/* =========================================================================== Doom 3 GPL Source Code Copyright (C) 1999-2011 id Software LLC, a ZeniMax Media company. This file is part of the Doom 3 GPL Source Code (?Doom 3 Source Code?). Doom 3 Source Code is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. Doom 3 Source Code is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with Doom 3 Source Code. If not, see . In addition, the Doom 3 Source Code is also subject to certain additional terms. You should have received a copy of these additional terms immediately following the terms and conditions of the GNU General Public License which accompanied the Doom 3 Source Code. If not, please request a copy in writing from id Software at the address below. If you have questions concerning this license or the applicable additional terms, you may contact in writing id Software LLC, c/o ZeniMax Media Inc., Suite 120, Rockville, Maryland 20850 USA. =========================================================================== */ #include "../precompiled.h" #pragma hdrstop //=============================================================== // // idODE_Euler // //=============================================================== /* ============= idODE_Euler::idODE_Euler ============= */ idODE_Euler::idODE_Euler( const int dim, deriveFunction_t dr, const void *ud ) { dimension = dim; derivatives = new float[dim]; derive = dr; userData = ud; } /* ============= idODE_Euler::~idODE_Euler ============= */ idODE_Euler::~idODE_Euler( void ) { delete[] derivatives; } /* ============= idODE_Euler::Evaluate ============= */ float idODE_Euler::Evaluate( const float *state, float *newState, float t0, float t1 ) { float delta; int i; derive( t0, userData, state, derivatives ); delta = t1 - t0; for ( i = 0; i < dimension; i++ ) { newState[i] = state[i] + delta * derivatives[i]; } return delta; } //=============================================================== // // idODE_Midpoint // //=============================================================== /* ============= idODE_Midpoint::idODE_Midpoint ============= */ idODE_Midpoint::idODE_Midpoint( const int dim, deriveFunction_t dr, const void *ud ) { dimension = dim; tmpState = new float[dim]; derivatives = new float[dim]; derive = dr; userData = ud; } /* ============= idODE_Midpoint::~idODE_Midpoint ============= */ idODE_Midpoint::~idODE_Midpoint( void ) { delete tmpState; delete derivatives; } /* ============= idODE_Midpoint::~Evaluate ============= */ float idODE_Midpoint::Evaluate( const float *state, float *newState, float t0, float t1 ) { double delta, halfDelta; int i; delta = t1 - t0; halfDelta = delta * 0.5; // first step derive( t0, userData, state, derivatives ); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + halfDelta * derivatives[i]; } // second step derive( t0 + halfDelta, userData, tmpState, derivatives ); for ( i = 0; i < dimension; i++ ) { newState[i] = state[i] + delta * derivatives[i]; } return delta; } //=============================================================== // // idODE_RK4 // //=============================================================== /* ============= idODE_RK4::idODE_RK4 ============= */ idODE_RK4::idODE_RK4( const int dim, deriveFunction_t dr, const void *ud ) { dimension = dim; derive = dr; userData = ud; tmpState = new float[dim]; d1 = new float[dim]; d2 = new float[dim]; d3 = new float[dim]; d4 = new float[dim]; } /* ============= idODE_RK4::~idODE_RK4 ============= */ idODE_RK4::~idODE_RK4( void ) { delete tmpState; delete d1; delete d2; delete d3; delete d4; } /* ============= idODE_RK4::Evaluate ============= */ float idODE_RK4::Evaluate( const float *state, float *newState, float t0, float t1 ) { double delta, halfDelta, sixthDelta; int i; delta = t1 - t0; halfDelta = delta * 0.5; // first step derive( t0, userData, state, d1 ); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + halfDelta * d1[i]; } // second step derive( t0 + halfDelta, userData, tmpState, d2 ); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + halfDelta * d2[i]; } // third step derive( t0 + halfDelta, userData, tmpState, d3 ); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + delta * d3[i]; } // fourth step derive( t0 + delta, userData, tmpState, d4 ); sixthDelta = delta * (1.0/6.0); for ( i = 0; i < dimension; i++ ) { newState[i] = state[i] + sixthDelta * (d1[i] + 2.0 * (d2[i] + d3[i]) + d4[i]); } return delta; } //=============================================================== // // idODE_RK4Adaptive // //=============================================================== /* ============= idODE_RK4Adaptive::idODE_RK4Adaptive ============= */ idODE_RK4Adaptive::idODE_RK4Adaptive( const int dim, deriveFunction_t dr, const void *ud ) { dimension = dim; derive = dr; userData = ud; maxError = 0.01f; tmpState = new float[dim]; d1 = new float[dim]; d1half = new float [dim]; d2 = new float[dim]; d3 = new float[dim]; d4 = new float[dim]; } /* ============= idODE_RK4Adaptive::~idODE_RK4Adaptive ============= */ idODE_RK4Adaptive::~idODE_RK4Adaptive( void ) { delete tmpState; delete d1; delete d1half; delete d2; delete d3; delete d4; } /* ============= idODE_RK4Adaptive::SetMaxError ============= */ void idODE_RK4Adaptive::SetMaxError( const float err ) { if ( err > 0.0f ) { maxError = err; } } /* ============= idODE_RK4Adaptive::Evaluate ============= */ float idODE_RK4Adaptive::Evaluate( const float *state, float *newState, float t0, float t1 ) { double delta, halfDelta, fourthDelta, sixthDelta; double error, max; int i, n; delta = t1 - t0; for ( n = 0; n < 4; n++ ) { halfDelta = delta * 0.5; fourthDelta = delta * 0.25; // first step of first half delta derive( t0, userData, state, d1 ); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + fourthDelta * d1[i]; } // second step of first half delta derive( t0 + fourthDelta, userData, tmpState, d2 ); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + fourthDelta * d2[i]; } // third step of first half delta derive( t0 + fourthDelta, userData, tmpState, d3 ); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + halfDelta * d3[i]; } // fourth step of first half delta derive( t0 + halfDelta, userData, tmpState, d4 ); sixthDelta = halfDelta * (1.0/6.0); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + sixthDelta * (d1[i] + 2.0 * (d2[i] + d3[i]) + d4[i]); } // first step of second half delta derive( t0 + halfDelta, userData, tmpState, d1half ); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + fourthDelta * d1half[i]; } // second step of second half delta derive( t0 + halfDelta + fourthDelta, userData, tmpState, d2 ); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + fourthDelta * d2[i]; } // third step of second half delta derive( t0 + halfDelta + fourthDelta, userData, tmpState, d3 ); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + halfDelta * d3[i]; } // fourth step of second half delta derive( t0 + delta, userData, tmpState, d4 ); sixthDelta = halfDelta * (1.0/6.0); for ( i = 0; i < dimension; i++ ) { newState[i] = state[i] + sixthDelta * (d1[i] + 2.0 * (d2[i] + d3[i]) + d4[i]); } // first step of full delta for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + halfDelta * d1[i]; } // second step of full delta derive( t0 + halfDelta, userData, tmpState, d2 ); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + halfDelta * d2[i]; } // third step of full delta derive( t0 + halfDelta, userData, tmpState, d3 ); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + delta * d3[i]; } // fourth step of full delta derive( t0 + delta, userData, tmpState, d4 ); sixthDelta = delta * (1.0/6.0); for ( i = 0; i < dimension; i++ ) { tmpState[i] = state[i] + sixthDelta * (d1[i] + 2.0 * (d2[i] + d3[i]) + d4[i]); } // get max estimated error max = 0.0; for ( i = 0; i < dimension; i++ ) { error = idMath::Fabs( (newState[i] - tmpState[i]) / (delta * d1[i] + 1e-10) ); if ( error > max ) { max = error; } } error = max / maxError; if ( error <= 1.0f ) { return delta * 4.0; } if ( delta <= 1e-7 ) { return delta; } delta *= 0.25; } return delta; }