fix tests
parent
f9e3280d75
commit
3abff90fb4
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@ -81,7 +81,7 @@ TEST(GaussianMixture, GaussianMixtureModel) {
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auto eliminationResult =
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gmm.toFactorGraph({{Z(0), Vector1(midway)}}).eliminateSequential();
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auto pMid = eliminationResult->at(0)->asDiscrete<TableDistribution>();
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EXPECT(assert_equal(TableDistribution(m, "60/40"), *pMid));
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EXPECT(assert_equal(TableDistribution(m, "60 40"), *pMid));
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// Everywhere else, the result should be a sigmoid.
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for (const double shift : {-4, -2, 0, 2, 4}) {
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@ -141,9 +141,8 @@ TEST(GaussianMixture, GaussianMixtureModel2) {
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EXPECT(assert_equal(expectedDiscretePosterior,
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eliminationResultMax->discretePosterior(vv)));
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auto pMax =
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*eliminationResultMax->at(0)->asDiscrete<TableDistribution>();
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EXPECT(assert_equal(TableDistribution(m, "42/58"), pMax, 1e-4));
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auto pMax = *eliminationResultMax->at(0)->asDiscrete<TableDistribution>();
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EXPECT(assert_equal(TableDistribution(m, "42 58"), pMax, 1e-4));
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// Everywhere else, the result should be a bell curve like function.
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for (const double shift : {-4, -2, 0, 2, 4}) {
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@ -464,7 +464,7 @@ TEST(HybridEstimation, EliminateSequentialRegression) {
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// Create expected discrete conditional on m0.
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DiscreteKey m(M(0), 2);
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TableDistribution expected(m % "0.51341712/1"); // regression
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TableDistribution expected(m, "0.51341712 1"); // regression
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// Eliminate into BN using one ordering
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const Ordering ordering1{X(0), X(1), M(0)};
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@ -650,7 +650,7 @@ TEST(HybridGaussianFactorGraph, EliminateTiny1) {
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mode, std::vector{conditional0, conditional1});
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// Add prior on mode.
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expectedBayesNet.emplace_shared<TableDistribution>(mode, "74/26");
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expectedBayesNet.emplace_shared<TableDistribution>(mode, "74 26");
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// Test elimination
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const auto posterior = fg.eliminateSequential();
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