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ratio tests for GaussianMixtureFactor

release/4.3a0
Varun Agrawal 2024-09-03 17:39:52 -04:00
parent 3f782a4ae7
commit 997d0b411b
1 changed files with 40 additions and 0 deletions
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40
gtsam/hybrid/tests/testGaussianMixtureFactor.cpp
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@ -519,6 +519,24 @@ TEST(GaussianMixtureFactor, TwoStateModel2) {
{ {
// Start with no measurement on x1, only on x0 // Start with no measurement on x1, only on x0
HybridGaussianFactorGraph gfg = hbn.toFactorGraph(given); HybridGaussianFactorGraph gfg = hbn.toFactorGraph(given);
{
VectorValues vv{
{X(0), Vector1(0.0)}, {X(1), Vector1(1.0)}, {Z(0), Vector1(0.5)}};
HybridValues hv0(vv, DiscreteValues{{M(1), 0}}),
hv1(vv, DiscreteValues{{M(1), 1}});
EXPECT_DOUBLES_EQUAL(gfg.error(hv0) / hbn.error(hv0),
gfg.error(hv1) / hbn.error(hv1), 1e-9);
}
{
VectorValues vv{
{X(0), Vector1(0.5)}, {X(1), Vector1(3.0)}, {Z(0), Vector1(0.5)}};
HybridValues hv0(vv, DiscreteValues{{M(1), 0}}),
hv1(vv, DiscreteValues{{M(1), 1}});
EXPECT_DOUBLES_EQUAL(gfg.error(hv0) / hbn.error(hv0),
gfg.error(hv1) / hbn.error(hv1), 1e-9);
}
HybridBayesNet::shared_ptr bn = gfg.eliminateSequential(); HybridBayesNet::shared_ptr bn = gfg.eliminateSequential();
// Since no measurement on x1, we a 50/50 probability // Since no measurement on x1, we a 50/50 probability
@ -535,6 +553,28 @@ TEST(GaussianMixtureFactor, TwoStateModel2) {
given.insert(z1, Vector1(2.2)); given.insert(z1, Vector1(2.2));
HybridGaussianFactorGraph gfg = hbn.toFactorGraph(given); HybridGaussianFactorGraph gfg = hbn.toFactorGraph(given);
{
VectorValues vv{{X(0), Vector1(0.0)},
{X(1), Vector1(1.0)},
{Z(0), Vector1(0.5)},
{Z(1), Vector1(2.2)}};
HybridValues hv0(vv, DiscreteValues{{M(1), 0}}),
hv1(vv, DiscreteValues{{M(1), 1}});
EXPECT_DOUBLES_EQUAL(gfg.error(hv0) / hbn.error(hv0),
gfg.error(hv1) / hbn.error(hv1), 1e-9);
}
{
VectorValues vv{{X(0), Vector1(0.5)},
{X(1), Vector1(3.0)},
{Z(0), Vector1(0.5)},
{Z(1), Vector1(2.2)}};
HybridValues hv0(vv, DiscreteValues{{M(1), 0}}),
hv1(vv, DiscreteValues{{M(1), 1}});
EXPECT_DOUBLES_EQUAL(gfg.error(hv0) / hbn.error(hv0),
gfg.error(hv1) / hbn.error(hv1), 1e-9);
}
HybridBayesNet::shared_ptr bn = gfg.eliminateSequential(); HybridBayesNet::shared_ptr bn = gfg.eliminateSequential();
// Since we have a measurement on z2, we get a definite result // Since we have a measurement on z2, we get a definite result