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Test SumFrontals

release/4.3a0
Frank Dellaert 2023-01-01 11:23:01 -05:00
parent fa76d53f16
commit 039c9b91c9
2 changed files with 26 additions and 12 deletions
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6
gtsam/hybrid/tests/TinyHybridExample.h
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@ -28,6 +28,9 @@ using symbol_shorthand::M;
using symbol_shorthand::X; using symbol_shorthand::X;
using symbol_shorthand::Z; using symbol_shorthand::Z;
// Create mode key: 0 is low-noise, 1 is high-noise.
const DiscreteKey mode{M(0), 2};
/** /**
* Create a tiny two variable hybrid model which represents * Create a tiny two variable hybrid model which represents
* the generative probability P(z, x, n) = P(z | x, n)P(x)P(n). * the generative probability P(z, x, n) = P(z | x, n)P(x)P(n).
@ -36,9 +39,6 @@ static HybridBayesNet createHybridBayesNet(int num_measurements = 1) {
// Create hybrid Bayes net. // Create hybrid Bayes net.
HybridBayesNet bayesNet; HybridBayesNet bayesNet;
// Create mode key: 0 is low-noise, 1 is high-noise.
const DiscreteKey mode{M(0), 2};
// Create Gaussian mixture Z(0) = X(0) + noise for each measurement. // Create Gaussian mixture Z(0) = X(0) + noise for each measurement.
for (int i = 0; i < num_measurements; i++) { for (int i = 0; i < num_measurements; i++) {
const auto conditional0 = boost::make_shared<GaussianConditional>( const auto conditional0 = boost::make_shared<GaussianConditional>(

32
gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp
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@ -615,18 +615,32 @@ TEST(HybridGaussianFactorGraph, ErrorAndProbPrimeTree) {
} }
/* ****************************************************************************/ /* ****************************************************************************/
// Test creation of a tiny hybrid Bayes net. // SumFrontals just assembles Gaussian factor graphs for each assignment.
TEST(HybridBayesNet, Tiny) { TEST(HybridGaussianFactorGraph, SumFrontals) {
auto fg = tiny::createHybridGaussianFactorGraph(); auto fg = tiny::createHybridGaussianFactorGraph();
EXPECT_LONGS_EQUAL(3, fg.size()); EXPECT_LONGS_EQUAL(3, fg.size());
}
/* ****************************************************************************/ auto sum = fg.SumFrontals();
// // Test summing frontals
// TEST(HybridGaussianFactorGraph, SumFrontals) { // Get mixture factor:
// HybridGaussianFactorGraph fg; auto mixture = boost::dynamic_pointer_cast<GaussianMixtureFactor>(fg.at(0));
// fg. using GF = GaussianFactor::shared_ptr;
// }
// Get prior factor:
const GF prior =
boost::dynamic_pointer_cast<HybridGaussianFactor>(fg.at(1))->inner();
// Create DiscreteValues for both 0 and 1:
DiscreteValues d0{{M(0), 0}}, d1{{M(0), 1}};
// Expected decision tree with two factor graphs:
// f(x0;mode=0)P(x0) and f(x0;mode=1)P(x0)
GaussianMixture::Sum expected{
M(0), GaussianFactorGraph(std::vector<GF>{mixture->factor(d0), prior}),
GaussianFactorGraph(std::vector<GF>{mixture->factor(d1), prior})};
EXPECT(assert_equal(expected(d0), sum(d0)));
}
/* ************************************************************************* */ /* ************************************************************************* */
int main() { int main() {