forked from LeenkxTeam/LNXSDK
		
	
		
			
				
	
	
		
			111 lines
		
	
	
		
			3.2 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			111 lines
		
	
	
		
			3.2 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
| /*
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| Bullet Continuous Collision Detection and Physics Library
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| Copyright (c) 2003-2013 Erwin Coumans  http://bulletphysics.org
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| 
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| This software is provided 'as-is', without any express or implied warranty.
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| In no event will the authors be held liable for any damages arising from the use of this software.
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| Permission is granted to anyone to use this software for any purpose, 
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| including commercial applications, and to alter it and redistribute it freely, 
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| subject to the following restrictions:
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| 
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| 1. The origin of this software must not be misrepresented; you must not claim that you wrote the original software. If you use this software in a product, an acknowledgment in the product documentation would be appreciated but is not required.
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| 2. Altered source versions must be plainly marked as such, and must not be misrepresented as being the original software.
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| 3. This notice may not be removed or altered from any source distribution.
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| */
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| ///original version written by Erwin Coumans, October 2013
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| 
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| #ifndef BT_SOLVE_PROJECTED_GAUSS_SEIDEL_H
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| #define BT_SOLVE_PROJECTED_GAUSS_SEIDEL_H
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| 
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| 
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| #include "btMLCPSolverInterface.h"
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| 
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| ///This solver is mainly for debug/learning purposes: it is functionally equivalent to the btSequentialImpulseConstraintSolver solver, but much slower (it builds the full LCP matrix)
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| class btSolveProjectedGaussSeidel : public btMLCPSolverInterface
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| {
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| 
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| public:
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| 
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| 	btScalar m_leastSquaresResidualThreshold;
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| 	btScalar m_leastSquaresResidual;
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| 
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| 	btSolveProjectedGaussSeidel()
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| 		:m_leastSquaresResidualThreshold(0),
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| 		m_leastSquaresResidual(0)
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| 	{
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| 	}
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| 
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| 	virtual bool solveMLCP(const btMatrixXu & A, const btVectorXu & b, btVectorXu& x, const btVectorXu & lo,const btVectorXu & hi,const btAlignedObjectArray<int>& limitDependency, int numIterations, bool useSparsity = true)
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| 	{
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| 		if (!A.rows())
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| 			return true;
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| 		//the A matrix is sparse, so compute the non-zero elements
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| 		A.rowComputeNonZeroElements();
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| 
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| 		//A is a m-n matrix, m rows, n columns
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| 		btAssert(A.rows() == b.rows());
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| 
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| 		int i, j, numRows = A.rows();
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| 	
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| 		btScalar delta;
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| 
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| 		for (int k = 0; k <numIterations; k++)
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| 		{
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| 			m_leastSquaresResidual = 0.f;
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| 			for (i = 0; i <numRows; i++)
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| 			{
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| 				delta = 0.0f;
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| 				if (useSparsity)
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| 				{
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| 					for (int h=0;h<A.m_rowNonZeroElements1[i].size();h++)
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| 					{
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| 						int j = A.m_rowNonZeroElements1[i][h];
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| 						if (j != i)//skip main diagonal
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| 						{
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| 							delta += A(i,j) * x[j];
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| 						}
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| 					}
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| 				} else
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| 				{
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| 					for (j = 0; j <i; j++) 
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| 						delta += A(i,j) * x[j];
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| 					for (j = i+1; j<numRows; j++) 
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| 						delta += A(i,j) * x[j];
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| 				}
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| 
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| 				btScalar aDiag = A(i,i);
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| 				btScalar xOld = x[i];
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| 				x [i] = (b [i] - delta) / aDiag;
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| 				btScalar s = 1.f;
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| 
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| 				if (limitDependency[i]>=0)
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| 				{
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| 					s = x[limitDependency[i]];
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| 					if (s<0)
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| 						s=1;
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| 				}
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| 			
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| 				if (x[i]<lo[i]*s)
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| 					x[i]=lo[i]*s;
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| 				if (x[i]>hi[i]*s)
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| 					x[i]=hi[i]*s;
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| 				btScalar diff = x[i] - xOld;
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| 				m_leastSquaresResidual += diff*diff;
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| 			}
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| 
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| 			btScalar eps  = m_leastSquaresResidualThreshold;
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| 			if ((m_leastSquaresResidual < eps) || (k >=(numIterations-1)))
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| 			{
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| #ifdef VERBOSE_PRINTF_RESIDUAL
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| 				printf("totalLenSqr = %f at iteration #%d\n", m_leastSquaresResidual,k);
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| #endif
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| 				break;
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| 			}
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| 		}
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| 		return true;
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| 	}
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| 
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| };
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| 
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| #endif //BT_SOLVE_PROJECTED_GAUSS_SEIDEL_H
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