Merge branch 'feature/discrete_wrapper' into feature/discrete_wrapper_2

gtsam/discrete/DiscreteBayesNet.h

@@ -83,6 +83,11 @@ namespace gtsam {
     //** evaluate for given DiscreteValues */
     double evaluate(const DiscreteValues & values) const;
 
+    //** (Preferred) sugar for the above for given DiscreteValues */
+    double operator()(const DiscreteValues & values) const {
+      return evaluate(values);
+    }
+
     /**
     * Solve the DiscreteBayesNet by back-substitution
     */

gtsam/discrete/DiscreteBayesTree.h

@@ -80,6 +80,12 @@ class GTSAM_EXPORT DiscreteBayesTree
 
   //** evaluate probability for given DiscreteValues */
   double evaluate(const DiscreteValues& values) const;
+
+  //** (Preferred) sugar for the above for given DiscreteValues */
+  double operator()(const DiscreteValues & values) const {
+    return evaluate(values);
+  }
+
 };
 
 }  // namespace gtsam

gtsam/discrete/DiscreteConditional.h

@@ -58,24 +58,28 @@ public:
   DiscreteConditional(const Signature& signature);
 
   /**
-  * Construct from key, parents, and a Table specifying the CPT.
+   * Construct from key, parents, and a Signature::Table specifying the
-  *
+   * conditional probability table (CPT) in 00 01 10 11 order. For
-  * The first string is parsed to add a key and parents.
+   * three-valued, it would be 00 01 02 10 11 12 20 21 22, etc....
-  * 
+   *
-  * Example: DiscreteConditional P(D, {B,E}, table);
+   * The first string is parsed to add a key and parents.
-  */
+   *
+   * Example: DiscreteConditional P(D, {B,E}, table);
+   */
   DiscreteConditional(const DiscreteKey& key, const DiscreteKeys& parents,
                       const Signature::Table& table)
       : DiscreteConditional(Signature(key, parents, table)) {}
 
   /**
-  * Construct from key, parents, and a string specifying the CPT.
+   * Construct from key, parents, and a string specifying the conditional
-  *
+   * probability table (CPT) in 00 01 10 11 order. For three-valued, it would
-  * The first string is parsed to add a key and parents. The second string
+   * be 00 01 02 10 11 12 20 21 22, etc....
-  * parses into a table.
+   *
-  * 
+   * The first string is parsed to add a key and parents. The second string
-  * Example: DiscreteConditional P(D, {B,E}, "9/1 2/8 3/7 1/9");
+   * parses into a table.
-  */
+   *
+   * Example: DiscreteConditional P(D, {B,E}, "9/1 2/8 3/7 1/9");
+   */
   DiscreteConditional(const DiscreteKey& key, const DiscreteKeys& parents,
                       const std::string& spec)
       : DiscreteConditional(Signature(key, parents, spec)) {}

gtsam/discrete/DiscreteFactor.h

@@ -83,9 +83,6 @@ public:
   /// Find value for given assignment of values to variables
   virtual double operator()(const DiscreteValues&) const = 0;
 
-  /// Synonym for operator(), mostly for wrapper
-  double evaluate(const DiscreteValues& values) const { return operator()(values); }
-
   /// Multiply in a DecisionTreeFactor and return the result as DecisionTreeFactor
   virtual DecisionTreeFactor operator*(const DecisionTreeFactor&) const = 0;
 

gtsam/discrete/DiscreteFactorGraph.h

@@ -136,9 +136,6 @@ public:
    */
   double operator()(const DiscreteValues& values) const;
 
-  /// Synonym for operator(), mostly for wrapper
-  double evaluate(const DiscreteValues& values) const { return operator()(values); }
-
   /// print
   void print(
       const std::string& s = "DiscreteFactorGraph",

gtsam/discrete/Signature.h

@@ -30,7 +30,7 @@ namespace gtsam {
    * The format is (Key % string) for nodes with no parents,
    * and (Key | Key, Key = string) for nodes with parents.
    *
-   * The string specifies a conditional probability spec in the 00 01 10 11 order.
+   * The string specifies a conditional probability table in 00 01 10 11 order.
    * For three-valued, it would be 00 01 02 10 11 12 20 21 22, etc...
    *
    * For example, given the following keys
@@ -73,22 +73,29 @@ namespace gtsam {
 
   public:
    /**
-    * Construct from key, parents, and a Table specifying the CPT.
+    * Construct from key, parents, and a Signature::Table specifying the
+    * conditional probability table (CPT) in 00 01 10 11 order. For
+    * three-valued, it would be 00 01 02 10 11 12 20 21 22, etc....
     *
     * The first string is parsed to add a key and parents.
-    * 
+    *
-    * Example: Signature sig(D, {B,E}, table);
+    * Example:
+    *   Signature::Table table{{0.9, 0.1}, {0.2, 0.8}, {0.3, 0.7}, {0.1, 0.9}};
+    *   Signature sig(D, {E, B}, table);
     */
    Signature(const DiscreteKey& key, const DiscreteKeys& parents,
              const Table& table);
 
    /**
-    * Construct from key, parents, and a string specifying the CPT.
+    * Construct from key, parents, and a string specifying the conditional
+    * probability table (CPT) in 00 01 10 11 order. For three-valued, it would
+    * be 00 01 02 10 11 12 20 21 22, etc....
     *
     * The first string is parsed to add a key and parents. The second string
     * parses into a table.
-    * 
+    *
-    * Example: Signature sig(D, {B,E}, "9/1 2/8 3/7 1/9");
+    * Example (same CPT as above):
+    *   Signature sig(D, {B,E}, "9/1 2/8 3/7 1/9");
     */
    Signature(const DiscreteKey& key, const DiscreteKeys& parents,
              const std::string& spec);

gtsam/discrete/discrete.i

@@ -1,5 +1,5 @@
 //*************************************************************************
-// basis
+// discrete
 //*************************************************************************
 
 namespace gtsam {
@@ -26,7 +26,7 @@ class DiscreteFactor {
   bool equals(const gtsam::DiscreteFactor& other, double tol = 1e-9) const;
   bool empty() const;
   size_t size() const;
-  double evaluate(const gtsam::DiscreteValues& values) const;
+  double operator()(const gtsam::DiscreteValues& values) const;
 };
 
 #include <gtsam/discrete/DecisionTreeFactor.h>
@@ -38,7 +38,7 @@ virtual class DecisionTreeFactor: gtsam::DiscreteFactor {
              const gtsam::KeyFormatter& keyFormatter =
                  gtsam::DefaultKeyFormatter) const;
   bool equals(const gtsam::DecisionTreeFactor& other, double tol = 1e-9) const;
-  double evaluate(const gtsam::DiscreteValues& values) const; // TODO(dellaert): why do I have to repeat???
+  double operator()(const gtsam::DiscreteValues& values) const; // TODO(dellaert): why do I have to repeat???
 };
 
 #include <gtsam/discrete/DiscreteConditional.h>
@@ -53,7 +53,7 @@ virtual class DiscreteConditional : gtsam::DecisionTreeFactor {
                       const gtsam::DecisionTreeFactor& marginal,
                       const gtsam::Ordering& orderedKeys);
   size_t size() const; // TODO(dellaert): why do I have to repeat???
-  double evaluate(const gtsam::DiscreteValues& values) const; // TODO(dellaert): why do I have to repeat???
+  double operator()(const gtsam::DiscreteValues& values) const; // TODO(dellaert): why do I have to repeat???
   void print(string s = "Discrete Conditional\n",
              const gtsam::KeyFormatter& keyFormatter =
                  gtsam::DefaultKeyFormatter) const;
@@ -86,7 +86,7 @@ class DiscreteBayesNet {
                 const gtsam::KeyFormatter& keyFormatter =
                  gtsam::DefaultKeyFormatter) const;
   void add(const gtsam::DiscreteConditional& s);
-  double evaluate(const gtsam::DiscreteValues& values) const;
+  double operator()(const gtsam::DiscreteValues& values) const;
   gtsam::DiscreteValues optimize() const;
   gtsam::DiscreteValues sample() const;
 };
@@ -98,7 +98,7 @@ class DiscreteBayesTree {
              const gtsam::KeyFormatter& keyFormatter =
                  gtsam::DefaultKeyFormatter) const;
   bool equals(const gtsam::DiscreteBayesTree& other, double tol = 1e-9) const;
-  double evaluate(const gtsam::DiscreteValues& values) const;
+  double operator()(const gtsam::DiscreteValues& values) const;
 };
 
 #include <gtsam/discrete/DiscreteFactorGraph.h>
@@ -119,7 +119,7 @@ class DiscreteFactorGraph {
   bool equals(const gtsam::DiscreteFactorGraph& fg, double tol = 1e-9) const;
   
   gtsam::DecisionTreeFactor product() const;
-  double evaluate(const gtsam::DiscreteValues& values) const;
+  double operator()(const gtsam::DiscreteValues& values) const;
   gtsam::DiscreteValues optimize() const;
 
   gtsam::DiscreteBayesNet eliminateSequential();

gtsam/discrete/tests/testSignature.cpp

@@ -92,7 +92,6 @@ TEST(testSignature, all_examples) {
   Signature b(B, {S}, "70/30  40/60");
   Signature e(E, {T, L}, "F F F 1");
   Signature x(X, {E}, "95/5 2/98");
-  Signature d(D, {E, B}, "9/1 2/8 3/7 1/9");
 }
 
 // Make sure we can create all signatures for Asia network with operator magic.
@@ -105,7 +104,17 @@ TEST(testSignature, all_examples_magic) {
   Signature b(B | S = "70/30  40/60");
   Signature e((E | T, L) = "F F F 1");
   Signature x(X | E = "95/5 2/98");
-  Signature d((D | E, B) = "9/1 2/8 3/7 1/9");
+}
+
+// Check example from docs.
+TEST(testSignature, doxygen_example) {
+  Signature::Table table{{0.9, 0.1}, {0.2, 0.8}, {0.3, 0.7}, {0.1, 0.9}};
+  Signature d1(D, {E, B}, table);
+  Signature d2((D | E, B) = "9/1 2/8 3/7 1/9");
+  Signature d3(D, {E, B}, "9/1 2/8 3/7 1/9");
+  EXPECT(*(d1.table()) == table);
+  EXPECT(*(d2.table()) == table);
+  EXPECT(*(d3.table()) == table);
 }
 
 /* ************************************************************************* */

python/gtsam/tests/test_DiscreteBayesNet.py

@@ -91,6 +91,9 @@ class TestDiscreteBayesNet(GtsamTestCase):
         self.assertEqual(list(actualMPE.items()),
                          list(expectedMPE.items()))
 
+        # Check value for MPE is the same
+        self.assertAlmostEqual(asia(actualMPE), fg(actualMPE))
+
         # add evidence, we were in Asia and we have dyspnea
         fg.add(Asia, "0 1")
         fg.add(Dyspnea, "0 1")

python/gtsam/tests/test_DiscreteFactorGraph.py

@@ -44,9 +44,9 @@ class TestDiscreteFactorGraph(GtsamTestCase):
         assignment[1] = 1
 
         # Check if graph evaluation works ( 0.3*0.6*4 )
-        self.assertAlmostEqual(.72, graph.evaluate(assignment))
+        self.assertAlmostEqual(.72, graph(assignment))
 
-        # Creating a new test with third node and adding unary and ternary factors on it
+        # Create a new test with third node and adding unary and ternary factor
         graph.add(P3, "0.9 0.2 0.5")
         keys = DiscreteKeys()
         keys.push_back(P1)
@@ -54,25 +54,25 @@ class TestDiscreteFactorGraph(GtsamTestCase):
         keys.push_back(P3)
         graph.add(keys, "1 2 3 4 5 6 7 8 9 10 11 12")
 
-        # Below assignment lead to selecting the 8th index in the ternary factor table
+        # Below assignment selects the 8th index in the ternary factor table
         assignment[0] = 1
         assignment[1] = 0
         assignment[2] = 1
 
         # Check if graph evaluation works (0.3*0.9*1*0.2*8)
-        self.assertAlmostEqual(4.32, graph.evaluate(assignment))
+        self.assertAlmostEqual(4.32, graph(assignment))
 
-        # Below assignment lead to selecting the 3rd index in the ternary factor table
+        # Below assignment selects the 3rd index in the ternary factor table
         assignment[0] = 0
         assignment[1] = 1
         assignment[2] = 0
 
         # Check if graph evaluation works (0.9*0.6*1*0.9*4)
-        self.assertAlmostEqual(1.944, graph.evaluate(assignment))
+        self.assertAlmostEqual(1.944, graph(assignment))
 
         # Check if graph product works
         product = graph.product()
-        self.assertAlmostEqual(1.944, product.evaluate(assignment))
+        self.assertAlmostEqual(1.944, product(assignment))
 
     def test_optimize(self):
         """Test constructing and optizing a discrete factor graph."""