Made CheckInvariants a static method in Conditional.*
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b99d464049
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cd2d37e724
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@ -63,4 +63,22 @@ double Conditional<FACTOR, DERIVEDCONDITIONAL>::normalizationConstant() const {
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return std::exp(logNormalizationConstant());
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}
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/* ************************************************************************* */
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template <class FACTOR, class DERIVEDCONDITIONAL>
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template <class VALUES>
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bool Conditional<FACTOR, DERIVEDCONDITIONAL>::CheckInvariants(
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const DERIVEDCONDITIONAL& conditional, const VALUES& values) {
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const double probability = conditional.evaluate(values);
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if (probability < 0.0 || probability > 1.0)
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return false; // probability is not in [0,1]
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const double logProb = conditional.logProbability(values);
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if (std::abs(probability - std::exp(logProb)) > 1e-9)
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return false; // logProb is not consistent with probability
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const double expected =
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conditional.logNormalizationConstant() - conditional.error(values);
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if (std::abs(logProb - expected) > 1e-9)
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return false; // logProb is not consistent with error
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return true;
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}
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} // namespace gtsam
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@ -181,6 +181,10 @@ namespace gtsam {
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/** Mutable iterator pointing past the last parent key. */
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typename FACTOR::iterator endParents() { return asFactor().end(); }
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template <class VALUES>
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static bool CheckInvariants(const DERIVEDCONDITIONAL& conditional,
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const VALUES& values);
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/// @}
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private:
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@ -135,23 +135,6 @@ static const auto unitPrior =
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noiseModel::Isotropic::Sigma(1, sigma));
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} // namespace density
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/* ************************************************************************* */
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template <class VALUES>
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bool checkInvariants(const GaussianConditional& conditional,
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const VALUES& values) {
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const double probability = conditional.evaluate(values);
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if (probability < 0.0 || probability > 1.0)
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return false; // probability is not in [0,1]
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const double logProb = conditional.logProbability(values);
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if (std::abs(probability - std::exp(logProb)) > 1e-9)
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return false; // logProb is not consistent with probability
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const double expected =
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conditional.logNormalizationConstant() - conditional.error(values);
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if (std::abs(logProb - expected) > 1e-9)
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return false; // logProb is not consistent with error
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return true;
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}
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/* ************************************************************************* */
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// Check that the evaluate function matches direct calculation with R.
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TEST(GaussianConditional, Evaluate1) {
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@ -174,8 +157,9 @@ TEST(GaussianConditional, Evaluate1) {
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// Check Invariants at the mean and a different value
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for (auto vv : {mean, VectorValues{{key, Vector1(4)}}}) {
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EXPECT(checkInvariants(density::unitPrior, vv));
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EXPECT(checkInvariants(density::unitPrior, HybridValues{vv, {}, {}}));
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EXPECT(GaussianConditional::CheckInvariants(density::unitPrior, vv));
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EXPECT(GaussianConditional::CheckInvariants(density::unitPrior,
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HybridValues{vv, {}, {}}));
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}
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// Let's numerically integrate and see that we integrate to 1.0.
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@ -206,8 +190,9 @@ TEST(GaussianConditional, Evaluate2) {
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// Check Invariants at the mean and a different value
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for (auto vv : {mean, VectorValues{{key, Vector1(4)}}}) {
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EXPECT(checkInvariants(density::widerPrior, vv));
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EXPECT(checkInvariants(density::widerPrior, HybridValues{vv, {}, {}}));
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EXPECT(GaussianConditional::CheckInvariants(density::widerPrior, vv));
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EXPECT(GaussianConditional::CheckInvariants(density::widerPrior,
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HybridValues{vv, {}, {}}));
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}
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// Let's numerically integrate and see that we integrate to 1.0.
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@ -422,8 +407,9 @@ TEST(GaussianConditional, FromMeanAndStddev) {
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// Check Invariants for both conditionals
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for (auto conditional : {conditional1, conditional2}) {
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EXPECT(checkInvariants(conditional, values));
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EXPECT(checkInvariants(conditional, HybridValues{values, {}, {}}));
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EXPECT(GaussianConditional::CheckInvariants(conditional, values));
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EXPECT(GaussianConditional::CheckInvariants(conditional,
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HybridValues{values, {}, {}}));
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}
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}
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