepEnd);<a name="line.252"></a> <FONT color="green">253</FONT> System.arraycopy(interpolator.getInterpolatedState(), 0, yTmp, 0, y0.length);<a name="line.253"></a> <FONT color="green">254</FONT> <a name="line.254"></a> <FONT color="green">255</FONT> // evaluate the derivative<a name="line.255"></a> <FONT color="green">256</FONT> computeDerivatives(stepEnd, yTmp, yDot);<a name="line.256"></a> <FONT color="green">257</FONT> <a name="line.257"></a> <FONT color="green">258</FONT> // update Nordsieck vector<a name="line.258"></a> <FONT color="green">259</FONT> final double[] predictedScaled = new double[y0.length];<a name="line.259"></a> <FONT color="green">260</FONT> for (int j = 0; j < y0.length; ++j) {<a name="line.260"></a> <FONT color="green">261</FONT> predictedScaled[j] = stepSize * yDot[j];<a name="line.261"></a> <FONT color="green">262</FONT> }<a name="line.262"></a> <FONT color="green">263</FONT> final Array2DRowRealMatrix nordsieckTmp = updateHighOrderDerivativesPhase1(nordsieck);<a name="line.263"></a> <FONT color="green">264</FONT> updateHighOrderDerivativesPhase2(scaled, predictedScaled, nordsieckTmp);<a name="line.264"></a> <FONT color="green">265</FONT> <a name="line.265"></a> <FONT color="green">266</FONT> // discrete events handling<a name="line.266"></a> <FONT color="green">267</FONT> interpolatorTmp.reinitialize(stepEnd, stepSize, predictedScaled, nordsieckTmp);<a name="line.267"></a> <FONT color="green">268</FONT> interpolatorTmp.storeTime(stepStart);<a name="line.268"></a> <FONT color="green">269</FONT> interpolatorTmp.shift();<a name="line.269"></a> <FONT color="green">270</FONT> interpolatorTmp.storeTime(stepEnd);<a name="line.270"></a> <FONT color="green">271</FONT> if (manager.evaluateStep(interpolatorTmp)) {<a name="line.271"></a> <FONT color="green">272</FONT> final double dt = manager.getEventTime() - stepStart;<a name="line.272"></a> <FONT color="green">273</FONT> if (Math.abs(dt) <= Math.ulp(stepStart)) {<a name="line.273"></a> <FONT color="green">274</FONT> // we cannot simply truncate the step, reject the current computation<a name="line.274"></a> <FONT color="green">275</FONT> // and let the loop compute another state with the truncated step.<a name="line.275"></a> <FONT color="green">276</FONT> // it is so small (much probably exactly 0 due to limited accuracy)<a name="line.276"></a> <FONT color="green">277</FONT> // that the code above would fail handling it.<a name="line.277"></a> <FONT color="green">278</FONT> // So we set up an artificial 0 size step by copying states<a name="line.278"></a> <FONT color="green">279</FONT> interpolator.storeTime(stepStart);<a name="line.279"></a> <FONT color="green">280</FONT> System.arraycopy(y, 0, yTmp, 0, y0.length);<a name="line.280"></a> <FONT color="green">281</FONT> hNew = 0;<a name="line.281"></a> <FONT color="green">282</FONT> stepSize = 0;<a name="line.282"></a> <FONT color="green">283</FONT> loop = false;<a name="line.283"></a> <FONT color="green">284</FONT> } else {<a name="line.284"></a> <FONT color="green">285</FONT> // reject the step to match exactly the next switch time<a name="line.285"></a> <FONT color="green">286</FONT> hNew = dt;<a name="line.286"></a> <FONT color="green">287</FONT> interpolator.rescale(hNew);<a name="line.287"></a> <FONT color="green">288</FONT> }<a name="line.288"></a> <FONT color="green">289</FONT> } else {<a name="line.289"></a> <FONT color="green">290</FONT> // accept the step<a name="line.290"></a> <FONT color="green">291</FONT> scaled = predictedScaled;<a name="line.291"></a> <FONT color="green">292</FONT> nordsieck = nordsieckTmp;<a name="line.292"></a> <FONT color="green">293</FONT> interpolator.reinitialize(stepEnd, stepSize, scaled, nordsieck);<a name="line.293"></a> <FONT color="green">294</FONT> loop = false;<a name="line.294"></a> <FONT color="green">295</FONT> }<a name="line.295"></a> <FONT color="green">296</FONT> <a name="line.296"></a> <FONT color="green">297</FONT> } else {<a name="line.297"></a> <FONT color="green">298</FONT> // reject the step and attempt to reduce error by stepsize control<a name="line.298"></a> <FONT color="green">299</FONT> final double factor = computeStepGrowShrinkFactor(error);<a name="line.299"></a> <FONT color="green">300</FONT> hNew = filterStep(stepSize * factor, forward, false);<a name="line.300"></a> <FONT color="green">301</FONT> interpolator.rescale(hNew);<a name="line.301"></a> <FONT color="green">302</FONT> }<a name="line.302"></a> <FONT color="green">303</FONT> <a name="line.303"></a> <FONT color="green">304</FONT> }<a name="line.304"></a> <FONT color="green">305</FONT> <a name="line.305"></a> <FONT color="green">306</FONT> // the step has been accepted (may have been truncated)<a name="line.306"></a> <FONT color="green">307</FONT> final double nextStep = stepStart + stepSize;<a name="line.307"></a> <FONT color="green">308</FONT> System.arraycopy(yTmp, 0, y, 0, n);<a name="line.308"></a> <FONT color="green">309</FONT> interpolator.storeTime(nextStep);<a name="line.309"></a> <FONT color="green">310</FONT> manager.stepAccepted(nextStep, y);<a name="line.310"></a> <FONT color="green">311</FONT> lastStep = manager.stop();<a name="line.311"></a> <FONT color="green">312</FONT> <a name="line.312"></a> <FONT color="green">313</FONT> // provide the step data to the step handler<a name="line.313"></a> <FONT color="green">314</FONT> for (StepHandler handler : stepHandlers) {<a name="line.314"></a> <FONT color="green">315</FONT> interpolator.setInterpolatedTime(nextStep);<a name="line.315"></a> <FONT color="green">316</FONT> handler.handleStep(interpolator, lastStep);<a name="line.316"></a> <FONT color="green">317</FONT> }<a name="line.317"></a> <FONT color="green">318</FONT> stepStart = nextStep;<a name="line.318"></a> <FONT color="green">319</FONT> <a name="line.319"></a> <FONT color="green">320</FONT> if (!lastStep && manager.reset(stepStart, y)) {<a name="line.320"></a> <FONT color="green">321</FONT> <a name="line.321"></a> <FONT color="green">322</FONT> // some events handler has triggered changes that<a name="line.322"></a> <FONT color="green">323</FONT> // invalidate the derivatives, we need to restart from scratch<a name="line.323"></a> <FONT color="green">324</FONT> start(stepStart, y, t);<a name="line.324"></a> <FONT color="green">325</FONT> interpolator.reinitialize(stepStart, stepSize, scaled, nordsieck);<a name="line.325"></a> <FONT color="green">326</FONT> <a name="line.326"></a> <FONT color="green">327</FONT> }<a name="line.327"></a> <FONT color="green">328</FONT> <a name="line.328"></a> <FONT color="green">329</FONT> if (! lastStep) {<a name="line.329"></a> <FONT color="green">330</FONT> // in some rare cases we may get here with stepSize = 0, for example<a name="line.330"></a> <FONT color="green">331</FONT> // when an event occurs at integration start, reducing the first step<a name="line.331"></a> <FONT color="green">332</FONT> // to zero; we have to reset the step to some safe non zero value<a name="line.332"></a> <FONT color="green">333</FONT> stepSize = filterStep(stepSize, forward, true);<a name="line.333"></a> <FONT color="green">334</FONT> <a name="line.334"></a> <FONT color="green">335</FONT> // stepsize control for next step<a name="line.335"></a> <FONT color="green">336</FONT> final double factor = computeStepGrowShrinkFactor(error);<a name="line.336"></a> <FONT color="green">337</FONT> final double scaledH = stepSize * factor;<a name="line.337"></a> <FONT color="green">338</FONT> final double nextT = stepStart + scaledH;<a name="line.338"></a> <FONT color="green">339</FONT> final boolean nextIsLast = forward ? (nextT >= t) : (nextT <= t);<a name="line.339"></a> <FONT color="green">340</FONT> hNew = filterStep(scaledH, forward, nextIsLast);<a name="line.340"></a> <FONT color="green">341</FONT> interpolator.rescale(hNew);<a name="line.341"></a> <FONT color="green">342</FONT> }<a name="line.342"></a> <FONT color="green">343</FONT> <a name="line.343"></a> <FONT color="green">344</FONT> }<a name="line.344"></a> <FONT color="green">345</FONT> <a name="line.345"></a> <FONT color="green">346</FONT> final double stopTime = stepStart;<a name="line.346"></a> <FONT color="green">347</FONT> stepStart = Double.NaN;<a name="line.347"></a> <FONT color="green">348</FONT> stepSize = Double.NaN;<a name="line.348"></a> <FONT color="green">349</FONT> return stopTime;<a name="line.349"></a> <FONT color="green">350</FONT> <a name="line.350"></a> <FONT color="green">351</FONT> }<a name="line.351"></a> <FONT color="green">352</FONT> <a name="line.352"></a> <FONT color="green">353</FONT> }<a name="line.353"></a> </PRE> </BODY> </HTML>