update tests
parent
0ee9aac434
commit
d5160f7006
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@ -544,8 +544,7 @@ std::shared_ptr<HybridGaussianFactor> mixedVarianceFactor(
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auto func =
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[&](const Assignment<Key>& assignment,
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const GaussianFactorValuePair& gfv) -> GaussianFactorValuePair {
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auto [gf, val] = gfv;
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const GaussianFactor::shared_ptr& gf) -> GaussianFactorValuePair {
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if (assignment.at(mode) != tight_index) {
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double factor_log_constant = -0.5 * d * log2pi + log(1.0 / noise_loose);
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@ -183,7 +183,7 @@ TEST(HybridGaussianConditional, Likelihood2) {
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// Check the detailed JacobianFactor calculation for mode==1.
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{
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// We have a JacobianFactor
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const auto gf1 = (*likelihood)(assignment1).first;
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const auto gf1 = (*likelihood)(assignment1);
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const auto jf1 = std::dynamic_pointer_cast<JacobianFactor>(gf1);
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CHECK(jf1);
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@ -734,8 +734,8 @@ TEST(HybridGaussianFactorGraph, assembleGraphTree) {
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// Expected decision tree with two factor graphs:
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// f(x0;mode=0)P(x0) and f(x0;mode=1)P(x0)
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GaussianFactorGraphTree expected{
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M(0), GaussianFactorGraph(std::vector<GF>{(*mixture)(d0).first, prior}),
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GaussianFactorGraph(std::vector<GF>{(*mixture)(d1).first, prior})};
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M(0), GaussianFactorGraph(std::vector<GF>{(*mixture)(d0), prior}),
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GaussianFactorGraph(std::vector<GF>{(*mixture)(d1), prior})};
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EXPECT(assert_equal(expected(d0), actual(d0), 1e-5));
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EXPECT(assert_equal(expected(d1), actual(d1), 1e-5));
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