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								/** 
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								 * @file    testNonlinearFactorGraph.cpp
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								 * @brief   Unit tests for Non-Linear Factor Graph
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								 * @brief   testNonlinearFactorGraph
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								 * @author  Carlos Nieto
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								 * @author  Christian Potthast
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								 */
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								/*STL/C++*/
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								#include <iostream>
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								using namespace std;
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								#include <CppUnitLite/TestHarness.h>
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								#include "Matrix.h"
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								#include "smallExample.h"
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								#include "FactorGraph-inl.h"
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								#include "NonlinearFactorGraph-inl.h"
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								using namespace gtsam;
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								/* ************************************************************************* */
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								TEST( ExampleNonlinearFactorGraph, equals )
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								{
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									ExampleNonlinearFactorGraph fg = createNonlinearFactorGraph();
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									ExampleNonlinearFactorGraph fg2 = createNonlinearFactorGraph();
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									CHECK( fg.equals(fg2) );
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								}
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								/* ************************************************************************* */
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								TEST( ExampleNonlinearFactorGraph, error )
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								{
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									ExampleNonlinearFactorGraph fg = createNonlinearFactorGraph();
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									VectorConfig c1 = createConfig();
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									double actual1 = fg.error(c1);
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									DOUBLES_EQUAL( 0.0, actual1, 1e-9 );
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									VectorConfig c2 = createNoisyConfig();
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									double actual2 = fg.error(c2);
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									DOUBLES_EQUAL( 5.625, actual2, 1e-9 );
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								}
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								/* ************************************************************************* */
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								TEST( ExampleNonlinearFactorGraph, probPrime )
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								{
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									ExampleNonlinearFactorGraph fg = createNonlinearFactorGraph();
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									VectorConfig cfg = createConfig();
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									// evaluate the probability of the factor graph
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									double actual = fg.probPrime(cfg);
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									double expected = 1.0;
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									DOUBLES_EQUAL(expected,actual,0);
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								}
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								/* ************************************************************************* */
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								TEST( ExampleNonlinearFactorGraph, linearize )
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								{
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									ExampleNonlinearFactorGraph fg = createNonlinearFactorGraph();
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									VectorConfig initial = createNoisyConfig();
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									GaussianFactorGraph linearized = fg.linearize(initial);
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									GaussianFactorGraph expected = createGaussianFactorGraph();
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									CHECK(expected.equals(linearized));
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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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