351 lines
		
	
	
		
			7.4 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			351 lines
		
	
	
		
			7.4 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_LEMKE_SOLVER_H
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| #define BT_LEMKE_SOLVER_H
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| 
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| 
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| #include "btMLCPSolverInterface.h"
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| #include "btLemkeAlgorithm.h"
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| 
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| 
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| 
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| 
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| ///The btLemkeSolver is based on "Fast Implementation of Lemke’s Algorithm for Rigid Body Contact Simulation (John E. Lloyd) "
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| ///It is a slower but more accurate solver. Increase the m_maxLoops for better convergence, at the cost of more CPU time.
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| ///The original implementation of the btLemkeAlgorithm was done by Kilian Grundl from the MBSim team
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| class btLemkeSolver : public btMLCPSolverInterface
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| {
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| protected:
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| 	
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| public:
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| 
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| 	btScalar	m_maxValue;
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| 	int			m_debugLevel;
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| 	int			m_maxLoops;
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| 	bool		m_useLoHighBounds;
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| 	
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| 	
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| 
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| 	btLemkeSolver()
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| 		:m_maxValue(100000),
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| 		m_debugLevel(0),
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| 		m_maxLoops(1000),
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| 		m_useLoHighBounds(true)
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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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| 		
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| 		if (m_useLoHighBounds)
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| 		{
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| 
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| 		BT_PROFILE("btLemkeSolver::solveMLCP");
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| 		int n = A.rows();
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| 		if (0==n)
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| 			return true;
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| 		
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| 		bool fail = false;
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| 
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| 		btVectorXu solution(n);
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| 		btVectorXu q1;
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| 		q1.resize(n);
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| 		for (int row=0;row<n;row++)
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| 		{
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| 			q1[row] = -b[row];
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| 		}
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| 
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| 	//		cout << "A" << endl;
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| 	//		cout << A << endl;
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| 
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| 			/////////////////////////////////////
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| 
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| 			//slow matrix inversion, replace with LU decomposition
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| 			btMatrixXu A1;
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| 			btMatrixXu B(n,n);
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| 			{
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| 				BT_PROFILE("inverse(slow)");
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| 				A1.resize(A.rows(),A.cols());
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| 				for (int row=0;row<A.rows();row++)
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| 				{
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| 					for (int col=0;col<A.cols();col++)
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| 					{
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| 						A1.setElem(row,col,A(row,col));
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| 					}
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| 				}
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| 
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| 				btMatrixXu matrix;
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| 				matrix.resize(n,2*n);
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| 				for (int row=0;row<n;row++)
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| 				{
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| 					for (int col=0;col<n;col++)
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| 					{
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| 						matrix.setElem(row,col,A1(row,col));
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| 					}
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| 				}
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| 
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| 
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| 				btScalar ratio,a;
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| 				int i,j,k;
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| 				for(i = 0; i < n; i++){
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| 				for(j = n; j < 2*n; j++){
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| 					if(i==(j-n))
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| 						matrix.setElem(i,j,1.0);
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| 					else
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| 						matrix.setElem(i,j,0.0);
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| 				}
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| 			}
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| 			for(i = 0; i < n; i++){
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| 				for(j = 0; j < n; j++){
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| 					if(i!=j)
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| 					{
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| 						btScalar v = matrix(i,i);
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| 						if (btFuzzyZero(v))
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| 						{
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| 							a = 0.000001f;
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| 						}
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| 						ratio = matrix(j,i)/matrix(i,i);
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| 						for(k = 0; k < 2*n; k++){
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| 							matrix.addElem(j,k,- ratio * matrix(i,k));
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| 						}
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| 					}
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| 				}
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| 			}
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| 			for(i = 0; i < n; i++){
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| 				a = matrix(i,i);
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| 				if (btFuzzyZero(a))
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| 				{
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| 					a = 0.000001f;
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| 				}
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| 				btScalar invA = 1.f/a;
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| 				for(j = 0; j < 2*n; j++){
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| 					matrix.mulElem(i,j,invA);
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| 				}
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| 			}
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| 
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| 	
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| 
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| 	
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| 
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| 			for (int row=0;row<n;row++)
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| 				{
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| 					for (int col=0;col<n;col++)
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| 					{
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| 						B.setElem(row,col,matrix(row,n+col));
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| 					}
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| 				}
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| 			}
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| 
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| 		btMatrixXu b1(n,1);
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| 
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| 		btMatrixXu M(n*2,n*2);
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| 		for (int row=0;row<n;row++)
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| 		{
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| 			b1.setElem(row,0,-b[row]);
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| 			for (int col=0;col<n;col++)
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| 			{
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| 				btScalar v =B(row,col);
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| 				M.setElem(row,col,v);
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| 				M.setElem(n+row,n+col,v);
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| 				M.setElem(n+row,col,-v);
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| 				M.setElem(row,n+col,-v);
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| 
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| 			}
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| 		}
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| 
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| 		btMatrixXu Bb1 = B*b1;
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| //		q = [ (-B*b1 - lo)'   (hi + B*b1)' ]'
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| 
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| 		btVectorXu qq;
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| 		qq.resize(n*2);
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| 		for (int row=0;row<n;row++)
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| 		{
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| 			qq[row] = -Bb1(row,0)-lo[row];
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| 			qq[n+row] = Bb1(row,0)+hi[row];
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| 		}
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| 
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| 		btVectorXu z1;
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| 
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| 		btMatrixXu y1;
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| 		y1.resize(n,1);
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| 		btLemkeAlgorithm lemke(M,qq,m_debugLevel);
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| 		{
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| 			BT_PROFILE("lemke.solve");
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| 			lemke.setSystem(M,qq);
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| 			z1  = lemke.solve(m_maxLoops);
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| 		}
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| 		for (int row=0;row<n;row++)
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| 		{
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| 			y1.setElem(row,0,z1[2*n+row]-z1[3*n+row]);
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| 		}
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| 		btMatrixXu y1_b1(n,1);
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| 		for (int i=0;i<n;i++)
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| 		{
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| 			y1_b1.setElem(i,0,y1(i,0)-b1(i,0));
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| 		}
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| 
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| 		btMatrixXu x1;
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| 
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| 		x1 = B*(y1_b1);
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| 			
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| 		for (int row=0;row<n;row++)
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| 		{
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| 			solution[row] = x1(row,0);//n];
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| 		}
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| 
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| 		int errorIndexMax = -1;
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| 		int errorIndexMin = -1;
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| 		float errorValueMax = -1e30;
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| 		float errorValueMin = 1e30;
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| 		
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| 		for (int i=0;i<n;i++)
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| 		{
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| 			x[i] = solution[i];
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| 			volatile btScalar check = x[i];
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| 			if (x[i] != check)
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| 			{
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| 				//printf("Lemke result is #NAN\n");
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| 				x.setZero();
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| 				return false;
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| 			}
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| 			
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| 			//this is some hack/safety mechanism, to discard invalid solutions from the Lemke solver 
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| 			//we need to figure out why it happens, and fix it, or detect it properly)
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| 			if (x[i]>m_maxValue)
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| 			{
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| 				if (x[i]> errorValueMax)
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| 				{
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| 					fail = true;
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| 					errorIndexMax = i;
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| 					errorValueMax = x[i];
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| 				}
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| 				////printf("x[i] = %f,",x[i]);
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| 			}
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| 			if (x[i]<-m_maxValue)
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| 			{
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| 				if (x[i]<errorValueMin)
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| 				{
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| 					errorIndexMin = i;
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| 					errorValueMin = x[i];
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| 					fail = true;
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| 					//printf("x[i] = %f,",x[i]);
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| 				}
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| 			}
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| 		}
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| 		if (fail)
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| 		{
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| 			int m_errorCountTimes = 0;
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| 			if (errorIndexMin<0)
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| 				errorValueMin = 0.f;
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| 			if (errorIndexMax<0)
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| 				errorValueMax = 0.f;
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| 			m_errorCountTimes++;
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| 		//	printf("Error (x[%d] = %f, x[%d] = %f), resetting %d times\n", errorIndexMin,errorValueMin, errorIndexMax, errorValueMax, errorCountTimes++);
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| 			for (int i=0;i<n;i++)
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| 			{
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| 				x[i]=0.f;
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| 			}
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| 		}
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| 		return !fail;
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| 	} else
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| 		
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| 	{
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| 			int dimension = A.rows();
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| 		if (0==dimension)
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| 			return true;
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| 		
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| //		printf("================ solving using Lemke/Newton/Fixpoint\n");
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| 
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| 		btVectorXu q;
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| 		q.resize(dimension);
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| 		for (int row=0;row<dimension;row++)
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| 		{
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| 			q[row] = -b[row];
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| 		}
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| 		
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| 		btLemkeAlgorithm lemke(A,q,m_debugLevel);
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| 		
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| 		
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| 		lemke.setSystem(A,q);
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| 		
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| 		btVectorXu solution = lemke.solve(m_maxLoops);
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| 		
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| 		//check solution
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| 		
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| 		bool fail = false;
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| 		int errorIndexMax = -1;
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| 		int errorIndexMin = -1;
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| 		float errorValueMax = -1e30;
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| 		float errorValueMin = 1e30;
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| 		
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| 		for (int i=0;i<dimension;i++)
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| 		{
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| 			x[i] = solution[i+dimension];
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| 			volatile btScalar check = x[i];
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| 			if (x[i] != check)
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| 			{
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| 				x.setZero();
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| 				return false;
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| 			}
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| 			
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| 			//this is some hack/safety mechanism, to discard invalid solutions from the Lemke solver 
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| 			//we need to figure out why it happens, and fix it, or detect it properly)
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| 			if (x[i]>m_maxValue)
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| 			{
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| 				if (x[i]> errorValueMax)
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| 				{
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| 					fail = true;
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| 					errorIndexMax = i;
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| 					errorValueMax = x[i];
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| 				}
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| 				////printf("x[i] = %f,",x[i]);
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| 			}
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| 			if (x[i]<-m_maxValue)
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| 			{
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| 				if (x[i]<errorValueMin)
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| 				{
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| 					errorIndexMin = i;
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| 					errorValueMin = x[i];
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| 					fail = true;
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| 					//printf("x[i] = %f,",x[i]);
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| 				}
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| 			}
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| 		}
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| 		if (fail)
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| 		{
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| 			static int errorCountTimes = 0;
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| 			if (errorIndexMin<0)
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| 				errorValueMin = 0.f;
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| 			if (errorIndexMax<0)
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| 				errorValueMax = 0.f;
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| 			printf("Error (x[%d] = %f, x[%d] = %f), resetting %d times\n", errorIndexMin,errorValueMin, errorIndexMax, errorValueMax, errorCountTimes++);
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| 			for (int i=0;i<dimension;i++)
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| 			{
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| 				x[i]=0.f;
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| 			}
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| 		}
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| 
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| 
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| 		return !fail;
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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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| 
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| #endif //BT_LEMKE_SOLVER_H
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