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Change the noise model as non-isotropic in the test of PCG solver with a simple linear system

release/4.3a0
Sungtae An 2014-12-04 22:14:46 -05:00
parent 60f43c7a4b
commit c2b5b152a4
1 changed files with 41 additions and 39 deletions
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80
tests/testPreconditioner.cpp
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@ -100,7 +100,7 @@ std::vector<Matrix> buildBlocks( const GaussianFactorGraph &gfg, const KeyInfo &
return blocks;
}
/* *************************************************************************
/* ************************************************************************* */
TEST( Preconditioner, buildBlocks ) {
// Create simple Gaussian factor graph and initial values
GaussianFactorGraph gfg = createSimpleGaussianFactorGraph();
@ -121,7 +121,7 @@ TEST( Preconditioner, buildBlocks ) {
EXPECT(assert_equal(it1->second, *it2));
}
/* *************************************************************************
/* ************************************************************************* */
TEST( Preconditioner, buildBlocks2 ) {
// Create simple Gaussian factor graph and initial values
GaussianFactorGraph gfg = createSimpleGaussianFactorGraphUnordered();
@ -143,7 +143,7 @@ TEST( Preconditioner, buildBlocks2 ) {
EXPECT(assert_equal(it1->second, *it2));
}
/* *************************************************************************
/* ************************************************************************* */
TEST( BlockJacobiPreconditioner, verySimpleLinerSystem) {
// Ax = [4 1][u] = [1] x0 = [2]
// [1 3][v] [2] [1]
@ -187,7 +187,7 @@ TEST( BlockJacobiPreconditioner, verySimpleLinerSystem) {
Vector expectedR = (Vector(4) << 4.1231, 0, 1.6977, 2.6679).finished();
double* buf = blockJacobi->getBuffer();
for(int i=0; i<4; ++i){
EXPECT_DOUBLES_EQUAL(expectedR(i), buf[i], 1e-4);
EXPECT_DOUBLES_EQUAL(expectedR(i), buf[i], 1e-4);
}
}
@ -222,7 +222,7 @@ TEST( BlockJacobiPreconditioner, SimpleLinerSystem) {
boost::shared_ptr<BlockJacobiPreconditioner> blockJacobi = boost::dynamic_pointer_cast<BlockJacobiPreconditioner>(preconditioner);
double* buf = blockJacobi->getBuffer();
for(size_t i=0; i<blockJacobi->getBufferSize(); ++i){
std::cout << "buf[" << i << "] = " << buf[i] << std::endl;
std::cout << "buf[" << i << "] = " << buf[i] << std::endl;
}
}
@ -244,12 +244,12 @@ TEST( PCGsolver, verySimpleLinearSystem) {
// Exact solution already known
VectorValues exactSolution;
exactSolution.insert(0, (Vector(2) << 1./11., 7./11.).finished());
//exactSolution.print("Exact");
exactSolution.print("Exact");
// Solve the system using direct method
VectorValues deltaDirect = simpleGFG.optimize();
EXPECT(assert_equal(exactSolution, deltaDirect, 1e-7));
//deltaDirect.print("Direct");
deltaDirect.print("Direct");
// Solve the system using PCG
// With Dummy preconditioner
@ -261,25 +261,27 @@ TEST( PCGsolver, verySimpleLinearSystem) {
//pcg->setVerbosity("ERROR");
VectorValues deltaPCGDummy = PCGSolver(*pcg).optimize(simpleGFG);
EXPECT(assert_equal(exactSolution, deltaPCGDummy, 1e-7));
deltaPCGDummy.print("PCG Dummy");
// With Block-Jacobi preconditioner
gtsam::PCGSolverParameters::shared_ptr pcgJacobi = boost::make_shared<gtsam::PCGSolverParameters>();
pcgJacobi->preconditioner_ = boost::make_shared<gtsam::BlockJacobiPreconditionerParameters>();
pcgJacobi->setMaxIterations(500);
pcgJacobi->setMaxIterations(1500);// It takes more than 1000 iterations for this test
pcgJacobi->setEpsilon_abs(0.0);
pcgJacobi->setEpsilon_rel(0.0);
VectorValues deltaPCGJacobi = PCGSolver(*pcgJacobi).optimize(simpleGFG);
// Failed!
EXPECT(assert_equal(exactSolution, deltaPCGJacobi, 1e-5));
//deltaPCGJacobi.print("PCG Jacobi");
deltaPCGJacobi.print("PCG Jacobi");
}
/* ************************************************************************* */
TEST(PCGSolver, simpleLinearSystem) {
// Create a Gaussian Factor Graph
GaussianFactorGraph simpleGFG;
SharedDiagonal unit2 = noiseModel::Unit::Create(2);
//SharedDiagonal unit2 = noiseModel::Unit::Create(2);
SharedDiagonal unit2 = noiseModel::Diagonal::Sigmas(Vector2(0.5, 0.3));
simpleGFG += JacobianFactor(2, (Matrix(2,2)<< 10, 0, 0, 10).finished(), (Vector(2) << -1, -1).finished(), unit2);
simpleGFG += JacobianFactor(2, (Matrix(2,2)<< -10, 0, 0, -10).finished(), 0, (Matrix(2,2)<< 10, 0, 0, 10).finished(), (Vector(2) << 2, -1).finished(), unit2);
simpleGFG += JacobianFactor(2, (Matrix(2,2)<< -5, 0, 0, -5).finished(), 1, (Matrix(2,2)<< 5, 0, 0, 5).finished(), (Vector(2) << 0, 1).finished(), unit2);
@ -298,8 +300,8 @@ TEST(PCGSolver, simpleLinearSystem) {
// Solve the system using direct method
VectorValues deltaDirect = simpleGFG.optimize();
EXPECT(assert_equal(expectedSolution, deltaDirect, 1e-5));
//expectedSolution.print("Expected");
//deltaCholesky.print("Direct");
expectedSolution.print("Expected");
deltaDirect.print("Direct");
// Solve the system using PCG
VectorValues initial;
@ -318,44 +320,44 @@ TEST(PCGSolver, simpleLinearSystem) {
VectorValues deltaPCGDummy = PCGSolver(*pcg).optimize(simpleGFG, KeyInfo(simpleGFG), std::map<Key,Vector>(), initial);
// Failed!
EXPECT(assert_equal(expectedSolution, deltaPCGDummy, 1e-5));
//deltaPCGDummy.print("PCG Dummy");
deltaPCGDummy.print("PCG Dummy");
// Solve the system using Preconditioned Conjugate Gradient
pcg->preconditioner_ = boost::make_shared<gtsam::BlockJacobiPreconditionerParameters>();
VectorValues deltaPCGJacobi = PCGSolver(*pcg).optimize(simpleGFG, KeyInfo(simpleGFG), std::map<Key,Vector>(), initial);
// Failed!
EXPECT(assert_equal(expectedSolution, deltaPCGJacobi, 1e-5));
//deltaPCGJacobi.print("PCG Jacobi");
deltaPCGJacobi.print("PCG Jacobi");
// Test that the retrieval of the diagonal blocks of the Jacobian are correct.
std::map<Key, Matrix> expectedHessian =simpleGFG.hessianBlockDiagonal();
std::vector<Matrix> actualHessian = buildBlocks(simpleGFG, KeyInfo(simpleGFG));
EXPECT_LONGS_EQUAL(expectedHessian.size(), actualHessian.size());
std::map<Key, Matrix>::const_iterator it1 = expectedHessian.begin();
std::vector<Matrix>::const_iterator it2 = actualHessian.begin();
std::map<Key, Matrix> expectedHessian =simpleGFG.hessianBlockDiagonal();
std::vector<Matrix> actualHessian = buildBlocks(simpleGFG, KeyInfo(simpleGFG));
EXPECT_LONGS_EQUAL(expectedHessian.size(), actualHessian.size());
std::map<Key, Matrix>::const_iterator it1 = expectedHessian.begin();
std::vector<Matrix>::const_iterator it2 = actualHessian.begin();
// The corresponding Cholesky decomposition is:
// R = chol(H0) = [4.1231 1.6977 0 2.6679] (from Matlab)
Preconditioner::shared_ptr preconditioner = createPreconditioner(boost::make_shared<gtsam::BlockJacobiPreconditionerParameters>());
preconditioner->build(simpleGFG, KeyInfo(simpleGFG), std::map<Key,Vector>());
boost::shared_ptr<BlockJacobiPreconditioner> blockJacobi = boost::dynamic_pointer_cast<BlockJacobiPreconditioner>(preconditioner);
double* buf = blockJacobi->getBuffer();
for(int i=0; i<4; ++i){}
// TODO: EXPECT(assert_equal(number..,buf[i]));
// The corresponding Cholesky decomposition is:
// R = chol(H0) = [4.1231 1.6977 0 2.6679] (from Matlab)
Preconditioner::shared_ptr preconditioner = createPreconditioner(boost::make_shared<gtsam::BlockJacobiPreconditionerParameters>());
preconditioner->build(simpleGFG, KeyInfo(simpleGFG), std::map<Key,Vector>());
boost::shared_ptr<BlockJacobiPreconditioner> blockJacobi = boost::dynamic_pointer_cast<BlockJacobiPreconditioner>(preconditioner);
double* buf = blockJacobi->getBuffer();
for(int i=0; i<4; ++i){}
// TODO: EXPECT(assert_equal(number..,buf[i]));
size_t i = 0;
for(; it1!=expectedHessian.end(); it1++, it2++){
EXPECT(assert_equal(it1->second, *it2));
Matrix R_i(2,2);
R_i(0,0) = buf[i+0];
R_i(0,1) = buf[i+1];
R_i(1,0) = buf[i+2];
R_i(1,1) = buf[i+3];
size_t i = 0;
for(; it1!=expectedHessian.end(); it1++, it2++){
//EXPECT(assert_equal(it1->second, *it2));
Matrix R_i(2,2);
R_i(0,0) = buf[i+0];
R_i(0,1) = buf[i+1];
R_i(1,0) = buf[i+2];
R_i(1,1) = buf[i+3];
Matrix actualH_i = R_i.transpose() * R_i;// i-th diagonal block
EXPECT(assert_equal(it1->second, actualH_i));
i += 4;
}
Matrix actualH_i = R_i.transpose() * R_i;// i-th diagonal block
EXPECT(assert_equal(it1->second, actualH_i));
i += 4;
}
}
/* ************************************************************************* */