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