158 lines
5.0 KiB
C++
158 lines
5.0 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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#include <boost/assign/std/set.hpp>
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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 <gtsam/base/Matrix.h>
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#include <tests/smallExample.h>
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#include <gtsam/inference/FactorGraph.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/nonlinear/Symbol.h>
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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( 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, keys )
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{
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Graph fg = createNonlinearFactorGraph();
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set<Key> actual = fg.keys();
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LONGS_EQUAL(3, actual.size());
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set<Key>::const_iterator it = actual.begin();
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LONGS_EQUAL(L(1), *(it++));
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LONGS_EQUAL(X(1), *(it++));
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LONGS_EQUAL(X(2), *(it++));
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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"; // For starting with x1,x2,l1
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Ordering expected; expected += L(1), X(2), X(1); // For starting with l1,x1,x2
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Graph nlfg = createNonlinearFactorGraph();
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SymbolicFactorGraph::shared_ptr symbolic;
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Ordering::shared_ptr ordering;
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boost::tie(symbolic, ordering) = nlfg.symbolic(createNoisyValues());
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Ordering actual = *nlfg.orderingCOLAMD(createNoisyValues());
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EXPECT(assert_equal(expected,actual));
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// Constrained ordering - put x2 at the end
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std::map<Key, int> constraints;
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constraints[X(2)] = 1;
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Ordering actualConstrained = *nlfg.orderingCOLAMDConstrained(createNoisyValues(), constraints);
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Ordering expectedConstrained; expectedConstrained += L(1), X(1), X(2);
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EXPECT(assert_equal(expectedConstrained, actualConstrained));
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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<FactorGraph<GaussianFactor> > linearized = fg.linearize(initial, *initial.orderingArbitrary());
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FactorGraph<GaussianFactor> 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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TEST( Graph, clone )
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{
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Graph fg = createNonlinearFactorGraph();
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Graph actClone = fg.clone();
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EXPECT(assert_equal(fg, actClone));
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for (size_t i=0; i<fg.size(); ++i)
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EXPECT(fg[i] != actClone[i]);
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}
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/* ************************************************************************* */
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TEST( Graph, rekey )
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{
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Graph init = createNonlinearFactorGraph();
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map<Key,Key> rekey_mapping;
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rekey_mapping.insert(make_pair(L(1), L(4)));
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Graph actRekey = init.rekey(rekey_mapping);
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// ensure deep clone
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LONGS_EQUAL(init.size(), actRekey.size());
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for (size_t i=0; i<init.size(); ++i)
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EXPECT(init[i] != actRekey[i]);
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Graph expRekey;
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// original measurements
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expRekey.push_back(init[0]);
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expRekey.push_back(init[1]);
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// updated measurements
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Point2 z3(0, -1), z4(-1.5, -1.);
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SharedDiagonal sigma0_2 = noiseModel::Isotropic::Sigma(2,0.2);
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expRekey.add(simulated2D::Measurement(z3, sigma0_2, X(1), L(4)));
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expRekey.add(simulated2D::Measurement(z4, sigma0_2, X(2), L(4)));
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EXPECT(assert_equal(expRekey, actRekey));
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}
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/* ************************************************************************* */
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int main() { TestResult tr; return TestRegistry::runAllTests(tr); }
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/* ************************************************************************* */
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