97 lines
2.8 KiB
C++
97 lines
2.8 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 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 <boost/assign/std/list.hpp>
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using namespace boost::assign;
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#include <gtsam/CppUnitLite/TestHarness.h>
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#define GTSAM_MAGIC_KEY
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#include <gtsam/base/Matrix.h>
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#include <gtsam/slam/smallExample.h>
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#include <gtsam/inference/FactorGraph-inl.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph-inl.h>
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using namespace gtsam;
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using namespace example;
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/* ************************************************************************* */
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TEST( Graph, equals )
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{
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Graph fg = createNonlinearFactorGraph();
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Graph fg2 = createNonlinearFactorGraph();
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CHECK( fg.equals(fg2) );
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}
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/* ************************************************************************* */
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TEST( Graph, error )
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{
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Graph fg = createNonlinearFactorGraph();
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Values c1 = createValues();
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double actual1 = fg.error(c1);
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DOUBLES_EQUAL( 0.0, actual1, 1e-9 );
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Values c2 = createNoisyValues();
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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( Graph, GET_ORDERING)
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{
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Ordering expected; expected += "x1","l1","x2";
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Graph nlfg = createNonlinearFactorGraph();
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Ordering actual = *nlfg.orderingCOLAMD(createNoisyValues());
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CHECK(assert_equal(expected,actual));
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}
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/* ************************************************************************* */
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TEST( Graph, probPrime )
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{
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Graph fg = createNonlinearFactorGraph();
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Values cfg = createValues();
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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( Graph, linearize )
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{
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Graph fg = createNonlinearFactorGraph();
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Values initial = createNoisyValues();
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boost::shared_ptr<GaussianFactorGraph> linearized = fg.linearize(initial, *initial.orderingArbitrary());
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GaussianFactorGraph expected = createGaussianFactorGraph(*initial.orderingArbitrary());
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CHECK(assert_equal(expected,*linearized)); // Needs correct linearizations
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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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