163 lines
5.0 KiB
C++
163 lines
5.0 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file testPCGSolver.cpp
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* @brief Unit tests for PCGSolver class
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* @author Yong-Dian Jian
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* @date Aug 06, 2014
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*/
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#include <tests/smallExample.h>
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#include <gtsam/slam/PriorFactor.h>
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#include <gtsam/slam/BetweenFactor.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/nonlinear/GaussNewtonOptimizer.h>
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#include <gtsam/nonlinear/DoglegOptimizer.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/linear/GaussianFactorGraph.h>
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#include <gtsam/linear/PCGSolver.h>
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#include <gtsam/linear/Preconditioner.h>
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#include <gtsam/linear/SubgraphPreconditioner.h>
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#include <gtsam/linear/NoiseModel.h>
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#include <gtsam/inference/Symbol.h>
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#include <gtsam/geometry/Pose2.h>
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#include <gtsam/base/Matrix.h>
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#include <CppUnitLite/TestHarness.h>
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#include <boost/shared_ptr.hpp>
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#include <boost/assign/std/list.hpp> // for operator +=
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using namespace boost::assign;
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#include <iostream>
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#include <fstream>
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using namespace std;
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using namespace gtsam;
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const double tol = 1e-3;
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using symbol_shorthand::X;
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using symbol_shorthand::L;
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/* ************************************************************************* */
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// Test cholesky decomposition
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TEST( PCGSolver, llt ) {
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Matrix R = (Matrix(3,3) <<
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1., -1., -1.,
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0., 2., -1.,
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0., 0., 1.).finished();
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Matrix AtA = R.transpose() * R;
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Vector Rvector = (Vector(9) << 1., -1., -1.,
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0., 2., -1.,
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0., 0., 1.).finished();
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// Vector Rvector = (Vector(6) << 1., -1., -1.,
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// 2., -1.,
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// 1.).finished();
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Vector b = Vector3(1., 2., 3.);
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Vector x = Vector3(6.5, 2.5, 3.) ;
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/* test cholesky */
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Matrix Rhat = AtA.llt().matrixL().transpose();
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EXPECT(assert_equal(R, Rhat, 1e-5));
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/* test backward substitution */
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Vector xhat = Rhat.triangularView<Eigen::Upper>().solve(b);
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EXPECT(assert_equal(x, xhat, 1e-5));
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/* test in-place back substitution */
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xhat = b;
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Rhat.triangularView<Eigen::Upper>().solveInPlace(xhat);
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EXPECT(assert_equal(x, xhat, 1e-5));
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/* test triangular matrix map */
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Eigen::Map<Eigen::MatrixXd> Radapter(Rvector.data(), 3, 3);
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xhat = Radapter.transpose().triangularView<Eigen::Upper>().solve(b);
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EXPECT(assert_equal(x, xhat, 1e-5));
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}
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/* ************************************************************************* */
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// Test Dummy Preconditioner
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TEST( PCGSolver, dummy )
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{
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LevenbergMarquardtParams paramsPCG;
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paramsPCG.linearSolverType = LevenbergMarquardtParams::Iterative;
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PCGSolverParameters::shared_ptr pcg = boost::make_shared<PCGSolverParameters>();
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pcg->preconditioner_ = boost::make_shared<DummyPreconditionerParameters>();
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paramsPCG.iterativeParams = pcg;
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NonlinearFactorGraph fg = example::createReallyNonlinearFactorGraph();
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Point2 x0(10,10);
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Values c0;
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c0.insert(X(1), x0);
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Values actualPCG = LevenbergMarquardtOptimizer(fg, c0, paramsPCG).optimize();
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DOUBLES_EQUAL(0,fg.error(actualPCG),tol);
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}
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/* ************************************************************************* */
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// Test Block-Jacobi Precondioner
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TEST( PCGSolver, blockjacobi )
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{
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LevenbergMarquardtParams paramsPCG;
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paramsPCG.linearSolverType = LevenbergMarquardtParams::Iterative;
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PCGSolverParameters::shared_ptr pcg = boost::make_shared<PCGSolverParameters>();
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pcg->preconditioner_ = boost::make_shared<BlockJacobiPreconditionerParameters>();
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paramsPCG.iterativeParams = pcg;
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NonlinearFactorGraph fg = example::createReallyNonlinearFactorGraph();
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Point2 x0(10,10);
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Values c0;
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c0.insert(X(1), x0);
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Values actualPCG = LevenbergMarquardtOptimizer(fg, c0, paramsPCG).optimize();
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DOUBLES_EQUAL(0,fg.error(actualPCG),tol);
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}
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/* ************************************************************************* */
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// Test Incremental Subgraph PCG Solver
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TEST( PCGSolver, subgraph )
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{
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LevenbergMarquardtParams paramsPCG;
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paramsPCG.linearSolverType = LevenbergMarquardtParams::Iterative;
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PCGSolverParameters::shared_ptr pcg = boost::make_shared<PCGSolverParameters>();
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pcg->preconditioner_ = boost::make_shared<SubgraphPreconditionerParameters>();
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paramsPCG.iterativeParams = pcg;
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NonlinearFactorGraph fg = example::createReallyNonlinearFactorGraph();
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Point2 x0(10,10);
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Values c0;
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c0.insert(X(1), x0);
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Values actualPCG = LevenbergMarquardtOptimizer(fg, c0, paramsPCG).optimize();
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DOUBLES_EQUAL(0,fg.error(actualPCG),tol);
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}
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/* ************************************************************************* */
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int main() {
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TestResult tr;
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return TestRegistry::runAllTests(tr);
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}
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