148 lines
4.6 KiB
C++
148 lines
4.6 KiB
C++
/**
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* @file testSymbolicFactorGraph.cpp
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* @brief Unit tests for a symbolic Factor Graph
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* @author Frank Dellaert
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*/
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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 <gtsam/CppUnitLite/TestHarness.h>
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#define GTSAM_MAGIC_KEY
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#include <gtsam/slam/smallExample.h>
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#include <gtsam/inference/SymbolicFactorGraph.h>
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#include <gtsam/inference/Factor-inl.h>
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#include <gtsam/inference/BayesNet-inl.h>
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#include <gtsam/inference/FactorGraph-inl.h>
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#include <gtsam/inference/inference-inl.h>
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#include <gtsam/nonlinear/Ordering.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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/* ************************************************************************* */
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TEST( SymbolicFactorGraph, symbolicFactorGraph )
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{
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Ordering o; o += "x1","l1","x2";
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// construct expected symbolic graph
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SymbolicFactorGraph expected;
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expected.push_factor(o["x1"]);
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expected.push_factor(o["x1"],o["x2"]);
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expected.push_factor(o["x1"],o["l1"]);
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expected.push_factor(o["l1"],o["x2"]);
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// construct it from the factor graph
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GaussianFactorGraph factorGraph = createGaussianFactorGraph(o);
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SymbolicFactorGraph actual(factorGraph);
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CHECK(assert_equal(expected, actual));
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}
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///* ************************************************************************* */
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//TEST( SymbolicFactorGraph, findAndRemoveFactors )
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//{
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// // construct it from the factor graph graph
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// GaussianFactorGraph factorGraph = createGaussianFactorGraph();
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// SymbolicFactorGraph actual(factorGraph);
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// SymbolicFactor::shared_ptr f1 = actual[0];
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// SymbolicFactor::shared_ptr f3 = actual[2];
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// actual.findAndRemoveFactors("x2");
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//
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// // construct expected graph after find_factors_and_remove
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// SymbolicFactorGraph expected;
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// SymbolicFactor::shared_ptr null;
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// expected.push_back(f1);
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// expected.push_back(null);
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// expected.push_back(f3);
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// expected.push_back(null);
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//
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// CHECK(assert_equal(expected, actual));
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//}
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///* ************************************************************************* */
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//TEST( SymbolicFactorGraph, factors)
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//{
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// // create a test graph
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// GaussianFactorGraph factorGraph = createGaussianFactorGraph();
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// SymbolicFactorGraph fg(factorGraph);
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//
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// // ask for all factor indices connected to x1
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// list<size_t> x1_factors = fg.factors("x1");
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// int x1_indices[] = { 0, 1, 2 };
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// list<size_t> x1_expected(x1_indices, x1_indices + 3);
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// CHECK(x1_factors==x1_expected);
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//
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// // ask for all factor indices connected to x2
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// list<size_t> x2_factors = fg.factors("x2");
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// int x2_indices[] = { 1, 3 };
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// list<size_t> x2_expected(x2_indices, x2_indices + 2);
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// CHECK(x2_factors==x2_expected);
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//}
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///* ************************************************************************* */
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//TEST( SymbolicFactorGraph, removeAndCombineFactors )
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//{
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// // create a test graph
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// GaussianFactorGraph factorGraph = createGaussianFactorGraph();
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// SymbolicFactorGraph fg(factorGraph);
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//
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// // combine all factors connected to x1
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// SymbolicFactor::shared_ptr actual = removeAndCombineFactors(fg,"x1");
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//
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// // check result
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// SymbolicFactor expected("l1","x1","x2");
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// CHECK(assert_equal(expected,*actual));
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//}
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/* ************************************************************************* */
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TEST( SymbolicFactorGraph, eliminateOne )
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{
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Ordering o; o += "x1","l1","x2";
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// create a test graph
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GaussianFactorGraph factorGraph = createGaussianFactorGraph(o);
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SymbolicFactorGraph fg(factorGraph);
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// eliminate
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VariableIndex<> varindex(fg);
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Conditional::shared_ptr actual = Inference::EliminateOne(fg, varindex, o["x1"]);
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// create expected symbolic Conditional
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Conditional expected(o["x1"],o["l1"],o["x2"]);
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CHECK(assert_equal(expected,*actual));
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}
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/* ************************************************************************* */
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TEST( GaussianFactorGraph, eliminate )
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{
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Ordering o; o += "x2","l1","x1";
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// create expected Chordal bayes Net
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Conditional::shared_ptr x2(new Conditional(o["x2"], o["l1"], o["x1"]));
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Conditional::shared_ptr l1(new Conditional(o["l1"], o["x1"]));
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Conditional::shared_ptr x1(new Conditional(o["x1"]));
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SymbolicBayesNet 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 a test 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 = *Inference::Eliminate(fg);
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CHECK(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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