Add tests for preconditioner and solver
Sungtae An
parent
f34c2d941c
commit
e72b346592
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@ -143,6 +143,182 @@ TEST( Preconditioner, buildBlocks2 ) {
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EXPECT(assert_equal(it1->second, *it2));
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}
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/* ************************************************************************* */
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TEST( BlockJacobiPreconditioner, verySimpleLinerSystem) {
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// Ax = [4 1][u] = [1] x0 = [2]
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// [1 3][v] [2] [1]
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//
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// exact solution x = [1/11, 7/11]';
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//
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// Create a Gaussian Factor Graph
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GaussianFactorGraph simpleGFG;
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simpleGFG += JacobianFactor(0, (Matrix(2,2)<< 4, 1, 1, 3), (Vector(2) << 1,2 ), noiseModel::Unit::Create(2));
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//simpleGFG.print("Factors\n");
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// Expected Hessian block diagonal matrices
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std::map<Key, Matrix> expectedHessian =simpleGFG.hessianBlockDiagonal();
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// Actual Hessian block diagonal matrices from BlockJacobiPreconditioner::build
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std::vector<Matrix> actualHessian = buildBlocks(simpleGFG, KeyInfo(simpleGFG));
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// Compare the number of block diagonal matrices
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EXPECT_LONGS_EQUAL(expectedHessian.size(), actualHessian.size());
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// Compare the values of matrices
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std::map<Key, Matrix>::const_iterator it1 = expectedHessian.begin();
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std::vector<Matrix>::const_iterator it2 = actualHessian.begin();
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// the function 'build' in BlockJacobianPreconditioner stores in 'buffer'
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// the cholesky decomposion of each block of the hessian
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// In this example there is a single block (i.e., a single value)
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// and the corresponding block of the Hessian is
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//
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// H0 = [17 7; 7 10]
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//
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EXPECT(assert_equal(it1->second, *it2));
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// TODO: Matrix expectedH0 ...
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//EXPECT(assert_equal(it1->second, *it2));
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// The corresponding Cholesky decomposition is:
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// R = chol(H0) = [4.1231 1.6977 0 2.6679] (from Matlab)
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Preconditioner::shared_ptr preconditioner = createPreconditioner(boost::make_shared<gtsam::BlockJacobiPreconditionerParameters>());
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preconditioner->build(simpleGFG, KeyInfo(simpleGFG), std::map<Key,Vector>());
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boost::shared_ptr<BlockJacobiPreconditioner> blockJacobi = boost::dynamic_pointer_cast<BlockJacobiPreconditioner>(preconditioner);
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double* buf = blockJacobi->getBuffer();
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for(int i=0; i<4; ++i){}
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// TODO: EXPECT(assert_equal(number..,buf[i]));
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}
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/* ************************************************************************* */
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TEST( PCGsolver, verySimpleLinearSystem) {
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// Ax = [4 1][u] = [1] x0 = [2]
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// [1 3][v] [2] [1]
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//
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// exact solution x = [1/11, 7/11]';
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//
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// Create a Gaussian Factor Graph
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GaussianFactorGraph simpleGFG;
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simpleGFG += JacobianFactor(0, (Matrix(2,2)<< 4, 1, 1, 3), (Vector(2) << 1,2 ), noiseModel::Unit::Create(2));
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//simpleGFG.print("Factors\n");
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// Exact solution already known
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VectorValues exactSolution;
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exactSolution.insert(0, (Vector(2) << 1./11., 7./11.));
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//exactSolution.print("Exact");
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// Solve the system using direct method
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VectorValues deltaDirect = simpleGFG.optimize();
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EXPECT(assert_equal(exactSolution, deltaDirect, 1e-7));
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//deltaDirect.print("Direct");
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// Solve the system using PCG
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// With Dummy preconditioner
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gtsam::PCGSolverParameters::shared_ptr pcg = boost::make_shared<gtsam::PCGSolverParameters>();
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pcg->preconditioner_ = boost::make_shared<gtsam::DummyPreconditionerParameters>();
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pcg->setMaxIterations(500);
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pcg->setEpsilon_abs(0.0);
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pcg->setEpsilon_rel(0.0);
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//pcg->setVerbosity("ERROR");
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VectorValues deltaPCGDummy = PCGSolver(*pcg).optimize(simpleGFG);
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EXPECT(assert_equal(exactSolution, deltaPCGDummy, 1e-7));
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// With Block-Jacobi preconditioner
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gtsam::PCGSolverParameters::shared_ptr pcgJacobi = boost::make_shared<gtsam::PCGSolverParameters>();
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pcgJacobi->preconditioner_ = boost::make_shared<gtsam::BlockJacobiPreconditionerParameters>();
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pcgJacobi->setMaxIterations(500);
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pcgJacobi->setEpsilon_abs(0.0);
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pcgJacobi->setEpsilon_rel(0.0);
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VectorValues deltaPCGJacobi = PCGSolver(*pcgJacobi).optimize(simpleGFG);
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// Failed!
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EXPECT(assert_equal(exactSolution, deltaPCGJacobi, 1e-5));
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//deltaPCGJacobi.print("PCG Jacobi");
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}
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/* ************************************************************************* */
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TEST(PCGSolver, simpleLinearSystem) {
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// Create a Gaussian Factor Graph
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GaussianFactorGraph simpleGFG;
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SharedDiagonal unit2 = noiseModel::Unit::Create(2);
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simpleGFG += JacobianFactor(2, (Matrix(2,2)<< 10, 0, 0, 10), (Vector(2) << -1, -1), unit2);
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simpleGFG += JacobianFactor(2, (Matrix(2,2)<< -10, 0, 0, -10), 0, (Matrix(2,2)<< 10, 0, 0, 10), (Vector(2) << 2, -1), unit2);
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simpleGFG += JacobianFactor(2, (Matrix(2,2)<< -5, 0, 0, -5), 1, (Matrix(2,2)<< 5, 0, 0, 5), (Vector(2) << 0, 1), unit2);
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simpleGFG += JacobianFactor(0, (Matrix(2,2)<< -5, 0, 0, -5), 1, (Matrix(2,2)<< 5, 0, 0, 5), (Vector(2) << -1, 1.5), unit2);
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simpleGFG += JacobianFactor(0, (Matrix(2,2)<< 1, 0, 0, 1), (Vector(2) << 0, 0), unit2);
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simpleGFG += JacobianFactor(1, (Matrix(2,2)<< 1, 0, 0, 1), (Vector(2) << 0, 0), unit2);
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simpleGFG += JacobianFactor(2, (Matrix(2,2)<< 1, 0, 0, 1), (Vector(2) << 0, 0), unit2);
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//simpleGFG.print("Factors\n");
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// Expected solution
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VectorValues expectedSolution;
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expectedSolution.insert(0, (Vector(2) << 0.100498, -0.196756));
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expectedSolution.insert(2, (Vector(2) << -0.0990413, -0.0980577));
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expectedSolution.insert(1, (Vector(2) << -0.0973252, 0.100582));
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// Solve the system using direct method
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VectorValues deltaDirect = simpleGFG.optimize();
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EXPECT(assert_equal(expectedSolution, deltaDirect, 1e-5));
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//expectedSolution.print("Expected");
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//deltaCholesky.print("Direct");
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// Solve the system using PCG
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VectorValues initial;
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initial.insert(0, (Vector(2) << 0.1, -0.1));
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initial.insert(1, (Vector(2) << -0.1, 0.1));
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initial.insert(2, (Vector(2) << -0.1, -0.1));
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// With Dummy preconditioner
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gtsam::PCGSolverParameters::shared_ptr pcg = boost::make_shared<gtsam::PCGSolverParameters>();
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pcg->preconditioner_ = boost::make_shared<gtsam::DummyPreconditionerParameters>();
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pcg->setMaxIterations(500);
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pcg->setEpsilon_abs(0.0);
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pcg->setEpsilon_rel(0.0);
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//pcg->setVerbosity("ERROR");
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VectorValues deltaPCGDummy = PCGSolver(*pcg).optimize(simpleGFG, KeyInfo(simpleGFG), std::map<Key,Vector>(), initial);
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// Failed!
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EXPECT(assert_equal(expectedSolution, deltaPCGDummy, 1e-5));
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//deltaPCGDummy.print("PCG Dummy");
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// Solve the system using Preconditioned Conjugate Gradient
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pcg->preconditioner_ = boost::make_shared<gtsam::BlockJacobiPreconditionerParameters>();
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VectorValues deltaPCGJacobi = PCGSolver(*pcg).optimize(simpleGFG, KeyInfo(simpleGFG), std::map<Key,Vector>(), initial);
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// Failed!
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EXPECT(assert_equal(expectedSolution, deltaPCGJacobi, 1e-5));
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//deltaPCGJacobi.print("PCG Jacobi");
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// Test that the retrieval of the diagonal blocks of the Jacobian are correct.
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std::map<Key, Matrix> expectedHessian =simpleGFG.hessianBlockDiagonal();
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std::vector<Matrix> actualHessian = buildBlocks(simpleGFG, KeyInfo(simpleGFG));
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EXPECT_LONGS_EQUAL(expectedHessian.size(), actualHessian.size());
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std::map<Key, Matrix>::const_iterator it1 = expectedHessian.begin();
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std::vector<Matrix>::const_iterator it2 = actualHessian.begin();
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// The corresponding Cholesky decomposition is:
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// R = chol(H0) = [4.1231 1.6977 0 2.6679] (from Matlab)
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Preconditioner::shared_ptr preconditioner = createPreconditioner(boost::make_shared<gtsam::BlockJacobiPreconditionerParameters>());
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preconditioner->build(simpleGFG, KeyInfo(simpleGFG), std::map<Key,Vector>());
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boost::shared_ptr<BlockJacobiPreconditioner> blockJacobi = boost::dynamic_pointer_cast<BlockJacobiPreconditioner>(preconditioner);
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double* buf = blockJacobi->getBuffer();
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for(int i=0; i<4; ++i){}
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// TODO: EXPECT(assert_equal(number..,buf[i]));
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size_t i = 0;
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for(; it1!=expectedHessian.end(); it1++, it2++){
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EXPECT(assert_equal(it1->second, *it2));
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Matrix R_i(2,2);
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R_i(0,0) = buf[i+0];
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R_i(0,1) = buf[i+1];
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R_i(1,0) = buf[i+2];
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R_i(1,1) = buf[i+3];
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Matrix actualH_i = R_i.transpose() * R_i;// i-th diagonal block
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EXPECT(assert_equal(it1->second, actualH_i));
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i += 4;
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}
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}
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/* ************************************************************************* */
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int main() { TestResult tr; return TestRegistry::runAllTests(tr); }
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/* ************************************************************************* */
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