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author | toma <toma@283d02a7-25f6-0310-bc7c-ecb5cbfe19da> | 2009-11-25 17:56:58 +0000 |
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committer | toma <toma@283d02a7-25f6-0310-bc7c-ecb5cbfe19da> | 2009-11-25 17:56:58 +0000 |
commit | 8b2aa1b5301ab60368a03e36df4ff5216726e87d (patch) | |
tree | 36163d4ee667c23b5cf232df2f3004cd0a76202a /kscreensaver/kdesavers/rkodesolver.cpp | |
download | tdeartwork-8b2aa1b5301ab60368a03e36df4ff5216726e87d.tar.gz tdeartwork-8b2aa1b5301ab60368a03e36df4ff5216726e87d.zip |
Copy the KDE 3.5 branch to branches/trinity for new KDE 3.5 features.
BUG:215923
git-svn-id: svn://anonsvn.kde.org/home/kde/branches/trinity/kdeartwork@1054174 283d02a7-25f6-0310-bc7c-ecb5cbfe19da
Diffstat (limited to 'kscreensaver/kdesavers/rkodesolver.cpp')
-rw-r--r-- | kscreensaver/kdesavers/rkodesolver.cpp | 252 |
1 files changed, 252 insertions, 0 deletions
diff --git a/kscreensaver/kdesavers/rkodesolver.cpp b/kscreensaver/kdesavers/rkodesolver.cpp new file mode 100644 index 00000000..2127a110 --- /dev/null +++ b/kscreensaver/kdesavers/rkodesolver.cpp @@ -0,0 +1,252 @@ +//============================================================================ +// +// Ordinary differential equation solver using the Runge-Kutta method. +// $Id$ +// Copyright (C) 2004 Georg Drenkhahn +// +// This file is free software; you can redistribute it and/or modify it under +// the terms of the GNU General Public License version 2 as published by the +// Free Software Foundation. +// +//============================================================================ + +#include <kdebug.h> +#include "rkodesolver.h" + +template<typename T> +RkOdeSolver<T>::RkOdeSolver(const T &x, + const std::valarray<T>& y, + const T &dx, + const T &eps) + : mX(x) +{ + Y(y); + dX(dx); + Eps(eps); +} + +// virtual dtor +template<typename T> +RkOdeSolver<T>::~RkOdeSolver(void) +{} + +// accessors + +template<typename T> +void +RkOdeSolver<T>::dX(const T &a) +{ + if (a < 0.0) + { + kdDebug() << "RkOdeSolver: dx was negative, made it positive" << endl; + mStep = -a; + } + else if (a == 0.0) + { + mStep = 0.001; // a very arbitrary value + kdDebug() << "RkOdeSolver: dx == 0, set it to " << mStep << endl; + } + else + { + mStep = a; + } +} + +template<typename T> +void +RkOdeSolver<T>::Eps(const T &a) +{ + if (a < 0.0) + { + kdDebug() << "RkOdeSolver: eps was negative, made it positive" << endl; + mEps = -a; + } + else if (a == 0.0) + { + mEps = 1e-5; // a very arbitrary value + kdDebug() << "RkOdeSolver: eps == 0, set it to 1e-5" << endl; + } + else + { + mEps = a; + } +} + +template<typename T> +void +RkOdeSolver<T>::Y(const std::valarray<T> &a) +{ + mY.resize(a.size()); + mY = a; +} + + +// public member functions + +template<typename T> +void +RkOdeSolver<T>::integrate(const T &deltaX) +{ + if (deltaX == 0) + { + return; // nothing to integrate + } + + // init dydx if uninitialised + if (mDydx.size() != mY.size()) + { + mDydx.resize(mY.size()); + mDydx = f(mX,mY); + } + + static const unsigned int maxiter = 10000; + const T x2 = mX + deltaX; + + unsigned int iter; + for (iter=0; + iter<maxiter && rkStepCheck(x2-mX) == false; + ++iter) + {} + + if (iter>maxiter) + { + kdDebug() << "RkOdeSolver: More than " << maxiter + << " iterations in RkOdeSolver::integrate" << endl; + // TODO throw exeption here + } +} + + +// private member functions + +template<typename T> +bool +RkOdeSolver<T>::rkStepCheck(const T& dx_requested) +{ + static const T safety = 0.9; + static const T pshrnk = -0.25; + static const T pgrow = -0.2; + + // reduce step size by no more than a factor 10 + static const T shrinkLimit = 0.1; + // enlarge step size by no more than a factor 5 + static const T growthLimit = 5.0; + // errmax_sl = 6561.0 + static const T errmax_sl = pow(shrinkLimit/safety, 1.0/pshrnk); + // errmax_gl = 1.89e-4 + static const T errmax_gl = pow(growthLimit/safety, 1.0/pgrow); + + static const unsigned int maxiter = 100; + + if (dx_requested == 0) + { + return true; // integration done + } + + std::valarray<T> ytmp(mY.size()); + std::valarray<T> yerr(mY.size()); + std::valarray<T> t(mY.size()); + + bool stepSizeWasMaximal; + T dx; + if (std::abs(dx_requested) > mStep) + { + stepSizeWasMaximal = true; + dx = dx_requested>0 ? mStep : -mStep; + } + else + { + stepSizeWasMaximal = false; + dx = dx_requested; + } + + // generic scaling factor + std::valarray<T> yscal = std::abs(mY) + std::abs(dx*mDydx) + 1e-15; + + unsigned int iter = 0; + T errmax = 0; + do + { + if (errmax >= 1.0) + { + // reduce step size + dx *= errmax<errmax_sl ? safety * pow(errmax, pshrnk) : shrinkLimit; + stepSizeWasMaximal = true; + if (mX == mX + dx) + { + // stepsize below numerical resolution + kdDebug() << "RkOdeSolver: stepsize underflow in rkStepCheck" + << endl; + // TODO throw exeption here + exit(0); + } + // new dx -> update scaling vector + yscal = std::abs(mY) + std::abs(dx*mDydx) + 1e-15; + } + + ytmp = rkStep(dx, yerr); // try to make a step forward + t = std::abs(yerr/yscal); // calc the error vector + errmax = t.max()/mEps; // calc the rel. maximal error + ++iter; + } while (iter < maxiter && errmax >= 1.0); + + if (iter >= maxiter) + { + kdDebug() << "RkOdeSolver: too many iterations in rkStepCheck" << endl; + // TODO throw exeption here + exit(0); + } + + if (stepSizeWasMaximal == true) + { + // estimate next step size if used step size was maximal + mStep = + std::abs(dx) + * (errmax>errmax_gl ? safety * pow(errmax, pgrow) : growthLimit); + } + mX += dx; // make step forward + mY = ytmp; // save new function values + mDydx = f(mX,mY); // and update derivatives + + return std::abs(dx) < std::abs(dx_requested); +} + +template<typename T> +std::valarray<T> +RkOdeSolver<T>::rkStep(const T& dx, std::valarray<T>& yerr) const +{ + static const T + a2=0.2, a3=0.3, a4=0.6, a5=1.0, a6=0.875, + b21=0.2, + b31=3.0/40.0, b32=9.0/40.0, + b41=0.3, b42=-0.9, b43=1.2, + b51=-11.0/54.0, b52=2.5, b53=-70.0/27.0, b54=35.0/27.0, + b61=1631.0/55296.0, b62=175.0/512.0, b63=575.0/13824.0, + b64=44275.0/110592.0, b65=253.0/4096.0, + c1=37.0/378.0, c3=250.0/621.0, c4=125.0/594.0, c6=512.0/1771.0, + dc1=c1-2825.0/27648.0, dc3=c3-18575.0/48384.0, + dc4=c4-13525.0/55296.0, dc5=-277.0/14336.0, dc6=c6-0.25; + + std::valarray<T> ak2 = f(mX + a2*dx, + mY + dx*b21*mDydx); // 2. step + std::valarray<T> ak3 = f(mX + a3*dx, + mY + dx*(b31*mDydx + b32*ak2)); // 3.step + std::valarray<T> ak4 = f(mX + a4*dx, + mY + dx*(b41*mDydx + b42*ak2 + + b43*ak3)); // 4.step + std::valarray<T> ak5 = f(mX + a5*dx, + mY + dx*(b51*mDydx + b52*ak2 + + b53*ak3 + b54*ak4)); // 5.step + std::valarray<T> ak6 = f(mX + a6*dx, + mY + dx*(b61*mDydx + b62*ak2 + + b63*ak3 + b64*ak4 + + b65*ak5)); // 6.step + yerr = dx*(dc1*mDydx + dc3*ak3 + dc4*ak4 + dc5*ak5 + dc6*ak6); + return mY + dx*( c1*mDydx + c3*ak3 + c4*ak4 + c6*ak6); +} + + +// explicite instantiations +//template RkOdeSolver<long double>; +template class RkOdeSolver<double>; +//template RkOdeSolver<float>; |