80 lines
		
	
	
		
			2.4 KiB
		
	
	
	
		
			C++
		
	
	
		
		
			
		
	
	
			80 lines
		
	
	
		
			2.4 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    testSymbolicBayesNetB.cpp | ||
|  |  * @brief   Unit tests for a symbolic Bayes chain | ||
|  |  * @author  Frank Dellaert | ||
|  |  */ | ||
|  | 
 | ||
|  | #include <boost/assign/list_inserter.hpp> // for 'insert()'
 | ||
|  | #include <boost/assign/std/list.hpp> // for operator +=
 | ||
|  | using namespace boost::assign; | ||
|  | 
 | ||
|  | #include <CppUnitLite/TestHarness.h>
 | ||
|  | 
 | ||
|  | #include <gtsam/base/Testable.h>
 | ||
|  | #include <gtsam/slam/smallExample.h>
 | ||
|  | #include <gtsam/inference/SymbolicFactorGraph.h>
 | ||
|  | #include <gtsam/inference/SymbolicSequentialSolver.h>
 | ||
|  | #include <gtsam/nonlinear/Ordering.h>
 | ||
|  | 
 | ||
|  | using namespace std; | ||
|  | using namespace gtsam; | ||
|  | using namespace example; | ||
|  | 
 | ||
|  | Key kx(size_t i) { return Symbol('x',i); } | ||
|  | Key kl(size_t i) { return Symbol('l',i); } | ||
|  | 
 | ||
|  | /* ************************************************************************* */ | ||
|  | TEST( SymbolicBayesNet, constructor ) | ||
|  | { | ||
|  |   Ordering o; o += kx(2),kl(1),kx(1); | ||
|  | 	// Create manually
 | ||
|  | 	IndexConditional::shared_ptr | ||
|  | 		x2(new IndexConditional(o[kx(2)],o[kl(1)], o[kx(1)])), | ||
|  | 		l1(new IndexConditional(o[kl(1)],o[kx(1)])), | ||
|  | 		x1(new IndexConditional(o[kx(1)])); | ||
|  | 	BayesNet<IndexConditional> expected; | ||
|  | 	expected.push_back(x2); | ||
|  | 	expected.push_back(l1); | ||
|  | 	expected.push_back(x1); | ||
|  | 
 | ||
|  | 	// Create from a factor graph
 | ||
|  | 	GaussianFactorGraph factorGraph = createGaussianFactorGraph(o); | ||
|  | 	SymbolicFactorGraph fg(factorGraph); | ||
|  | 
 | ||
|  | 	// eliminate it
 | ||
|  |   SymbolicBayesNet actual = *SymbolicSequentialSolver(fg).eliminate( | ||
|  | 			&EliminateSymbolic); | ||
|  | 
 | ||
|  |   CHECK(assert_equal(expected, actual)); | ||
|  | } | ||
|  | 
 | ||
|  | /* ************************************************************************* */ | ||
|  | TEST( SymbolicBayesNet, FromGaussian) { | ||
|  |   SymbolicBayesNet expected; | ||
|  |   expected.push_back(IndexConditional::shared_ptr(new IndexConditional(0, 1))); | ||
|  |   expected.push_back(IndexConditional::shared_ptr(new IndexConditional(1))); | ||
|  | 
 | ||
|  |   GaussianBayesNet gbn = createSmallGaussianBayesNet(); | ||
|  |   SymbolicBayesNet actual(gbn); | ||
|  | 
 | ||
|  |   EXPECT(assert_equal(expected, actual)); | ||
|  | } | ||
|  | 
 | ||
|  | /* ************************************************************************* */ | ||
|  | int main() { | ||
|  | 	TestResult tr; | ||
|  | 	return TestRegistry::runAllTests(tr); | ||
|  | } | ||
|  | /* ************************************************************************* */ |