149 lines
4.4 KiB
C++
149 lines
4.4 KiB
C++
/**
|
|
* @file testBayesTree.cpp
|
|
* @brief Unit tests for Bayes Tree
|
|
* @author Frank Dellaert
|
|
*/
|
|
|
|
#include <boost/assign/std/list.hpp> // for operator +=
|
|
using namespace boost::assign;
|
|
|
|
#include <CppUnitLite/TestHarness.h>
|
|
|
|
#include "SymbolicBayesNet.h"
|
|
#include "GaussianBayesNet.h"
|
|
#include "Ordering.h"
|
|
#include "BayesTree-inl.h"
|
|
#include "smallExample.h"
|
|
|
|
using namespace gtsam;
|
|
|
|
// Conditionals for ASIA example from the tutorial with A and D evidence
|
|
SymbolicConditional::shared_ptr B(new SymbolicConditional("B")), L(
|
|
new SymbolicConditional("L", "B")), E(
|
|
new SymbolicConditional("E", "L", "B")), S(new SymbolicConditional("S",
|
|
"L", "B")), T(new SymbolicConditional("T", "E", "L")), X(
|
|
new SymbolicConditional("X", "E"));
|
|
|
|
/* ************************************************************************* */
|
|
TEST( BayesTree, Front )
|
|
{
|
|
SymbolicBayesNet f1;
|
|
f1.push_back(B);
|
|
f1.push_back(L);
|
|
SymbolicBayesNet f2;
|
|
f2.push_back(L);
|
|
f2.push_back(B);
|
|
CHECK(f1.equals(f1));
|
|
CHECK(!f1.equals(f2));
|
|
}
|
|
|
|
/* ************************************************************************* */
|
|
TEST( BayesTree, constructor )
|
|
{
|
|
// Create using insert
|
|
BayesTree<SymbolicConditional> bayesTree;
|
|
bayesTree.insert(B);
|
|
bayesTree.insert(L);
|
|
bayesTree.insert(E);
|
|
bayesTree.insert(S);
|
|
bayesTree.insert(T);
|
|
bayesTree.insert(X);
|
|
|
|
// Check Size
|
|
LONGS_EQUAL(6,bayesTree.size());
|
|
|
|
// Check root
|
|
BayesNet<SymbolicConditional> expected_root;
|
|
expected_root.push_back(E);
|
|
expected_root.push_back(L);
|
|
expected_root.push_back(B);
|
|
boost::shared_ptr<BayesNet<SymbolicConditional> > actual_root = bayesTree.root();
|
|
CHECK(assert_equal(expected_root,*actual_root));
|
|
|
|
// Create from symbolic Bayes chain in which we want to discover cliques
|
|
SymbolicBayesNet ASIA;
|
|
ASIA.push_back(X);
|
|
ASIA.push_back(T);
|
|
ASIA.push_back(S);
|
|
ASIA.push_back(E);
|
|
ASIA.push_back(L);
|
|
ASIA.push_back(B);
|
|
BayesTree<SymbolicConditional> bayesTree2(ASIA);
|
|
//bayesTree2.print("bayesTree2");
|
|
|
|
// Check whether the same
|
|
CHECK(assert_equal(bayesTree,bayesTree2));
|
|
}
|
|
|
|
/* ************************************************************************* *
|
|
Bayes tree for smoother with "natural" ordering:
|
|
x6 x7
|
|
x5 : x6
|
|
x4 : x5
|
|
x3 : x4
|
|
x2 : x3
|
|
x1 : x2
|
|
/* ************************************************************************* */
|
|
TEST( BayesTree, smoother )
|
|
{
|
|
// Create smoother with 7 nodes
|
|
LinearFactorGraph smoother = createSmoother(7);
|
|
Ordering ordering;
|
|
for (int t = 1; t <= 7; t++)
|
|
ordering.push_back(symbol('x', t));
|
|
|
|
// eliminate using the "natural" ordering
|
|
GaussianBayesNet::shared_ptr chordalBayesNet = smoother.eliminate(ordering);
|
|
|
|
// Create the Bayes tree
|
|
BayesTree<ConditionalGaussian> bayesTree(*chordalBayesNet);
|
|
LONGS_EQUAL(7,bayesTree.size());
|
|
}
|
|
|
|
/* ************************************************************************* *
|
|
Bayes tree for smoother with "nested dissection" ordering:
|
|
x5 x6 x4
|
|
x3 x2 : x4
|
|
x1 : x2
|
|
x7 : x6
|
|
/* ************************************************************************* */
|
|
TEST( BayesTree, balanced_smoother_marginals )
|
|
{
|
|
// Create smoother with 7 nodes
|
|
LinearFactorGraph smoother = createSmoother(7);
|
|
Ordering ordering;
|
|
ordering += "x1","x3","x5","x7","x2","x6","x4";
|
|
|
|
// eliminate using a "nested dissection" ordering
|
|
GaussianBayesNet::shared_ptr chordalBayesNet = smoother.eliminate(ordering);
|
|
|
|
// Create the Bayes tree
|
|
BayesTree<ConditionalGaussian> bayesTree(*chordalBayesNet);
|
|
LONGS_EQUAL(7,bayesTree.size());
|
|
|
|
// Check root clique
|
|
//BayesNet<ConditionalGaussian> expected_root;
|
|
//BayesNet<ConditionalGaussian> actual_root = bayesTree.root();
|
|
//CHECK(assert_equal(expected_root,actual_root));
|
|
|
|
// Check marginal on x1
|
|
double data1[] = { 1.0, 0.0,
|
|
0.0, 1.0};
|
|
Matrix R1 = Matrix_(2,2, data1);
|
|
Vector d1(2); d1(0) = -0.615385; d1(1) = 0;
|
|
Vector sigma1(2); sigma1(0) = 0.786153; sigma1(1) = 0.786153;
|
|
ConditionalGaussian expected("x1",d1, R1, sigma1);
|
|
ConditionalGaussian::shared_ptr actual = bayesTree.marginal<LinearFactor>("x1");
|
|
CHECK(assert_equal(expected,*actual,1e-4));
|
|
|
|
// JunctionTree is an undirected tree of cliques
|
|
// JunctionTree<ConditionalGaussian> marginals = bayesTree.marginals();
|
|
}
|
|
|
|
/* ************************************************************************* */
|
|
int main() {
|
|
TestResult tr;
|
|
return TestRegistry::runAllTests(tr);
|
|
}
|
|
/* ************************************************************************* */
|