optimalAssignment -> optimize. Not deprecating as in unstable.

gtsam_unstable/discrete/CSP.cpp

@@ -14,18 +14,6 @@ using namespace std;
 
 namespace gtsam {
 
-/// Find the best total assignment - can be expensive
-DiscreteValues CSP::optimalAssignment() const {
-  DiscreteBayesNet::shared_ptr chordal = this->eliminateSequential();
-  return chordal->optimize();
-}
-
-/// Find the best total assignment - can be expensive
-DiscreteValues CSP::optimalAssignment(const Ordering& ordering) const {
-  DiscreteBayesNet::shared_ptr chordal = this->eliminateSequential(ordering);
-  return chordal->optimize();
-}
-
 bool CSP::runArcConsistency(const VariableIndex& index,
                             Domains* domains) const {
   bool changed = false;

gtsam_unstable/discrete/CSP.h

@@ -43,12 +43,6 @@ class GTSAM_UNSTABLE_EXPORT CSP : public DiscreteFactorGraph {
   //      return result;
   //    }
 
-  /// Find the best total assignment - can be expensive.
-  DiscreteValues optimalAssignment() const;
-
-  /// Find the best total assignment, with given ordering - can be expensive.
-  DiscreteValues optimalAssignment(const Ordering& ordering) const;
-
   //    /*
   //     * Perform loopy belief propagation
   //     * True belief propagation would check for each value in domain

gtsam_unstable/discrete/Scheduler.cpp

@@ -255,23 +255,6 @@ DiscreteBayesNet::shared_ptr Scheduler::eliminate() const {
   return chordal;
 }
 
-/** Find the best total assignment - can be expensive */
-DiscreteValues Scheduler::optimalAssignment() const {
-  DiscreteBayesNet::shared_ptr chordal = eliminate();
-
-  if (ISDEBUG("Scheduler::optimalAssignment")) {
-    DiscreteBayesNet::const_iterator it = chordal->end() - 1;
-    const Student& student = students_.front();
-    cout << endl;
-    (*it)->print(student.name_);
-  }
-
-  gttic(my_optimize);
-  DiscreteValues mpe = chordal->optimize();
-  gttoc(my_optimize);
-  return mpe;
-}
-
 /** find the assignment of students to slots with most possible committees */
 DiscreteValues Scheduler::bestSchedule() const {
   DiscreteValues best;

gtsam_unstable/discrete/Scheduler.h

@@ -147,9 +147,6 @@ class GTSAM_UNSTABLE_EXPORT Scheduler : public CSP {
   /** Eliminate, return a Bayes net */
   DiscreteBayesNet::shared_ptr eliminate() const;
 
-  /** Find the best total assignment - can be expensive */
-  DiscreteValues optimalAssignment() const;
-
   /** find the assignment of students to slots with most possible committees */
   DiscreteValues bestSchedule() const;
 

gtsam_unstable/discrete/examples/schedulingExample.cpp

@@ -122,7 +122,7 @@ void runLargeExample() {
   //  SETDEBUG("timing-verbose", true);
   SETDEBUG("DiscreteConditional::DiscreteConditional", true);
   gttic(large);
-  auto MPE = scheduler.optimalAssignment();
+  auto MPE = scheduler.optimize();
   gttoc(large);
   tictoc_finishedIteration();
   tictoc_print();

gtsam_unstable/discrete/examples/schedulingQuals12.cpp

@@ -143,7 +143,7 @@ void runLargeExample() {
   }
 #else
   gttic(large);
-  auto MPE = scheduler.optimalAssignment();
+  auto MPE = scheduler.optimize();
   gttoc(large);
   tictoc_finishedIteration();
   tictoc_print();

gtsam_unstable/discrete/examples/schedulingQuals13.cpp

@@ -167,7 +167,7 @@ void runLargeExample() {
   }
 #else
   gttic(large);
-  auto MPE = scheduler.optimalAssignment();
+  auto MPE = scheduler.optimize();
   gttoc(large);
   tictoc_finishedIteration();
   tictoc_print();

gtsam_unstable/discrete/tests/testCSP.cpp

@@ -132,7 +132,7 @@ TEST(CSP, allInOne) {
   EXPECT(assert_equal(expectedProduct, product));
 
   // Solve
-  auto mpe = csp.optimalAssignment();
+  auto mpe = csp.optimize();
   DiscreteValues expected;
   insert(expected)(ID.first, 1)(UT.first, 0)(AZ.first, 1);
   EXPECT(assert_equal(expected, mpe));
@@ -172,22 +172,18 @@ TEST(CSP, WesternUS) {
   csp.addAllDiff(WY, CO);
   csp.addAllDiff(CO, NM);
 
+  DiscreteValues mpe;
+  insert(mpe)(0, 2)(1, 3)(2, 2)(3, 1)(4, 1)(5, 3)(6, 3)(7, 2)(8, 0)(9, 1)(10, 0);
+
   // Create ordering according to example in ND-CSP.lyx
   Ordering ordering;
   ordering += Key(0), Key(1), Key(2), Key(3), Key(4), Key(5), Key(6), Key(7),
       Key(8), Key(9), Key(10);
-  // Solve using that ordering:
-  auto mpe = csp.optimalAssignment(ordering);
-  // GTSAM_PRINT(mpe);
-  DiscreteValues expected;
-  insert(expected)(WA.first, 1)(CA.first, 1)(NV.first, 3)(OR.first, 0)(
-      MT.first, 1)(WY.first, 0)(NM.first, 3)(CO.first, 2)(ID.first, 2)(
-      UT.first, 1)(AZ.first, 0);
 
-  // TODO: Fix me! mpe result seems to be right. (See the printing)
+  // Solve using that ordering:
-  // It has the same prob as the expected solution.
+  auto actualMPE = csp.optimize(ordering);
-  // Is mpe another solution, or the expected solution is unique???
+
-  EXPECT(assert_equal(expected, mpe));
+  EXPECT(assert_equal(mpe, actualMPE));
   EXPECT_DOUBLES_EQUAL(1, csp(mpe), 1e-9);
 
   // Write out the dual graph for hmetis
@@ -227,7 +223,7 @@ TEST(CSP, ArcConsistency) {
   EXPECT_DOUBLES_EQUAL(1, csp(valid), 1e-9);
 
   // Solve
-  auto mpe = csp.optimalAssignment();
+  auto mpe = csp.optimize();
   DiscreteValues expected;
   insert(expected)(ID.first, 1)(UT.first, 0)(AZ.first, 2);
   EXPECT(assert_equal(expected, mpe));

gtsam_unstable/discrete/tests/testScheduler.cpp

@@ -122,7 +122,7 @@ TEST(schedulingExample, test) {
 
   // Do exact inference
   gttic(small);
-  auto MPE = s.optimalAssignment();
+  auto MPE = s.optimize();
   gttoc(small);
 
   // print MPE, commented out as unit tests don't print

gtsam_unstable/discrete/tests/testSudoku.cpp

@@ -100,7 +100,7 @@ class Sudoku : public CSP {
 
   /// solve and print solution
   void printSolution() const {
-    auto MPE = optimalAssignment();
+    auto MPE = optimize();
     printAssignment(MPE);
   }
 
@@ -126,7 +126,7 @@ TEST(Sudoku, small) {
              0, 1, 0, 0);
 
   // optimize and check
-  auto solution = csp.optimalAssignment();
+  auto solution = csp.optimize();
   DiscreteValues expected;
   insert(expected)(csp.key(0, 0), 0)(csp.key(0, 1), 1)(csp.key(0, 2), 2)(
       csp.key(0, 3), 3)(csp.key(1, 0), 2)(csp.key(1, 1), 3)(csp.key(1, 2), 0)(
@@ -148,7 +148,7 @@ TEST(Sudoku, small) {
   EXPECT_LONGS_EQUAL(16, new_csp.size());
 
   // Check that solution
-  auto new_solution = new_csp.optimalAssignment();
+  auto new_solution = new_csp.optimize();
   // csp.printAssignment(new_solution);
   EXPECT(assert_equal(expected, new_solution));
 }
@@ -250,7 +250,7 @@ TEST(Sudoku, AJC_3star_Feb8_2012) {
   EXPECT_LONGS_EQUAL(81, new_csp.size());
 
   // Check that solution
-  auto solution = new_csp.optimalAssignment();
+  auto solution = new_csp.optimize();
   // csp.printAssignment(solution);
   EXPECT_LONGS_EQUAL(6, solution.at(key99));
 }