gtsam/tests/testNonlinearOptimizer.cpp

/* ----------------------------------------------------------------------------

 * 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    testNonlinearOptimizer.cpp
 * @brief   Unit tests for NonlinearOptimizer class
 * @author  Frank Dellaert
 */

#include <iostream>
using namespace std;

#include <boost/assign/std/list.hpp> // for operator +=
using namespace boost::assign;

#include <CppUnitLite/TestHarness.h>

#include <boost/shared_ptr.hpp>
using namespace boost;

#define GTSAM_MAGIC_KEY

#include <gtsam/base/Matrix.h>
#include <gtsam/slam/smallExample.h>
#include <gtsam/slam/pose2SLAM.h>
#include <gtsam/linear/GaussianFactorGraph.h>
#include <gtsam/linear/NoiseModel.h>

// template definitions
#include <gtsam/nonlinear/NonlinearFactorGraph-inl.h>
#include <gtsam/nonlinear/NonlinearOptimizer-inl.h>
//#include <gtsam/linear/SubgraphSolver-inl.h>

using namespace gtsam;

const double tol = 1e-5;

typedef NonlinearOptimizer<example::Graph,example::Values> Optimizer;

/* ************************************************************************* */
TEST( NonlinearOptimizer, linearizeAndOptimizeForDelta )
{
	shared_ptr<example::Graph> fg(new example::Graph(
			example::createNonlinearFactorGraph()));
	Optimizer::shared_values initial = example::sharedNoisyValues();

	// Expected values structure is the difference between the noisy config
	// and the ground-truth config. One step only because it's linear !
  Ordering ord1; ord1 += "x2","l1","x1";
	VectorValues expected(initial->dims(ord1));
	Vector dl1(2);
	dl1(0) = -0.1;
	dl1(1) = 0.1;
	expected[ord1["l1"]] = dl1;
	Vector dx1(2);
	dx1(0) = -0.1;
	dx1(1) = -0.1;
	expected[ord1["x1"]] = dx1;
	Vector dx2(2);
	dx2(0) = 0.1;
	dx2(1) = -0.2;
	expected[ord1["x2"]] = dx2;

	// Check one ordering
	Optimizer optimizer1(fg, initial, Optimizer::shared_ordering(new Ordering(ord1)));

	VectorValues actual1 = optimizer1.linearizeAndOptimizeForDelta();
	CHECK(assert_equal(actual1,expected));

// SL-FIX	// Check another
//	shared_ptr<Ordering> ord2(new Ordering());
//	*ord2 += "x1","x2","l1";
//	solver = Optimizer::shared_solver(new Optimizer::solver(ord2));
//	Optimizer optimizer2(fg, initial, solver);
//
//	VectorValues actual2 = optimizer2.linearizeAndOptimizeForDelta();
//	CHECK(assert_equal(actual2,expected));
//
//	// And yet another...
//	shared_ptr<Ordering> ord3(new Ordering());
//	*ord3 += "l1","x1","x2";
//	solver = Optimizer::shared_solver(new Optimizer::solver(ord3));
//	Optimizer optimizer3(fg, initial, solver);
//
//	VectorValues actual3 = optimizer3.linearizeAndOptimizeForDelta();
//	CHECK(assert_equal(actual3,expected));
//
//	// More...
//	shared_ptr<Ordering> ord4(new Ordering());
//	*ord4 += "x1","x2", "l1";
//	solver = Optimizer::shared_solver(new Optimizer::solver(ord4));
//	Optimizer optimizer4(fg, initial, solver);
//
//	VectorValues actual4 = optimizer4.linearizeAndOptimizeForDelta();
//	CHECK(assert_equal(actual4,expected));
}

/* ************************************************************************* */
TEST( NonlinearOptimizer, iterateLM )
{
	// really non-linear factor graph
  shared_ptr<example::Graph> fg(new example::Graph(
  		example::createReallyNonlinearFactorGraph()));

	// config far from minimum
	Point2 x0(3,0);
	boost::shared_ptr<example::Values> config(new example::Values);
	config->insert(simulated2D::PoseKey(1), x0);

	// ordering
	shared_ptr<Ordering> ord(new Ordering());
	ord->push_back("x1");

	// create initial optimization state, with lambda=0
	Optimizer optimizer(fg, config, ord, 0.);

	// normal iterate
	Optimizer iterated1 = optimizer.iterate();

	// LM iterate with lambda 0 should be the same
	Optimizer iterated2 = optimizer.iterateLM();

	// Try successive iterates. TODO: ugly pointers, better way ?
	Optimizer *pointer = new Optimizer(iterated2);
	for (int i=0;i<10;i++) {
		Optimizer* newOptimizer = new Optimizer(pointer->iterateLM());
		delete pointer;
		pointer = newOptimizer;
	}
	delete(pointer);

	CHECK(assert_equal(*iterated1.values(), *iterated2.values(), 1e-9));
}

/* ************************************************************************* */
TEST( NonlinearOptimizer, optimize )
{
  shared_ptr<example::Graph> fg(new example::Graph(
  		example::createReallyNonlinearFactorGraph()));

	// test error at minimum
	Point2 xstar(0,0);
	example::Values cstar;
	cstar.insert(simulated2D::PoseKey(1), xstar);
	DOUBLES_EQUAL(0.0,fg->error(cstar),0.0);

	// test error at initial = [(1-cos(3))^2 + (sin(3))^2]*50 =
	Point2 x0(3,3);
	boost::shared_ptr<example::Values> c0(new example::Values);
	c0->insert(simulated2D::PoseKey(1), x0);
	DOUBLES_EQUAL(199.0,fg->error(*c0),1e-3);

	// optimize parameters
	shared_ptr<Ordering> ord(new Ordering());
	ord->push_back("x1");
	double relativeThreshold = 1e-5;
	double absoluteThreshold = 1e-5;

	// initial optimization state is the same in both cases tested
	Optimizer optimizer(fg, c0, ord);

	// Gauss-Newton
	Optimizer actual1 = optimizer.gaussNewton(relativeThreshold,
			absoluteThreshold);
	DOUBLES_EQUAL(0,fg->error(*(actual1.values())),tol);

	// Levenberg-Marquardt
	Optimizer actual2 = optimizer.levenbergMarquardt(relativeThreshold,
			absoluteThreshold, Optimizer::Parameters::SILENT);
	DOUBLES_EQUAL(0,fg->error(*(actual2.values())),tol);
}

/* ************************************************************************* */
TEST( NonlinearOptimizer, SimpleLMOptimizer )
{
	shared_ptr<example::Graph> fg(new example::Graph(
			example::createReallyNonlinearFactorGraph()));

	Point2 x0(3,3);
	boost::shared_ptr<example::Values> c0(new example::Values);
	c0->insert(simulated2D::PoseKey(1), x0);

	Optimizer::shared_values actual = Optimizer::optimizeLM(fg, c0);
	DOUBLES_EQUAL(0,fg->error(*actual),tol);
}

/* ************************************************************************* */
TEST( NonlinearOptimizer, SimpleLMOptimizer_noshared )
{
	example::Graph fg = example::createReallyNonlinearFactorGraph();

	Point2 x0(3,3);
	example::Values c0;
	c0.insert(simulated2D::PoseKey(1), x0);

	Optimizer::shared_values actual = Optimizer::optimizeLM(fg, c0);
	DOUBLES_EQUAL(0,fg.error(*actual),tol);
}

/* ************************************************************************* */
TEST( NonlinearOptimizer, SimpleGNOptimizer )
{
	shared_ptr<example::Graph> fg(new example::Graph(
			example::createReallyNonlinearFactorGraph()));

	Point2 x0(3,3);
	boost::shared_ptr<example::Values> c0(new example::Values);
	c0->insert(simulated2D::PoseKey(1), x0);

	Optimizer::shared_values actual = Optimizer::optimizeGN(fg, c0);
	DOUBLES_EQUAL(0,fg->error(*actual),tol);
}

/* ************************************************************************* */
TEST( NonlinearOptimizer, SimpleGNOptimizer_noshared )
{
	example::Graph fg = example::createReallyNonlinearFactorGraph();

	Point2 x0(3,3);
	example::Values c0;
	c0.insert(simulated2D::PoseKey(1), x0);

	Optimizer::shared_values actual = Optimizer::optimizeGN(fg, c0);
	DOUBLES_EQUAL(0,fg.error(*actual),tol);
}

/* ************************************************************************* */
TEST( NonlinearOptimizer, Factorization )
{
	typedef NonlinearOptimizer<Pose2Graph, Pose2Values, GaussianFactorGraph, GaussianSequentialSolver > Optimizer;

	boost::shared_ptr<Pose2Values> config(new Pose2Values);
	config->insert(1, Pose2(0.,0.,0.));
	config->insert(2, Pose2(1.5,0.,0.));

	boost::shared_ptr<Pose2Graph> graph(new Pose2Graph);
	graph->addPrior(1, Pose2(0.,0.,0.), noiseModel::Isotropic::Sigma(3, 1e-10));
	graph->addConstraint(1,2, Pose2(1.,0.,0.), noiseModel::Isotropic::Sigma(3, 1));

	boost::shared_ptr<Ordering> ordering(new Ordering);
	ordering->push_back(Pose2Values::Key(1));
	ordering->push_back(Pose2Values::Key(2));

	Optimizer optimizer(graph, config, ordering);
	Optimizer optimized = optimizer.iterateLM();

	Pose2Values expected;
	expected.insert(1, Pose2(0.,0.,0.));
	expected.insert(2, Pose2(1.,0.,0.));
	CHECK(assert_equal(expected, *optimized.values(), 1e-5));
}

///* ************************************************************************* */
// SL-FIX TEST( NonlinearOptimizer, SubgraphSolver )
//{
//	using namespace pose2SLAM;
//	typedef SubgraphSolver<Graph, Values> Solver;
//	typedef NonlinearOptimizer<Graph, Values, SubgraphPreconditioner, Solver> Optimizer;
//
//	// Create a graph
//	boost::shared_ptr<Graph> graph(new Graph);
//	graph->addPrior(1, Pose2(0., 0., 0.), noiseModel::Isotropic::Sigma(3, 1e-10));
//	graph->addConstraint(1, 2, Pose2(1., 0., 0.), noiseModel::Isotropic::Sigma(3, 1));
//
//	// Create an initial config
//	boost::shared_ptr<Values> config(new Values);
//	config->insert(1, Pose2(0., 0., 0.));
//	config->insert(2, Pose2(1.5, 0., 0.));
//
//	// Create solver and optimizer
//	Optimizer::shared_solver solver
//		(new SubgraphSolver<Graph, Values> (*graph, *config));
//	Optimizer optimizer(graph, config, solver);
//
//	// Optimize !!!!
//	double relativeThreshold = 1e-5;
//	double absoluteThreshold = 1e-5;
//	Optimizer optimized = optimizer.gaussNewton(relativeThreshold,
//			absoluteThreshold, Optimizer::SILENT);
//
//	// Check solution
//	Values expected;
//	expected.insert(1, Pose2(0., 0., 0.));
//	expected.insert(2, Pose2(1., 0., 0.));
//	CHECK(assert_equal(expected, *optimized.values(), 1e-5));
//}

/* ************************************************************************* */
// SL-FIX TEST( NonlinearOptimizer, MultiFrontalSolver )
//{
//	shared_ptr<example::Graph> fg(new example::Graph(
//			example::createNonlinearFactorGraph()));
//	Optimizer::shared_values initial = example::sharedNoisyValues();
//
//	Values expected;
//	expected.insert(simulated2D::PoseKey(1), Point2(0.0, 0.0));
//	expected.insert(simulated2D::PoseKey(2), Point2(1.5, 0.0));
//	expected.insert(simulated2D::PointKey(1), Point2(0.0, -1.0));
//
//	Optimizer::shared_solver solver;
//
//	// Check one ordering
//	shared_ptr<Ordering> ord1(new Ordering());
//	*ord1 += "x2","l1","x1";
//	solver = Optimizer::shared_solver(new Optimizer::solver(ord1));
//	Optimizer optimizer1(fg, initial, solver);
//
//	Values actual = optimizer1.levenbergMarquardt();
//	CHECK(assert_equal(actual,expected));
//}


/* ************************************************************************* */
int main() {
	TestResult tr;
	return TestRegistry::runAllTests(tr);
}
/* ************************************************************************* */