void test_3()
{
GetLog() << "\n-------------------------------------------------\n";
GetLog() << "TEST: generic system with stiffness blocks \n\n";
// Important: create a 'system descriptor' object that
// contains variables and constraints:
ChLcpSystemDescriptor mdescriptor;
// Now let's add variables, constraints and stiffness, as sparse data:
mdescriptor.BeginInsertion(); // ----- system description
// Create C++ objects representing 'variables', set their M blocks
// (the masses) and set their known terms 'fb'
ChMatrix33<> minertia;
minertia.FillDiag(6);
ChLcpVariablesBodyOwnMass mvarA;
mvarA.SetBodyMass(5);
mvarA.SetBodyInertia(&minertia);
mvarA.Get_fb().FillRandom(-3,5);
ChLcpVariablesBodyOwnMass mvarB;
mvarB.SetBodyMass(4);
mvarB.SetBodyInertia(&minertia);
mvarB.Get_fb().FillRandom(1,3);
ChLcpVariablesBodyOwnMass mvarC;
mvarC.SetBodyMass(5.5);
mvarC.SetBodyInertia(&minertia);
mvarC.Get_fb().FillRandom(-8,3);
mdescriptor.InsertVariables(&mvarA);
mdescriptor.InsertVariables(&mvarB);
mdescriptor.InsertVariables(&mvarC);
// Create two C++ objects representing 'constraints' between variables
// and set the jacobian to random values;
// Also set cfm term (E diagonal = -cfm)
ChLcpConstraintTwoBodies mca(&mvarA, &mvarB);
mca.Set_b_i(3);
mca.Get_Cq_a()->FillRandom(-1,1);
mca.Get_Cq_b()->FillRandom(-1,1);
mca.Set_cfm_i(0.2);
ChLcpConstraintTwoBodies mcb(&mvarA, &mvarB);
mcb.Set_b_i(5);
mcb.Get_Cq_a()->FillRandom(-1,1);
mcb.Get_Cq_b()->FillRandom(-1,1);
mcb.Set_cfm_i(0.1);
mdescriptor.InsertConstraint(&mca);
mdescriptor.InsertConstraint(&mcb);
// Create two C++ objects representing 'stiffness' between variables:
ChLcpKstiffnessGeneric mKa;
// set the affected variables (so this K is a 12x12 matrix, relative to 4 6x6 blocks)
std::vector<ChLcpVariables*> mvarsa;
mvarsa.push_back(&mvarA);
mvarsa.push_back(&mvarB);
mKa.SetVariables(mvarsa);
// just fill K with random values (but symmetric, by making a product of matr*matrtransposed)
ChMatrixDynamic<> mtempA = *mKa.Get_K(); // easy init to same size of K
mtempA.FillRandom(-0.3,0.3);
ChMatrixDynamic<> mtempB;
mtempB.CopyFromMatrixT(mtempA);
*mKa.Get_K() = -mtempA*mtempB;
mdescriptor.InsertKstiffness(&mKa);
ChLcpKstiffnessGeneric mKb;
// set the affected variables (so this K is a 12x12 matrix, relative to 4 6x6 blocks)
std::vector<ChLcpVariables*> mvarsb;
mvarsb.push_back(&mvarB);
mvarsb.push_back(&mvarC);
mKb.SetVariables(mvarsb);
*mKb.Get_K() = *mKa.Get_K();
mdescriptor.InsertKstiffness(&mKb);
mdescriptor.EndInsertion(); // ----- system description ends here
// SOLVE the problem with an iterative Krylov solver.
// In this case we use a MINRES-like solver, that features
// very good convergence, it supports indefinite cases (ex.
// redundant constraints) and also supports the presence
// of ChStiffness blocks (other solvers cannot cope with this!)
// .. create the solver
ChLcpIterativePMINRES msolver_mr(80, // max iterations
false, // don't use warm start
1e-12); // termination tolerance
// .. set optional parameters of solver
msolver_mr.SetDiagonalPreconditioning(true);
msolver_mr.SetVerbose(true);
// .. solve the system (passing variables, constraints, stiffness
// blocks with the ChSystemDescriptor that we populated above)
msolver_mr.Solve(mdescriptor);
// .. optional: get the result as a single vector (it collects all q_i and l_i
// solved values stored in variables and constraints), just for check.
chrono::ChMatrixDynamic<double> mx;
mdescriptor.FromUnknownsToVector(mx); // x ={q,-l}
// CHECK. Test if, with the solved x, we really have Z*x-d=0 ...
// to this end do the multiplication with the special function
// SystemProduct() that is 'sparse-friendly' and does not build Z explicitly:
chrono::ChMatrixDynamic<double> md;
mdescriptor.BuildDiVector(md); // d={f;-b}
chrono::ChMatrixDynamic<double> mZx;
mdescriptor.SystemProduct(mZx, &mx); // Zx = Z*x
GetLog() << "CHECK: norm of solver residual: ||Z*x-d|| -------------------\n";
GetLog() << (mZx - md).NormInf() << "\n";
/*
// Alternatively, instead of using FromUnknownsToVector, to fetch
// result, you could just loop over the variables (q values) and
// over the constraints (l values), as already shown in previous examples:
for (int im = 0; im < mdescriptor.GetVariablesList().size(); im++)
GetLog() << " " << mdescriptor.GetVariablesList()[im]->Get_qb()(0) << "\n";
for (int ic = 0; ic < mdescriptor.GetConstraintsList().size(); ic++)
GetLog() << " " << mdescriptor.GetConstraintsList()[ic]->Get_l_i() << "\n";
*/
}
void test_1()
{
GetLog() << "\n-------------------------------------------------\n";
GetLog() << "TEST: generic system with two constraints \n\n";
// Important: create a 'system descriptor' object that
// contains variables and constraints:
ChLcpSystemDescriptor mdescriptor;
// Now let's add variables and constraints, as sparse data:
mdescriptor.BeginInsertion(); // ----- system description starts here
// create C++ objects representing 'variables':
ChLcpVariablesGeneric mvarA(3);
mvarA.GetMass().SetIdentity();
mvarA.GetMass()*=10;
ChLinearAlgebra::Invert(mvarA.GetInvMass(),&mvarA.GetMass());
mvarA.Get_fb()(0)=1;
mvarA.Get_fb()(1)=2;
ChLcpVariablesGeneric mvarB(3);
mvarB.GetMass().SetIdentity();
mvarB.GetMass()*=20;
ChLinearAlgebra::Invert(mvarB.GetInvMass(),&mvarB.GetMass());
mdescriptor.InsertVariables(&mvarA);
mdescriptor.InsertVariables(&mvarB);
// create C++ objects representing 'constraints' between variables:
ChLcpConstraintTwoGeneric mca(&mvarA, &mvarB);
mca.Set_b_i(-5);
mca.Get_Cq_a()->ElementN(0)=1;
mca.Get_Cq_a()->ElementN(1)=2;
mca.Get_Cq_a()->ElementN(2)=-1;
mca.Get_Cq_b()->ElementN(0)=1;
mca.Get_Cq_b()->ElementN(1)=-2;
mca.Get_Cq_b()->ElementN(2)=0;
ChLcpConstraintTwoGeneric mcb(&mvarA, &mvarB);
mcb.Set_b_i( 1);
mcb.Get_Cq_a()->ElementN(0)=0;
mcb.Get_Cq_a()->ElementN(1)=1;
mcb.Get_Cq_a()->ElementN(2)=0;
mcb.Get_Cq_b()->ElementN(0)=0;
mcb.Get_Cq_b()->ElementN(1)=-2;
mcb.Get_Cq_b()->ElementN(2)=0;
mdescriptor.InsertConstraint(&mca);
mdescriptor.InsertConstraint(&mcb);
mdescriptor.EndInsertion(); // ----- system description ends here
// Solve the problem with an iterative fixed-point solver, for an
// approximate (but very fast) solution:
//
// .. create the solver
ChLcpIterativeSOR msolver_iter( 1, // max iterations
false, // don't use warm start
0.0, // termination tolerance
0.8); // omega
// .. pass the constraint and the variables to the solver
// to solve - that's all.
msolver_iter.Solve(mdescriptor);
// Ok, now present the result to the user, with some
// statistical information:
double max_res, max_LCPerr;
mdescriptor.ComputeFeasabilityViolation(max_res, max_LCPerr);
// If needed, dump the full system M and Cq matrices
// on disk, in Matlab sparse format:
ChSparseMatrix matrM;
ChSparseMatrix matrCq;
mdescriptor.BuildMatrices(&matrCq, &matrM);
try
{
ChStreamOutAsciiFile fileM ("dump_M.dat");
ChStreamOutAsciiFile fileCq ("dump_Cq.dat");
matrM.StreamOUTsparseMatlabFormat(fileM);
matrCq.StreamOUTsparseMatlabFormat(fileCq);
}
catch (ChException myex)
{
GetLog() << "FILE ERROR: " << myex.what();
}
// Other checks
GetLog() << "**** Using ChLcpIterativeSOR ********** \n\n";
GetLog() << "METRICS: max residual: " << max_res << " max LCP error: " << max_LCPerr << " \n\n";
GetLog() << "vars q_a and q_b -------------------\n";
GetLog() << mvarA.Get_qb();
GetLog() << mvarB.Get_qb() << " \n";;
GetLog() << "multipliers l_1 and l_2 ------------\n\n";
GetLog() << mca.Get_l_i() << " \n";
GetLog() << mcb.Get_l_i() << " \n\n";
GetLog() << "constraint residuals c_1 and c_2 ---\n";
GetLog() << mca.Get_c_i() << " \n";
GetLog() << mcb.Get_c_i() << " \n\n\n";
// reset variables
mvarA.Get_qb().FillElem(0.);
mvarB.Get_qb().FillElem(0.);
// Now solve it again, but using the simplex solver.
// The simplex solver is much slower, and it cannot handle
// the case of unilateral constraints. This is reccomended
// only for reference or very precise solution of systems with only
// bilateral constraints, in a limited number.
ChLcpSimplexSolver msolver_simpl;
msolver_simpl.Solve(mdescriptor);
mdescriptor.ComputeFeasabilityViolation(max_res, max_LCPerr);
GetLog() << "**** Using ChLcpSimplexSolver ********* \n\n";
GetLog() << "METRICS: max residual: " << max_res << " max LCP error: " << max_LCPerr << " \n\n";
GetLog() << "vars q_a and q_b -------------------\n";
GetLog() << mvarA.Get_qb();
GetLog() << mvarB.Get_qb() << " \n";;
GetLog() << "multipliers l_1 and l_2 ------------\n\n";
GetLog() << mca.Get_l_i() << " \n";
GetLog() << mcb.Get_l_i() << " \n\n";
GetLog() << "constraint residuals c_1 and c_2 ---\n";
GetLog() << mca.Get_c_i() << " \n";
GetLog() << mcb.Get_c_i() << " \n";
}
void test_2()
{
GetLog() << "\n-------------------------------------------------\n";
GetLog() << "TEST: 1D vertical pendulum - ChLcpIterativePMINRES \n\n";
ChLcpSystemDescriptor mdescriptor;
mdescriptor.BeginInsertion(); // ----- system description starts here
int n_masses = 11;
std::vector<ChLcpVariablesGeneric*> vars;
std::vector<ChLcpConstraintTwoGeneric*> constraints;
for (int im = 0; im < n_masses; im++)
{
vars.push_back (new ChLcpVariablesGeneric(1));
vars[im]->GetMass()(0)=10;
vars[im]->GetInvMass()(0)=1./vars[im]->GetMass()(0);
vars[im]->Get_fb()(0)= -9.8*vars[im]->GetMass()(0)*0.01;
//if (im==5) vars[im]->Get_fb()(0)= 50;
mdescriptor.InsertVariables(vars[im]);
if (im>0)
{
constraints.push_back (new ChLcpConstraintTwoGeneric(vars[im], vars[im-1]) );
constraints[im-1]->Set_b_i(0);
constraints[im-1]->Get_Cq_a()->ElementN(0)= 1;
constraints[im-1]->Get_Cq_b()->ElementN(0)= -1;
//constraints[im-1]->SetMode(CONSTRAINT_UNILATERAL); // not supported by ChLcpSimplexSolver
mdescriptor.InsertConstraint(constraints[im-1]);
}
}
// First variable of 1st domain is 'fixed' like in a hanging chain
vars[0]->SetDisabled(true);
mdescriptor.EndInsertion(); // ----- system description is finished
try
{
chrono::ChSparseMatrix mdM;
chrono::ChSparseMatrix mdCq;
chrono::ChSparseMatrix mdE;
chrono::ChMatrixDynamic<double> mdf;
chrono::ChMatrixDynamic<double> mdb;
chrono::ChMatrixDynamic<double> mdfric;
mdescriptor.ConvertToMatrixForm(&mdCq, &mdM, &mdE, &mdf, &mdb, &mdfric);
chrono::ChStreamOutAsciiFile file_M("dump_M.dat");
mdM.StreamOUTsparseMatlabFormat(file_M);
chrono::ChStreamOutAsciiFile file_Cq("dump_Cq.dat");
mdCq.StreamOUTsparseMatlabFormat(file_Cq);
chrono::ChStreamOutAsciiFile file_E("dump_E.dat");
mdE.StreamOUTsparseMatlabFormat(file_E);
chrono::ChStreamOutAsciiFile file_f("dump_f.dat");
mdf.StreamOUTdenseMatlabFormat(file_f);
chrono::ChStreamOutAsciiFile file_b("dump_b.dat");
mdb.StreamOUTdenseMatlabFormat(file_b);
chrono::ChStreamOutAsciiFile file_fric("dump_fric.dat");
mdfric.StreamOUTdenseMatlabFormat(file_fric);
}
catch(chrono::ChException myexc)
{
chrono::GetLog() << myexc.what();
}
// Create a solver of Krylov type
ChLcpIterativePMINRES msolver_krylov(20, // max iterations
false, // warm start
0.00001); // tolerance
// .. pass the constraint and the variables to the solver
// to solve - that's all.
msolver_krylov.Solve(mdescriptor);
// Output values
GetLog() << "VARIABLES: \n";
for (int im = 0; im < vars.size(); im++)
GetLog() << " " << vars[im]->Get_qb()(0) << "\n";
GetLog() << "CONSTRAINTS: \n";
for (int ic = 0; ic < constraints.size(); ic++)
GetLog() << " " << constraints[ic]->Get_l_i() << "\n";
// Try again, for reference, using a direct solver.
// This type of solver is much slower, and it cannot handle
// the case of unilateral constraints. This is reccomended
// only for reference or very precise solution of systems with only
// bilateral constraints, in a limited number.
GetLog() << "\n\nTEST: 1D vertical pendulum - ChLcpSimplexSolver \n\n";
ChLcpSimplexSolver msolver_simpl;
msolver_simpl.Solve(mdescriptor);
GetLog() << "VARIABLES: \n";
for (int im = 0; im < vars.size(); im++)
GetLog() << " " << vars[im]->Get_qb()(0) << "\n";
GetLog() << "CONSTRAINTS: \n";
for (int ic = 0; ic < constraints.size(); ic++)
GetLog() << " " << constraints[ic]->Get_l_i() << "\n";
}