/* ---------------------------------------------------------------------------- * GTSAM Copyright 2010, Georgia Tech Research Corporation, * Atlanta, Georgia 30332-0415 * All Rights Reserved * Authors: Frank Dellaert, et al. (see THANKS for the full author list) * See LICENSE for the license information * -------------------------------------------------------------------------- */ /** * @file testPreconditioner.cpp * @brief Unit tests for Preconditioners * @author Sungtae An * @date Nov 6, 2014 **/ #include #include #include #include #include #include using namespace std; using namespace gtsam; /* ************************************************************************* */ static GaussianFactorGraph createSimpleGaussianFactorGraph() { GaussianFactorGraph fg; SharedDiagonal unit2 = noiseModel::Unit::Create(2); // linearized prior on x1: c[_x1_]+x1=0 i.e. x1=-c[_x1_] fg += JacobianFactor(2, 10*eye(2), -1.0*ones(2), unit2); // odometry between x1 and x2: x2-x1=[0.2;-0.1] fg += JacobianFactor(2, -10*eye(2), 0, 10*eye(2), (Vector(2) << 2.0, -1.0), unit2); // measurement between x1 and l1: l1-x1=[0.0;0.2] fg += JacobianFactor(2, -5*eye(2), 1, 5*eye(2), (Vector(2) << 0.0, 1.0), unit2); // measurement between x2 and l1: l1-x2=[-0.2;0.3] fg += JacobianFactor(0, -5*eye(2), 1, 5*eye(2), (Vector(2) << -1.0, 1.5), unit2); return fg; } /* ************************************************************************* */ // Copy of BlockJacobiPreconditioner::build std::vector buildBlocks( const GaussianFactorGraph &gfg, const KeyInfo &keyInfo) { const size_t n = keyInfo.size(); std::vector dims_ = keyInfo.colSpec(); /* prepare the buffer of block diagonals */ std::vector blocks; blocks.reserve(n); /* allocate memory for the factorization of block diagonals */ size_t nnz = 0; for ( size_t i = 0 ; i < n ; ++i ) { const size_t dim = dims_[i]; blocks.push_back(Matrix::Zero(dim, dim)); // nnz += (((dim)*(dim+1)) >> 1); // d*(d+1) / 2 ; nnz += dim*dim; } /* compute the block diagonal by scanning over the factors */ BOOST_FOREACH ( const GaussianFactor::shared_ptr &gf, gfg ) { if ( JacobianFactor::shared_ptr jf = boost::dynamic_pointer_cast(gf) ) { for ( JacobianFactor::const_iterator it = jf->begin() ; it != jf->end() ; ++it ) { const KeyInfoEntry &entry = keyInfo.find(*it)->second; const Matrix &Ai = jf->getA(it); blocks[entry.index()] += (Ai.transpose() * Ai); } } else if ( HessianFactor::shared_ptr hf = boost::dynamic_pointer_cast(gf) ) { for ( HessianFactor::const_iterator it = hf->begin() ; it != hf->end() ; ++it ) { const KeyInfoEntry &entry = keyInfo.find(*it)->second; const Matrix &Hii = hf->info(it, it).selfadjointView(); blocks[entry.index()] += Hii; } } else { throw invalid_argument("BlockJacobiPreconditioner::build gfg contains a factor that is neither a JacobianFactor nor a HessianFactor."); } } return blocks; } /* ************************************************************************* */ TEST( Preconditioner, buildBlocks ) { // Create simple Gaussian factor graph and initial values GaussianFactorGraph gfg = createSimpleGaussianFactorGraph(); Values initial; initial.insert(0,Point2(4, 5)); initial.insert(1,Point2(0, 1)); initial.insert(2,Point2(-5, 7)); // Expected Hessian block diagonal matrices std::map expectedHessian =gfg.hessianBlockDiagonal(); // Actual Hessian block diagonal matrices from BlockJacobiPreconditioner::build std::vector actualHessian = buildBlocks(gfg, KeyInfo(gfg)); // Compare the number of block diagonal matrices EXPECT_LONGS_EQUAL(expectedHessian.size(), actualHessian.size()); // Compare the values of matrices std::map::const_iterator it1 = expectedHessian.begin(); std::vector::const_iterator it2 = actualHessian.begin(); for(; it1!=expectedHessian.end(); it1++, it2++) EXPECT(assert_equal(it1->second, *it2)); } /* ************************************************************************* */ int main() { TestResult tr; return TestRegistry::runAllTests(tr); } /* ************************************************************************* */