deprecated optimize

gtsam/discrete/DiscreteBayesNet.cpp

@@ -43,6 +43,7 @@ double DiscreteBayesNet::evaluate(const DiscreteValues& values) const {
 }
 
 /* ************************************************************************* */
+#ifdef GTSAM_ALLOW_DEPRECATED_SINCE_V42
 DiscreteValues DiscreteBayesNet::optimize() const {
   DiscreteValues result;
   return optimize(result);
@@ -50,10 +51,16 @@ DiscreteValues DiscreteBayesNet::optimize() const {
 
 DiscreteValues DiscreteBayesNet::optimize(DiscreteValues result) const {
   // solve each node in turn in topological sort order (parents first)
+#ifdef _MSC_VER
+#pragma message("DiscreteBayesNet::optimize (deprecated) does not compute MPE!")
+#else
+#warning "DiscreteBayesNet::optimize (deprecated) does not compute MPE!"
+#endif
   for (auto conditional : boost::adaptors::reverse(*this))
     conditional->solveInPlace(&result);
   return result;
 }
+#endif
 
 /* ************************************************************************* */
 DiscreteValues DiscreteBayesNet::sample() const {

gtsam/discrete/DiscreteBayesNet.h

@@ -31,12 +31,12 @@
 
 namespace gtsam {
 
-/** A Bayes net made from linear-Discrete densities */
+/** A Bayes net made from discrete conditional distributions. */
   class GTSAM_EXPORT DiscreteBayesNet: public BayesNet<DiscreteConditional>
   {
   public:
 
-    typedef FactorGraph<DiscreteConditional> Base;
+    typedef BayesNet<DiscreteConditional> Base;
     typedef DiscreteBayesNet This;
     typedef DiscreteConditional ConditionalType;
     typedef boost::shared_ptr<This> shared_ptr;
@@ -45,7 +45,7 @@ namespace gtsam {
     /// @name Standard Constructors
     /// @{
 
-    /** Construct empty factor graph */
+    /// Construct empty Bayes net.
     DiscreteBayesNet() {}
 
     /** Construct from iterator over conditionals */
@@ -98,27 +98,6 @@ namespace gtsam {
       return evaluate(values);
     }
 
-    /**
-     * @brief solve by back-substitution.
-     *
-     * Assumes the Bayes net is reverse topologically sorted, i.e. last
-     * conditional will be optimized first. If the Bayes net resulted from
-     * eliminating a factor graph, this is true for the elimination ordering.
-     *
-     * @return a sampled value for all variables.
-    */
-    DiscreteValues optimize() const;
-
-    /**
-     * @brief solve by back-substitution, given certain variables.
-     *
-     * Assumes the Bayes net is reverse topologically sorted *and* that the
-     * Bayes net does not contain any conditionals for the given values.
-     *
-     * @return given values extended with optimized value for other variables.
-     */
-    DiscreteValues optimize(DiscreteValues given) const;
-
     /**
      * @brief do ancestral sampling
      *
@@ -152,7 +131,16 @@ namespace gtsam {
     std::string html(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
                      const DiscreteFactor::Names& names = {}) const;
 
+    ///@}
+
+#ifdef GTSAM_ALLOW_DEPRECATED_SINCE_V42
+    /// @name Deprecated functionality
+    /// @{
+
+    DiscreteValues GTSAM_DEPRECATED optimize() const;
+    DiscreteValues GTSAM_DEPRECATED optimize(DiscreteValues given) const;
     /// @}
+#endif
 
  private:
     /** Serialization function */

gtsam/discrete/tests/testDiscreteBayesNet.cpp

@@ -106,26 +106,13 @@ TEST(DiscreteBayesNet, Asia) {
   DiscreteConditional expected2(Bronchitis % "11/9");
   EXPECT(assert_equal(expected2, *chordal->back()));
 
-  // solve
-  auto actualMPE = chordal->optimize();
-  DiscreteValues expectedMPE;
-  insert(expectedMPE)(Asia.first, 0)(Dyspnea.first, 0)(XRay.first, 0)(
-      Tuberculosis.first, 0)(Smoking.first, 0)(Either.first, 0)(
-      LungCancer.first, 0)(Bronchitis.first, 0);
-  EXPECT(assert_equal(expectedMPE, actualMPE));
-
   // 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
   DiscreteBayesNet::shared_ptr chordal2 = fg.eliminateSequential(ordering);
-  auto actualMPE2 = chordal2->optimize();
-  DiscreteValues expectedMPE2;
-  insert(expectedMPE2)(Asia.first, 1)(Dyspnea.first, 1)(XRay.first, 0)(
-      Tuberculosis.first, 0)(Smoking.first, 1)(Either.first, 0)(
-      LungCancer.first, 0)(Bronchitis.first, 1);
-  EXPECT(assert_equal(expectedMPE2, actualMPE2));
+  EXPECT(assert_equal(expected2, *chordal->back()));
 
   // now sample from it
   DiscreteValues expectedSample;