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

1 files changed, 187 insertions, 0 deletions

diff --git a/kscreensaver/kdesavers/rkodesolver.h b/kscreensaver/kdesavers/rkodesolver.h
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+++ b/kscreensaver/kdesavers/rkodesolver.h
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+//============================================================================
+//
+// 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.
+//
+//============================================================================
+
+#ifndef RKODESOLVER_H
+#define RKODESOLVER_H
+
+// STL headers
+#include <valarray>
+
+/** @brief Solver class to integrate a first-order ordinary differential
+ * equation (ODE) by means of a 6. order Runge-Kutta method.
+ *
+ * The ODE system must be given as the derivative
+ * dy/dx = f(x,y)
+ * with x in R and y in R^n.
+ *
+ * Within this class the function f() is a pure virtual function, which must be
+ * reimplemented in a derived class.
+ *
+ * No other special data type for vectors or matrices are needed besides the STL
+ * class std::valarray. */
+template<typename T>
+class RkOdeSolver
+{
+  public:
+   /** @brief Constructor
+    * @param x Initial integration parameter
+    * @param y Initial function values of function to integrate
+    * @param dx Initial guess for step size.  Will be automatically adjusted to
+    * guarantee required precision.
+    * @param eps Relative precision
+    *
+    * Initialises the solver with start conditions. */
+   RkOdeSolver(const T& x=0.0,
+               const std::valarray<T>& y=std::valarray<T>(0),
+               const T& dx=0,
+               const T& eps=1e-6);
+   /** @brief Destructor */
+   virtual ~RkOdeSolver(void);
+
+   /** @brief Integrates the ordinary differential equation from the current x
+    * value to x+@a dx.
+    * @param dx x-interval size to integrate over starting from x.  dx may be
+    * negative.
+    *
+    * The integration is performed by calling rkStepCheck() repeatedly until the
+    * desired x value is reached. */
+   void integrate(const T& dx);
+
+   // Accessors
+
+   // get/set x value
+   /** @brief Get current x value.
+    * @return Reference of x value. */
+   const T& X(void) const;
+   /** @brief Set current x value.
+    * @param a The value to be set. */
+   void X(const T& a);
+
+   // get/set y value
+   /** @brief Get current y value.
+    * @return Reference of y vector. */
+   const std::valarray<T>& Y(void) const;
+   /** @brief Set current y values.
+    * @param a The vector to be set. */
+   void Y(const std::valarray<T>& a);
+
+   /** @brief Get current dy/dx value.
+    * @return Reference of dy/dx vector. */
+   const std::valarray<T>& dYdX(void) const;
+
+   // get/set dx value
+   /** @brief Get current estimated step size dX.
+    * @return Reference of dX value. */
+   const T& dX(void) const;
+   /** @brief Set estimated step size dX.
+    * @param a The value to be set. */
+   void dX(const T& a);
+
+   // get/set eps value
+   /** @brief Get current presision.
+    * @return Reference of precision value. */
+   const T& Eps(void) const;
+   /** @brief Set estimated presision.
+    * @param a The value to be set. */
+   void Eps(const T& a);
+
+  protected:
+   // purely virtual function which is integrated
+   /** @brief ODE function
+    * @param x Integration value
+    * @param y Function value
+    * @return Derivation
+    *
+    * This purely virtual function returns the value of dy/dx for the given
+    * parameter values of x and y. */
+   virtual std::valarray<T>
+      f(const T& x, const std::valarray<T>& y) const = 0;
+
+  private:
+   /** @brief Perform one integration step with a tolerable relative error given
+    * by ::mErr.
+    * @param dx Maximal step size, may be positive or negative depending on
+    * integration direction.
+    * @return Flag indicating if made absolute integration step was equal |@a dx
+    * | (true) less than |@a dx | (false).
+    *
+    * A new estimate for the maximum next step size is saved to ::mStep.  The
+    * new values for x, y and f are saved in ::mX, ::mY and ::mDydx. */
+   bool rkStepCheck(const T& dx);
+   /** @brief Perform one Runge-Kutta integration step forward with step size
+    * ::mStep
+    * @param dx Step size relative to current x value.
+    * @param yerr Reference to vector in which the estimated error made in y is
+    * returned.
+    * @return The y value after the step at x+@a dx.
+    *
+    * Stored current x,y values are not adjusted. */
+   std::valarray<T> rkStep(const T& dx, std::valarray<T>& yerr) const;
+
+   /** current x value */
+   T mX;
+   /** current y value */
+   std::valarray<T> mY;
+   /** current value of dy/dx */
+   std::valarray<T> mDydx;
+
+   /** allowed relative error */
+   T mEps;
+   /** estimated step size for next Runge-Kutta step */
+   T mStep;
+};
+
+// inline accessors
+
+template<typename T>
+inline const T&
+RkOdeSolver<T>::X(void) const
+{
+   return mX;
+}
+
+template<typename T>
+inline void
+RkOdeSolver<T>::X(const T &a)
+{
+   mX = a;
+}
+
+template<typename T>
+inline const std::valarray<T>&
+RkOdeSolver<T>::Y(void) const
+{
+   return mY;
+}
+
+template<typename T>
+inline const std::valarray<T>&
+RkOdeSolver<T>::dYdX(void) const
+{
+   return mDydx;
+}
+
+template<typename T>
+inline const T&
+RkOdeSolver<T>::dX(void) const
+{
+   return mStep;
+}
+
+template<typename T>
+inline const T&
+RkOdeSolver<T>::Eps(void) const
+{
+   return mEps;
+}
+
+#endif