DiscreteBayesNet::mode method to get maximizing assignment

gtsam/discrete/DiscreteBayesNet.cpp

@@ -62,6 +62,14 @@ DiscreteValues DiscreteBayesNet::sample(DiscreteValues result) const {
   return result;
 }
 
+DiscreteValues DiscreteBayesNet::mode() const {
+  DiscreteValues result;
+  for (auto it = begin(); it != end(); ++it) {
+    result[(*it)->firstFrontalKey()] = (*it)->argmax(result);
+  }
+  return result;
+}
+
 /* *********************************************************************** */
 std::string DiscreteBayesNet::markdown(
     const KeyFormatter& keyFormatter,

gtsam/discrete/DiscreteBayesNet.h

@@ -124,6 +124,14 @@ class GTSAM_EXPORT DiscreteBayesNet: public BayesNet<DiscreteConditional> {
      */
     DiscreteValues sample(DiscreteValues given) const;
 
+    /**
+     * @brief Compute the discrete assignment which gives the highest
+     * probability for the DiscreteBayesNet.
+     *
+     * @return DiscreteValues
+     */
+    DiscreteValues mode() const;
+
     ///@}
     /// @name Wrapper support
     /// @{

gtsam/discrete/tests/testDiscreteBayesNet.cpp

@@ -122,6 +122,32 @@ TEST(DiscreteBayesNet, Asia) {
   EXPECT(assert_equal(expectedSample, actualSample));
 }
 
+/* ************************************************************************* */
+TEST(DiscreteBayesNet, Mode) {
+  DiscreteBayesNet asia;
+
+  asia.add(Asia, "99/1");
+  asia.add(Smoking % "50/50");  // Signature version
+
+  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");
+
+  DiscreteValues actual = asia.mode();
+  // NOTE: Examined the DBN and found the optimal assignment.
+  DiscreteValues expected{
+      {Asia.first, 0},       {Smoking.first, 0},    {Tuberculosis.first, 0},
+      {LungCancer.first, 0}, {Bronchitis.first, 0}, {Either.first, 0},
+      {XRay.first, 0},       {Dyspnea.first, 0},
+  };
+  EXPECT(assert_equal(expected, actual));
+}
+
 /* ************************************************************************* */
 TEST(DiscreteBayesNet, Sugar) {
   DiscreteKey T(0, 2), L(1, 2), E(2, 2), C(8, 3), S(7, 2);