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Removed .finished() from testGaussianBayesTreeUnordered.cpp

release/4.3a0
indelman 2014-02-10 08:53:30 -05:00
parent c1a018a1fd
commit 5db9dd4081
1 changed files with 28 additions and 28 deletions
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56
gtsam/linear/tests/testGaussianBayesTreeUnordered.cpp
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@ -114,39 +114,39 @@ TEST(GaussianBayesTree, complicatedMarginal) {
// Create the conditionals to go in the BayesTree // Create the conditionals to go in the BayesTree
GaussianBayesTree bt; GaussianBayesTree bt;
bt.insertRoot( bt.insertRoot(
MakeClique(GaussianConditional(pair_list_of<Key, Matrix> (11, (Matrix(3,1) << 0.0971, 0, 0).finished()) MakeClique(GaussianConditional(pair_list_of<Key, Matrix> (11, (Matrix(3,1) << 0.0971, 0, 0))
(12, (Matrix(3,2) << 0.3171, 0.4387, 0.9502, 0.3816, 0, 0.7655).finished()), (12, (Matrix(3,2) << 0.3171, 0.4387, 0.9502, 0.3816, 0, 0.7655)),
2, (Vector(3) << 0.2638, 0.1455, 0.1361).finished()), list_of 2, (Vector(3) << 0.2638, 0.1455, 0.1361)), list_of
(MakeClique(GaussianConditional(pair_list_of<Key, Matrix> (9, (Matrix(3,1) << 0.7952, 0, 0).finished()) (MakeClique(GaussianConditional(pair_list_of<Key, Matrix> (9, (Matrix(3,1) << 0.7952, 0, 0))
(10, (Matrix(3,2) << 0.4456, 0.7547, 0.6463, 0.2760, 0, 0.6797).finished()) (10, (Matrix(3,2) << 0.4456, 0.7547, 0.6463, 0.2760, 0, 0.6797))
(11, (Matrix(3,1) << 0.6551, 0.1626, 0.1190).finished()) (11, (Matrix(3,1) << 0.6551, 0.1626, 0.1190))
(12, (Matrix(3,2) << 0.4984, 0.5853, 0.9597, 0.2238, 0.3404, 0.7513).finished()), (12, (Matrix(3,2) << 0.4984, 0.5853, 0.9597, 0.2238, 0.3404, 0.7513)),
2, (Vector(3) << 0.4314, 0.9106, 0.1818).finished()))) 2, (Vector(3) << 0.4314, 0.9106, 0.1818))))
(MakeClique(GaussianConditional(pair_list_of<Key, Matrix> (7, (Matrix(3,1) << 0.2551, 0, 0).finished()) (MakeClique(GaussianConditional(pair_list_of<Key, Matrix> (7, (Matrix(3,1) << 0.2551, 0, 0))
(8, (Matrix(3,2) << 0.8909, 0.1386, 0.9593, 0.1493, 0, 0.2575).finished()) (8, (Matrix(3,2) << 0.8909, 0.1386, 0.9593, 0.1493, 0, 0.2575))
(11, (Matrix(3,1) << 0.8407, 0.2543, 0.8143).finished()), (11, (Matrix(3,1) << 0.8407, 0.2543, 0.8143)),
2, (Vector(3) << 0.3998, 0.2599, 0.8001).finished()), list_of 2, (Vector(3) << 0.3998, 0.2599, 0.8001)), list_of
(MakeClique(GaussianConditional(pair_list_of<Key, Matrix> (5, (Matrix(3,1) << 0.2435, 0, 0).finished()) (MakeClique(GaussianConditional(pair_list_of<Key, Matrix> (5, (Matrix(3,1) << 0.2435, 0, 0))
(6, (Matrix(3,2) << 0.4733, 0.1966, 0.3517, 0.2511, 0.8308, 0.0).finished()) (6, (Matrix(3,2) << 0.4733, 0.1966, 0.3517, 0.2511, 0.8308, 0.0))
// NOTE the non-upper-triangular form // NOTE the non-upper-triangular form
// here since this test was written when we had column permutations // here since this test was written when we had column permutations
// from LDL. The code still works currently (does not enfore // from LDL. The code still works currently (does not enfore
// upper-triangularity in this case) but this test will need to be // upper-triangularity in this case) but this test will need to be
// redone if this stops working in the future // redone if this stops working in the future
(7, (Matrix(3,1) << 0.5853, 0.5497, 0.9172).finished()) (7, (Matrix(3,1) << 0.5853, 0.5497, 0.9172))
(8, (Matrix(3,2) << 0.2858, 0.3804, 0.7572, 0.5678, 0.7537, 0.0759).finished()), (8, (Matrix(3,2) << 0.2858, 0.3804, 0.7572, 0.5678, 0.7537, 0.0759)),
2, (Vector(3) << 0.8173, 0.8687, 0.0844).finished()), list_of 2, (Vector(3) << 0.8173, 0.8687, 0.0844)), list_of
(MakeClique(GaussianConditional(pair_list_of<Key, Matrix> (3, (Matrix(3,1) << 0.0540, 0, 0).finished()) (MakeClique(GaussianConditional(pair_list_of<Key, Matrix> (3, (Matrix(3,1) << 0.0540, 0, 0))
(4, (Matrix(3,2) << 0.9340, 0.4694, 0.1299, 0.0119, 0, 0.3371).finished()) (4, (Matrix(3,2) << 0.9340, 0.4694, 0.1299, 0.0119, 0, 0.3371))
(6, (Matrix(3,2) << 0.1622, 0.5285, 0.7943, 0.1656, 0.3112, 0.6020).finished()), (6, (Matrix(3,2) << 0.1622, 0.5285, 0.7943, 0.1656, 0.3112, 0.6020)),
2, (Vector(3) << 0.9619, 0.0046, 0.7749).finished()))) 2, (Vector(3) << 0.9619, 0.0046, 0.7749))))
(MakeClique(GaussianConditional(pair_list_of<Key, Matrix> (1, (Matrix(3,1) << 0.2630, 0, 0).finished()) (MakeClique(GaussianConditional(pair_list_of<Key, Matrix> (1, (Matrix(3,1) << 0.2630, 0, 0))
(2, (Matrix(3,2) << 0.7482, 0.2290, 0.4505, 0.9133, 0, 0.1524).finished()) (2, (Matrix(3,2) << 0.7482, 0.2290, 0.4505, 0.9133, 0, 0.1524))
(5, (Matrix(3,1) << 0.8258, 0.5383, 0.9961).finished()), (5, (Matrix(3,1) << 0.8258, 0.5383, 0.9961)),
2, (Vector(3) << 0.0782, 0.4427, 0.1067).finished()))))))))); 2, (Vector(3) << 0.0782, 0.4427, 0.1067))))))))));
// Marginal on 5 // Marginal on 5
Matrix expectedCov = (Matrix(1,1) << 236.5166).finished(); Matrix expectedCov = (Matrix(1,1) << 236.5166);
//GaussianConditional actualJacobianChol = *bt.marginalFactor(5, EliminateCholesky); //GaussianConditional actualJacobianChol = *bt.marginalFactor(5, EliminateCholesky);
GaussianConditional actualJacobianQR = *bt.marginalFactor(5, EliminateQR); GaussianConditional actualJacobianQR = *bt.marginalFactor(5, EliminateQR);
//EXPECT(assert_equal(actualJacobianChol, actualJacobianQR)); // Check that Chol and QR obtained marginals are the same //EXPECT(assert_equal(actualJacobianChol, actualJacobianQR)); // Check that Chol and QR obtained marginals are the same
@ -160,10 +160,10 @@ TEST(GaussianBayesTree, complicatedMarginal) {
// Marginal on 6 // Marginal on 6
// expectedCov = (Matrix(2,2) << // expectedCov = (Matrix(2,2) <<
// 8471.2, 2886.2, // 8471.2, 2886.2,
// 2886.2, 1015.8).finished(); // 2886.2, 1015.8);
expectedCov = (Matrix(2,2) << expectedCov = (Matrix(2,2) <<
1015.8, 2886.2, 1015.8, 2886.2,
2886.2, 8471.2).finished(); 2886.2, 8471.2);
//actualJacobianChol = bt.marginalFactor(6, EliminateCholesky); //actualJacobianChol = bt.marginalFactor(6, EliminateCholesky);
actualJacobianQR = *bt.marginalFactor(6, EliminateQR); actualJacobianQR = *bt.marginalFactor(6, EliminateQR);
//EXPECT(assert_equal(actualJacobianChol, actualJacobianQR)); // Check that Chol and QR obtained marginals are the same //EXPECT(assert_equal(actualJacobianChol, actualJacobianQR)); // Check that Chol and QR obtained marginals are the same