gtsam/tests/testInference.cpp

81 lines
3.0 KiB
C++

/* ----------------------------------------------------------------------------
* 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 testInference.cpp
* @brief Unit tests for functionality declared in inference.h
* @author Frank Dellaert
*/
#include <CppUnitLite/TestHarness.h>
// Magically casts strings like "x3" to a Symbol('x',3) key, see Key.h
#define GTSAM_MAGIC_KEY
#include <gtsam/linear/GaussianSequentialSolver.h>
#include <gtsam/slam/smallExample.h>
#include <gtsam/slam/planarSLAM.h>
using namespace std;
using namespace gtsam;
/* ************************************************************************* */
// The tests below test the *generic* inference algorithms. Some of these have
// specialized versions in the derived classes GaussianFactorGraph etc...
/* ************************************************************************* */
/* ************************************************************************* */
TEST( Inference, marginals )
{
using namespace example;
// create and marginalize a small Bayes net on "x"
GaussianBayesNet cbn = createSmallGaussianBayesNet();
vector<Index> xvar; xvar.push_back(0);
GaussianBayesNet actual = *GaussianSequentialSolver(
*GaussianSequentialSolver(GaussianFactorGraph(cbn)).jointFactorGraph(xvar)).eliminate();
// expected is just scalar Gaussian on x
GaussianBayesNet expected = scalarGaussian(0, 4, sqrt(2));
CHECK(assert_equal(expected,actual));
}
/* ************************************************************************* */
TEST( Inference, marginals2)
{
using namespace gtsam::planarSLAM;
Graph fg;
SharedDiagonal poseModel(sharedSigma(3, 0.1));
SharedDiagonal pointModel(sharedSigma(3, 0.1));
fg.addPrior(PoseKey(0), Pose2(), poseModel);
fg.addOdometry(PoseKey(0), PoseKey(1), Pose2(1.0,0.0,0.0), poseModel);
fg.addOdometry(PoseKey(1), PoseKey(2), Pose2(1.0,0.0,0.0), poseModel);
fg.addBearingRange(PoseKey(0), PointKey(0), Rot2(), 1.0, pointModel);
fg.addBearingRange(PoseKey(1), PointKey(0), Rot2(), 1.0, pointModel);
fg.addBearingRange(PoseKey(2), PointKey(0), Rot2(), 1.0, pointModel);
Values init;
init.insert(PoseKey(0), Pose2(0.0,0.0,0.0));
init.insert(PoseKey(1), Pose2(1.0,0.0,0.0));
init.insert(PoseKey(2), Pose2(2.0,0.0,0.0));
init.insert(PointKey(0), Point2(1.0,1.0));
Ordering ordering(*fg.orderingCOLAMD(init));
FactorGraph<GaussianFactor>::shared_ptr gfg(fg.linearize(init, ordering));
GaussianMultifrontalSolver solver(*gfg);
solver.marginalFactor(ordering[PointKey(0)]);
}
/* ************************************************************************* */
int main() { TestResult tr; return TestRegistry::runAllTests(tr);}
/* ************************************************************************* */