Made all Bayesnets derive from BayesNet

gtsam/discrete/DiscreteBayesNet.h

@@ -31,11 +31,12 @@
 
 namespace gtsam {
 
-/** A Bayes net made from discrete conditional distributions. */
+/** 
-  class GTSAM_EXPORT DiscreteBayesNet: public BayesNet<DiscreteConditional>
+ * A Bayes net made from discrete conditional distributions. 
-  {
+ * @addtogroup discrete
-  public:
+ */
-
+class GTSAM_EXPORT DiscreteBayesNet: public BayesNet<DiscreteConditional> {
+ public:
     typedef BayesNet<DiscreteConditional> Base;
     typedef DiscreteBayesNet This;
     typedef DiscreteConditional ConditionalType;
@@ -49,16 +50,20 @@ namespace gtsam {
     DiscreteBayesNet() {}
 
     /** Construct from iterator over conditionals */
-    template<typename ITERATOR>
+    template <typename ITERATOR>
-    DiscreteBayesNet(ITERATOR firstConditional, ITERATOR lastConditional) : Base(firstConditional, lastConditional) {}
+    DiscreteBayesNet(ITERATOR firstConditional, ITERATOR lastConditional)
+        : Base(firstConditional, lastConditional) {}
 
     /** Construct from container of factors (shared_ptr or plain objects) */
-    template<class CONTAINER>
+    template <class CONTAINER>
-    explicit DiscreteBayesNet(const CONTAINER& conditionals) : Base(conditionals) {}
+    explicit DiscreteBayesNet(const CONTAINER& conditionals)
+        : Base(conditionals) {}
 
-    /** Implicit copy/downcast constructor to override explicit template container constructor */
+    /** Implicit copy/downcast constructor to override explicit template
-    template<class DERIVEDCONDITIONAL>
+     * container constructor */
-    DiscreteBayesNet(const FactorGraph<DERIVEDCONDITIONAL>& graph) : Base(graph) {}
+    template <class DERIVEDCONDITIONAL>
+    DiscreteBayesNet(const FactorGraph<DERIVEDCONDITIONAL>& graph)
+        : Base(graph) {}
 
     /// Destructor
     virtual ~DiscreteBayesNet() {}

gtsam/discrete/tests/testDiscreteBayesNet.cpp

@@ -150,12 +150,13 @@ TEST(DiscreteBayesNet, Dot) {
   fragment.add((Either | Tuberculosis, LungCancer) = "F T T T");
 
   string actual = fragment.dot();
+  cout << actual << endl;
   EXPECT(actual ==
          "digraph G{\n"
-         "0->3\n"
-         "4->6\n"
          "3->5\n"
          "6->5\n"
+         "4->6\n"
+         "0->3\n"
          "}");
 }
 

gtsam/inference/BayesNet-inst.h

@@ -23,6 +23,7 @@
 
 #include <boost/range/adaptor/reversed.hpp>
 #include <fstream>
+#include <string>
 
 namespace gtsam {
 
@@ -39,7 +40,7 @@ void BayesNet<CONDITIONAL>::dot(std::ostream& os,
                                 const KeyFormatter& keyFormatter) const {
   os << "digraph G{\n";
 
-  for (auto conditional : *this) {
+  for (auto conditional : boost::adaptors::reverse(*this)) {
     auto frontals = conditional->frontals();
     const Key me = frontals.front();
     auto parents = conditional->parents();

gtsam/inference/BayesNet.h

@@ -18,17 +18,17 @@
 
 #pragma once
 
+#include <gtsam/inference/FactorGraph.h>
+
 #include <boost/shared_ptr.hpp>
 
-#include <gtsam/inference/FactorGraph.h>
+#include <string>
 
 namespace gtsam {
 
   /**
   * A BayesNet is a tree of conditionals, stored in elimination order.
-  *
+  * @addtogroup inference
-  * todo:  how to handle Bayes nets with an optimize function?  Currently using global functions.
-  * \nosubgrouping
   */
   template<class CONDITIONAL>
   class BayesNet : public FactorGraph<CONDITIONAL> {

gtsam/linear/GaussianBayesNet.h

@@ -21,17 +21,21 @@
 #pragma once
 
 #include <gtsam/linear/GaussianConditional.h>
+#include <gtsam/inference/BayesNet.h>
 #include <gtsam/inference/FactorGraph.h>
 #include <gtsam/global_includes.h>
 
 namespace gtsam {
 
-  /** A Bayes net made from linear-Gaussian densities */
+  /** 
-  class GTSAM_EXPORT GaussianBayesNet: public FactorGraph<GaussianConditional>
+   * GaussianBayesNet is a Bayes net made from linear-Gaussian conditionals.
+   * @addtogroup linear
+   */
+  class GTSAM_EXPORT GaussianBayesNet: public BayesNet<GaussianConditional>
   {
   public:
 
-    typedef FactorGraph<GaussianConditional> Base;
+    typedef BayesNet<GaussianConditional> Base;
     typedef GaussianBayesNet This;
     typedef GaussianConditional ConditionalType;
     typedef boost::shared_ptr<This> shared_ptr;
@@ -44,16 +48,21 @@ namespace gtsam {
     GaussianBayesNet() {}
 
     /** Construct from iterator over conditionals */
-    template<typename ITERATOR>
+    template <typename ITERATOR>
-    GaussianBayesNet(ITERATOR firstConditional, ITERATOR lastConditional) : Base(firstConditional, lastConditional) {}
+    GaussianBayesNet(ITERATOR firstConditional, ITERATOR lastConditional)
+        : Base(firstConditional, lastConditional) {}
 
     /** Construct from container of factors (shared_ptr or plain objects) */
-    template<class CONTAINER>
+    template <class CONTAINER>
-    explicit GaussianBayesNet(const CONTAINER& conditionals) : Base(conditionals) {}
+    explicit GaussianBayesNet(const CONTAINER& conditionals) {
+      push_back(conditionals);
+    }
 
-    /** Implicit copy/downcast constructor to override explicit template container constructor */
+    /** Implicit copy/downcast constructor to override explicit template
-    template<class DERIVEDCONDITIONAL>
+     * container constructor */
-    GaussianBayesNet(const FactorGraph<DERIVEDCONDITIONAL>& graph) : Base(graph) {}
+    template <class DERIVEDCONDITIONAL>
+    explicit GaussianBayesNet(const FactorGraph<DERIVEDCONDITIONAL>& graph)
+        : Base(graph) {}
 
     /// Destructor
     virtual ~GaussianBayesNet() {}

gtsam/symbolic/SymbolicBayesNet.h

@@ -19,19 +19,19 @@
 #pragma once
 
 #include <gtsam/symbolic/SymbolicConditional.h>
+#include <gtsam/inference/BayesNet.h>
 #include <gtsam/inference/FactorGraph.h>
 #include <gtsam/base/types.h>
 
 namespace gtsam {
 
-  /** Symbolic Bayes Net
+  /** 
-   *  \nosubgrouping
+   * A SymbolicBayesNet is a Bayes Net of purely symbolic conditionals.
+   * @addtogroup symbolic
    */
-  class SymbolicBayesNet : public FactorGraph<SymbolicConditional> {
+  class SymbolicBayesNet : public BayesNet<SymbolicConditional> {
-
+   public:
-  public:
+    typedef BayesNet<SymbolicConditional> Base;
-
-    typedef FactorGraph<SymbolicConditional> Base;
     typedef SymbolicBayesNet This;
     typedef SymbolicConditional ConditionalType;
     typedef boost::shared_ptr<This> shared_ptr;
@@ -44,16 +44,21 @@ namespace gtsam {
     SymbolicBayesNet() {}
 
     /** Construct from iterator over conditionals */
-    template<typename ITERATOR>
+    template <typename ITERATOR>
-    SymbolicBayesNet(ITERATOR firstConditional, ITERATOR lastConditional) : Base(firstConditional, lastConditional) {}
+    SymbolicBayesNet(ITERATOR firstConditional, ITERATOR lastConditional)
+        : Base(firstConditional, lastConditional) {}
 
     /** Construct from container of factors (shared_ptr or plain objects) */
-    template<class CONTAINER>
+    template <class CONTAINER>
-    explicit SymbolicBayesNet(const CONTAINER& conditionals) : Base(conditionals) {}
+    explicit SymbolicBayesNet(const CONTAINER& conditionals) {
+      push_back(conditionals);
+    }
 
-    /** Implicit copy/downcast constructor to override explicit template container constructor */
+    /** Implicit copy/downcast constructor to override explicit template
-    template<class DERIVEDCONDITIONAL>
+     * container constructor */
-    SymbolicBayesNet(const FactorGraph<DERIVEDCONDITIONAL>& graph) : Base(graph) {}
+    template <class DERIVEDCONDITIONAL>
+    explicit SymbolicBayesNet(const FactorGraph<DERIVEDCONDITIONAL>& graph)
+        : Base(graph) {}
 
     /// Destructor
     virtual ~SymbolicBayesNet() {}