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fix tests due to change to EliminateDiscrete

release/4.3a0
Varun Agrawal 2023-01-03 03:47:27 -05:00
parent ca1c517f8a
commit 7825ffd6d2
3 changed files with 13 additions and 13 deletions
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12
gtsam/hybrid/tests/testHybridGaussianISAM.cpp
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@ -177,19 +177,19 @@ TEST(HybridGaussianElimination, IncrementalInference) {
// Test the probability values with regression tests. // Test the probability values with regression tests.
DiscreteValues assignment; DiscreteValues assignment;
EXPECT(assert_equal(0.000956191, m00_prob, 1e-5)); EXPECT(assert_equal(0.0952922, m00_prob, 1e-5));
assignment[M(0)] = 0; assignment[M(0)] = 0;
assignment[M(1)] = 0; assignment[M(1)] = 0;
EXPECT(assert_equal(0.000956191, (*discreteConditional)(assignment), 1e-5)); EXPECT(assert_equal(0.0952922, (*discreteConditional)(assignment), 1e-5));
assignment[M(0)] = 1; assignment[M(0)] = 1;
assignment[M(1)] = 0; assignment[M(1)] = 0;
EXPECT(assert_equal(0.00283728, (*discreteConditional)(assignment), 1e-5)); EXPECT(assert_equal(0.282758, (*discreteConditional)(assignment), 1e-5));
assignment[M(0)] = 0; assignment[M(0)] = 0;
assignment[M(1)] = 1; assignment[M(1)] = 1;
EXPECT(assert_equal(0.00315253, (*discreteConditional)(assignment), 1e-5)); EXPECT(assert_equal(0.314175, (*discreteConditional)(assignment), 1e-5));
assignment[M(0)] = 1; assignment[M(0)] = 1;
assignment[M(1)] = 1; assignment[M(1)] = 1;
EXPECT(assert_equal(0.00308831, (*discreteConditional)(assignment), 1e-5)); EXPECT(assert_equal(0.307775, (*discreteConditional)(assignment), 1e-5));
// Check if the clique conditional generated from incremental elimination // Check if the clique conditional generated from incremental elimination
// matches that of batch elimination. // matches that of batch elimination.
@ -199,7 +199,7 @@ TEST(HybridGaussianElimination, IncrementalInference) {
isam[M(1)]->conditional()->inner()); isam[M(1)]->conditional()->inner());
// Account for the probability terms from evaluating continuous FGs // Account for the probability terms from evaluating continuous FGs
DiscreteKeys discrete_keys = {{M(0), 2}, {M(1), 2}}; DiscreteKeys discrete_keys = {{M(0), 2}, {M(1), 2}};
vector<double> probs = {0.00095619114, 0.0031525308, 0.0028372777, 0.0030883072}; vector<double> probs = {0.095292197, 0.31417524, 0.28275772, 0.30777485};
auto expectedConditional = auto expectedConditional =
boost::make_shared<DecisionTreeFactor>(discrete_keys, probs); boost::make_shared<DecisionTreeFactor>(discrete_keys, probs);
EXPECT(assert_equal(*expectedConditional, *actualConditional, 1e-6)); EXPECT(assert_equal(*expectedConditional, *actualConditional, 1e-6));

2
gtsam/hybrid/tests/testHybridNonlinearFactorGraph.cpp
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@ -443,7 +443,7 @@ TEST(HybridFactorGraph, Full_Elimination) {
ordering.clear(); ordering.clear();
for (size_t k = 0; k < self.K - 1; k++) ordering += M(k); for (size_t k = 0; k < self.K - 1; k++) ordering += M(k);
discreteBayesNet = discreteBayesNet =
*discrete_fg.eliminateSequential(ordering, EliminateForMPE); *discrete_fg.eliminateSequential(ordering, EliminateDiscrete);
} }
// Create ordering. // Create ordering.

12
gtsam/hybrid/tests/testHybridNonlinearISAM.cpp
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@ -195,19 +195,19 @@ TEST(HybridNonlinearISAM, IncrementalInference) {
// Test the probability values with regression tests. // Test the probability values with regression tests.
DiscreteValues assignment; DiscreteValues assignment;
EXPECT(assert_equal(0.000956191, m00_prob, 1e-5)); EXPECT(assert_equal(0.0952922, m00_prob, 1e-5));
assignment[M(0)] = 0; assignment[M(0)] = 0;
assignment[M(1)] = 0; assignment[M(1)] = 0;
EXPECT(assert_equal(0.000956191, (*discreteConditional)(assignment), 1e-5)); EXPECT(assert_equal(0.0952922, (*discreteConditional)(assignment), 1e-5));
assignment[M(0)] = 1; assignment[M(0)] = 1;
assignment[M(1)] = 0; assignment[M(1)] = 0;
EXPECT(assert_equal(0.00283728, (*discreteConditional)(assignment), 1e-5)); EXPECT(assert_equal(0.282758, (*discreteConditional)(assignment), 1e-5));
assignment[M(0)] = 0; assignment[M(0)] = 0;
assignment[M(1)] = 1; assignment[M(1)] = 1;
EXPECT(assert_equal(0.00315253, (*discreteConditional)(assignment), 1e-5)); EXPECT(assert_equal(0.314175, (*discreteConditional)(assignment), 1e-5));
assignment[M(0)] = 1; assignment[M(0)] = 1;
assignment[M(1)] = 1; assignment[M(1)] = 1;
EXPECT(assert_equal(0.00308831, (*discreteConditional)(assignment), 1e-5)); EXPECT(assert_equal(0.307775, (*discreteConditional)(assignment), 1e-5));
// Check if the clique conditional generated from incremental elimination // Check if the clique conditional generated from incremental elimination
// matches that of batch elimination. // matches that of batch elimination.
@ -216,7 +216,7 @@ TEST(HybridNonlinearISAM, IncrementalInference) {
bayesTree[M(1)]->conditional()->inner()); bayesTree[M(1)]->conditional()->inner());
// Account for the probability terms from evaluating continuous FGs // Account for the probability terms from evaluating continuous FGs
DiscreteKeys discrete_keys = {{M(0), 2}, {M(1), 2}}; DiscreteKeys discrete_keys = {{M(0), 2}, {M(1), 2}};
vector<double> probs = {0.00095619114, 0.0031525308, 0.0028372777, 0.0030883072}; vector<double> probs = {0.095292197, 0.31417524, 0.28275772, 0.30777485};
auto expectedConditional = auto expectedConditional =
boost::make_shared<DecisionTreeFactor>(discrete_keys, probs); boost::make_shared<DecisionTreeFactor>(discrete_keys, probs);
EXPECT(assert_equal(*expectedConditional, *actualConditional, 1e-6)); EXPECT(assert_equal(*expectedConditional, *actualConditional, 1e-6));