| 1 | /* ---------------------------------------------------------------------------- |
| 2 | |
| 3 | * GTSAM Copyright 2010, Georgia Tech Research Corporation, |
| 4 | * Atlanta, Georgia 30332-0415 |
| 5 | * All Rights Reserved |
| 6 | * Authors: Frank Dellaert, et al. (see THANKS for the full author list) |
| 7 | |
| 8 | * See LICENSE for the license information |
| 9 | |
| 10 | * -------------------------------------------------------------------------- */ |
| 11 | |
| 12 | /** |
| 13 | * @file DiscreteBayesNetExample.cpp |
| 14 | * @brief Discrete Bayes Net example with famous Asia Bayes Network |
| 15 | * @author Frank Dellaert |
| 16 | * @date JULY 10, 2020 |
| 17 | */ |
| 18 | |
| 19 | #include <gtsam/discrete/DiscreteFactorGraph.h> |
| 20 | #include <gtsam/discrete/DiscreteMarginals.h> |
| 21 | #include <gtsam/inference/BayesNet.h> |
| 22 | |
| 23 | #include <iomanip> |
| 24 | |
| 25 | using namespace std; |
| 26 | using namespace gtsam; |
| 27 | |
| 28 | int main(int argc, char **argv) { |
| 29 | DiscreteBayesNet asia; |
| 30 | DiscreteKey Asia(0, 2), Smoking(4, 2), Tuberculosis(3, 2), LungCancer(6, 2), |
| 31 | Bronchitis(7, 2), Either(5, 2), XRay(2, 2), Dyspnea(1, 2); |
| 32 | asia.add(args: Asia % "99/1" ); |
| 33 | asia.add(args: Smoking % "50/50" ); |
| 34 | |
| 35 | asia.add(args&: Tuberculosis | Asia = "99/1 95/5" ); |
| 36 | asia.add(args&: LungCancer | Smoking = "99/1 90/10" ); |
| 37 | asia.add(args&: Bronchitis | Smoking = "70/30 40/60" ); |
| 38 | |
| 39 | asia.add(args&: (Either | Tuberculosis, LungCancer) = "F T T T" ); |
| 40 | |
| 41 | asia.add(args&: XRay | Either = "95/5 2/98" ); |
| 42 | asia.add(args&: (Dyspnea | Either, Bronchitis) = "9/1 2/8 3/7 1/9" ); |
| 43 | |
| 44 | // print |
| 45 | vector<string> pretty = {"Asia" , "Dyspnea" , "XRay" , "Tuberculosis" , |
| 46 | "Smoking" , "Either" , "LungCancer" , "Bronchitis" }; |
| 47 | auto formatter = [pretty](Key key) { return pretty[key]; }; |
| 48 | asia.print(s: "Asia" , formatter); |
| 49 | |
| 50 | // Convert to factor graph |
| 51 | DiscreteFactorGraph fg(asia); |
| 52 | |
| 53 | // Create solver and eliminate |
| 54 | const Ordering ordering{0, 1, 2, 3, 4, 5, 6, 7}; |
| 55 | |
| 56 | // solve |
| 57 | auto mpe = fg.optimize(); |
| 58 | GTSAM_PRINT(mpe); |
| 59 | |
| 60 | // We can also build a Bayes tree (directed junction tree). |
| 61 | // The elimination order above will do fine: |
| 62 | auto bayesTree = fg.eliminateMultifrontal(ordering); |
| 63 | bayesTree->print(s: "bayesTree" , keyFormatter: formatter); |
| 64 | |
| 65 | // add evidence, we were in Asia and we have dyspnea |
| 66 | fg.add(args&: Asia, args: "0 1" ); |
| 67 | fg.add(args&: Dyspnea, args: "0 1" ); |
| 68 | |
| 69 | // solve again, now with evidence |
| 70 | auto mpe2 = fg.optimize(); |
| 71 | GTSAM_PRINT(mpe2); |
| 72 | |
| 73 | // We can also sample from it |
| 74 | DiscreteBayesNet::shared_ptr chordal = fg.eliminateSequential(ordering); |
| 75 | cout << "\n10 samples:" << endl; |
| 76 | for (size_t i = 0; i < 10; i++) { |
| 77 | auto sample = chordal->sample(); |
| 78 | GTSAM_PRINT(sample); |
| 79 | } |
| 80 | return 0; |
| 81 | } |
| 82 | |