Resurrected remaining tests and deleted two
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				|  | @ -169,35 +169,6 @@ TEST(GaussianFactorGraph, eliminateOne_l1_fast) { | |||
|   EXPECT(assert_equal(expected, *actual, tol)); | ||||
| } | ||||
| 
 | ||||
| // /* ************************************************************************* */
 | ||||
| // TEST( GaussianFactorGraph, eliminateAll )
 | ||||
| // {
 | ||||
| //   // create expected Chordal bayes Net
 | ||||
| //   Matrix I = I_2x2;
 | ||||
| 
 | ||||
| //   Ordering ordering;
 | ||||
| //   ordering += X(2),L(1),X(1);
 | ||||
| 
 | ||||
| //   Vector d1 = Vector2(-0.1,-0.1);
 | ||||
| //   GaussianBayesNet expected = simpleGaussian(X(1),d1,0.1);
 | ||||
| 
 | ||||
| //   double sig1 = 0.149071;
 | ||||
| //   Vector d2 = Vector2(0.0, 0.2)/sig1, sigma2 = Vector::Ones(2);
 | ||||
| //   push_front(expected,L(1),d2, I/sig1,X(1), (-1)*I/sig1,sigma2);
 | ||||
| 
 | ||||
| //   double sig2 = 0.0894427;
 | ||||
| //   Vector d3 = Vector2(0.2, -0.14)/sig2, sigma3 = Vector::Ones(2);
 | ||||
| //   push_front(expected,X(2),d3, I/sig2,L(1), (-0.2)*I/sig2, X(1), (-0.8)*I/sig2, sigma3);
 | ||||
| 
 | ||||
| //   // Check one ordering
 | ||||
| //   GaussianFactorGraph fg1 = createGaussianFactorGraph();
 | ||||
| //   GaussianBayesNet actual = *fg1.eliminateSequential();
 | ||||
| //   EXPECT(assert_equal(expected,actual,tol));
 | ||||
| 
 | ||||
| //   GaussianBayesNet actualQR = *fg1.eliminateSequential(, true);
 | ||||
| //   EXPECT(assert_equal(expected,actualQR,tol));
 | ||||
| // }
 | ||||
| 
 | ||||
| /* ************************************************************************* */ | ||||
| TEST(GaussianFactorGraph, copying) { | ||||
|   // Create a graph
 | ||||
|  | @ -338,19 +309,16 @@ TEST(GaussianFactorGraph, elimination) { | |||
|          equal_with_abs_tol(expected2, R, 1e-6)); | ||||
| } | ||||
| 
 | ||||
| #if 0 | ||||
| 
 | ||||
| /* ************************************************************************* */ | ||||
| // Tests ported from ConstrainedGaussianFactorGraph
 | ||||
| /* ************************************************************************* */ | ||||
| TEST( GaussianFactorGraph, constrained_simple ) | ||||
| { | ||||
| TEST(GaussianFactorGraph, constrained_simple) { | ||||
|   // get a graph with a constraint in it
 | ||||
|   GaussianFactorGraph fg = createSimpleConstraintGraph(); | ||||
|   EXPECT(hasConstraints(fg)); | ||||
| 
 | ||||
|   // eliminate and solve
 | ||||
|   VectorValues actual = *fg.eliminateSequential().optimize(); | ||||
|   VectorValues actual = fg.eliminateSequential()->optimize(); | ||||
| 
 | ||||
|   // verify
 | ||||
|   VectorValues expected = createSimpleConstraintValues(); | ||||
|  | @ -358,14 +326,13 @@ TEST( GaussianFactorGraph, constrained_simple ) | |||
| } | ||||
| 
 | ||||
| /* ************************************************************************* */ | ||||
| TEST( GaussianFactorGraph, constrained_single ) | ||||
| { | ||||
| TEST(GaussianFactorGraph, constrained_single) { | ||||
|   // get a graph with a constraint in it
 | ||||
|   GaussianFactorGraph fg = createSingleConstraintGraph(); | ||||
|   EXPECT(hasConstraints(fg)); | ||||
| 
 | ||||
|   // eliminate and solve
 | ||||
|   VectorValues actual = *fg.eliminateSequential().optimize(); | ||||
|   VectorValues actual = fg.eliminateSequential()->optimize(); | ||||
| 
 | ||||
|   // verify
 | ||||
|   VectorValues expected = createSingleConstraintValues(); | ||||
|  | @ -373,14 +340,13 @@ TEST( GaussianFactorGraph, constrained_single ) | |||
| } | ||||
| 
 | ||||
| /* ************************************************************************* */ | ||||
| TEST( GaussianFactorGraph, constrained_multi1 ) | ||||
| { | ||||
| TEST(GaussianFactorGraph, constrained_multi1) { | ||||
|   // get a graph with a constraint in it
 | ||||
|   GaussianFactorGraph fg = createMultiConstraintGraph(); | ||||
|   EXPECT(hasConstraints(fg)); | ||||
| 
 | ||||
|   // eliminate and solve
 | ||||
|   VectorValues actual = *fg.eliminateSequential().optimize(); | ||||
|   VectorValues actual = fg.eliminateSequential()->optimize(); | ||||
| 
 | ||||
|   // verify
 | ||||
|   VectorValues expected = createMultiConstraintValues(); | ||||
|  | @ -420,27 +386,6 @@ TEST(GaussianFactorGraph, replace) | |||
|   EXPECT(assert_equal(expected, actual)); | ||||
| } | ||||
| 
 | ||||
| /* ************************************************************************* */ | ||||
| TEST(GaussianFactorGraph, createSmoother2) | ||||
| { | ||||
|   using namespace example; | ||||
|   GaussianFactorGraph fg2; | ||||
|   Ordering ordering; | ||||
|   boost::tie(fg2,ordering) = createSmoother(3); | ||||
|   LONGS_EQUAL(5,fg2.size()); | ||||
| 
 | ||||
|   // eliminate
 | ||||
|   vector<Index> x3var; x3var.push_back(ordering[X(3)]); | ||||
|   vector<Index> x1var; x1var.push_back(X(1)); | ||||
|   GaussianBayesNet p_x3 = *GaussianSequentialSolver( | ||||
|       *fg2.eliminateSequential().jointFactorGraph(x3var)); | ||||
|   GaussianBayesNet p_x1 = *GaussianSequentialSolver( | ||||
|       *fg2.eliminateSequential().jointFactorGraph(x1var)); | ||||
|   CHECK(assert_equal(*p_x1.back(),*p_x3.front())); // should be the same because of symmetry
 | ||||
| } | ||||
| 
 | ||||
| #endif | ||||
| 
 | ||||
| /* ************************************************************************* */ | ||||
| TEST(GaussianFactorGraph, hasConstraints) | ||||
| { | ||||
|  |  | |||
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