/** Find the best total assignment - can be expensive */
Scheduler::sharedValues Scheduler::optimalAssignment() const {
DiscreteBayesNet::shared_ptr chordal = eliminate();
if (ISDEBUG("Scheduler::optimalAssignment")) {
DiscreteBayesNet::const_iterator it = chordal->end()-1;
const Student & student = students_.front();
cout << endl;
(*it)->print(student.name_);
}
gttic(my_optimize);
sharedValues mpe = chordal->optimize();
gttoc(my_optimize);
return mpe;
}
/* ************************************************************************* */
TEST(DiscreteBayesNet, Asia)
{
DiscreteBayesNet asia;
// DiscreteKey A("Asia"), S("Smoking"), T("Tuberculosis"), L("LungCancer"), B(
// "Bronchitis"), E("Either"), X("XRay"), D("Dyspnoea");
DiscreteKey A(0,2), S(4,2), T(3,2), L(6,2), B(7,2), E(5,2), X(2,2), D(1,2);
// TODO: make a version that doesn't use the parser
asia.add(A % "99/1");
asia.add(S % "50/50");
asia.add(T | A = "99/1 95/5");
asia.add(L | S = "99/1 90/10");
asia.add(B | S = "70/30 40/60");
asia.add((E | T, L) = "F T T T");
asia.add(X | E = "95/5 2/98");
// next lines are same as asia.add((D | E, B) = "9/1 2/8 3/7 1/9");
DiscreteConditional::shared_ptr actual =
boost::make_shared<DiscreteConditional>((D | E, B) = "9/1 2/8 3/7 1/9");
asia.push_back(actual);
// GTSAM_PRINT(asia);
// Convert to factor graph
DiscreteFactorGraph fg(asia);
// GTSAM_PRINT(fg);
LONGS_EQUAL(3,fg.back()->size());
Potentials::ADT expected(B & D & E, "0.9 0.3 0.1 0.7 0.2 0.1 0.8 0.9");
CHECK(assert_equal(expected,(Potentials::ADT)*actual));
// Create solver and eliminate
Ordering ordering;
ordering += Key(0),Key(1),Key(2),Key(3),Key(4),Key(5),Key(6),Key(7);
DiscreteBayesNet::shared_ptr chordal = fg.eliminateSequential(ordering);
// GTSAM_PRINT(*chordal);
DiscreteConditional expected2(B % "11/9");
CHECK(assert_equal(expected2,*chordal->back()));
// solve
DiscreteFactor::sharedValues actualMPE = chordal->optimize();
DiscreteFactor::Values expectedMPE;
insert(expectedMPE)(A.first, 0)(D.first, 0)(X.first, 0)(T.first, 0)(S.first,
0)(E.first, 0)(L.first, 0)(B.first, 0);
EXPECT(assert_equal(expectedMPE, *actualMPE));
// add evidence, we were in Asia and we have Dispnoea
fg.add(A, "0 1");
fg.add(D, "0 1");
// fg.product().dot("fg");
// solve again, now with evidence
DiscreteBayesNet::shared_ptr chordal2 = fg.eliminateSequential(ordering);
// GTSAM_PRINT(*chordal2);
DiscreteFactor::sharedValues actualMPE2 = chordal2->optimize();
DiscreteFactor::Values expectedMPE2;
insert(expectedMPE2)(A.first, 1)(D.first, 1)(X.first, 0)(T.first, 0)(S.first,
1)(E.first, 0)(L.first, 0)(B.first, 1);
EXPECT(assert_equal(expectedMPE2, *actualMPE2));
// now sample from it
DiscreteFactor::Values expectedSample;
SETDEBUG("DiscreteConditional::sample", false);
insert(expectedSample)(A.first, 1)(D.first, 1)(X.first, 0)(T.first, 0)(
S.first, 1)(E.first, 0)(L.first, 0)(B.first, 1);
DiscreteFactor::sharedValues actualSample = chordal2->sample();
EXPECT(assert_equal(expectedSample, *actualSample));
}