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