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Remove FromConditionals

release/4.3a0
Frank Dellaert 2022-12-29 13:54:44 -05:00
parent 7ba5392525
commit d4ee6997f7
6 changed files with 25 additions and 26 deletions
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11
gtsam/hybrid/GaussianMixture.cpp
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@ -42,15 +42,12 @@ const GaussianMixture::Conditionals &GaussianMixture::conditionals() const {
} }
/* *******************************************************************************/ /* *******************************************************************************/
GaussianMixture GaussianMixture::FromConditionals( GaussianMixture::GaussianMixture(
const KeyVector &continuousFrontals, const KeyVector &continuousParents, const KeyVector &continuousFrontals, const KeyVector &continuousParents,
const DiscreteKeys &discreteParents, const DiscreteKeys &discreteParents,
const std::vector<GaussianConditional::shared_ptr> &conditionalsList) { const std::vector<GaussianConditional::shared_ptr> &conditionalsList)
Conditionals dt(discreteParents, conditionalsList); : GaussianMixture(continuousFrontals, continuousParents, discreteParents,
Conditionals(discreteParents, conditionalsList)) {}
return GaussianMixture(continuousFrontals, continuousParents, discreteParents,
dt);
}
/* *******************************************************************************/ /* *******************************************************************************/
GaussianMixture::Sum GaussianMixture::add( GaussianMixture::Sum GaussianMixture::add(

2
gtsam/hybrid/GaussianMixture.h
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@ -114,7 +114,7 @@ class GTSAM_EXPORT GaussianMixture
* @param discreteParents Discrete parents variables * @param discreteParents Discrete parents variables
* @param conditionals List of conditionals * @param conditionals List of conditionals
*/ */
static This FromConditionals( GaussianMixture(
const KeyVector &continuousFrontals, const KeyVector &continuousParents, const KeyVector &continuousFrontals, const KeyVector &continuousParents,
const DiscreteKeys &discreteParents, const DiscreteKeys &discreteParents,
const std::vector<GaussianConditional::shared_ptr> &conditionals); const std::vector<GaussianConditional::shared_ptr> &conditionals);

17
gtsam/hybrid/hybrid.i
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@ -66,13 +66,14 @@ class GaussianMixtureFactor : gtsam::HybridFactor {
#include <gtsam/hybrid/GaussianMixture.h> #include <gtsam/hybrid/GaussianMixture.h>
class GaussianMixture : gtsam::HybridFactor { class GaussianMixture : gtsam::HybridFactor {
static GaussianMixture FromConditionals( GaussianMixture(const gtsam::KeyVector& continuousFrontals,
const gtsam::KeyVector& continuousFrontals,
const gtsam::KeyVector& continuousParents, const gtsam::KeyVector& continuousParents,
const gtsam::DiscreteKeys& discreteParents, const gtsam::DiscreteKeys& discreteParents,
const std::vector<gtsam::GaussianConditional::shared_ptr>& const std::vector<gtsam::GaussianConditional::shared_ptr>&
conditionalsList); conditionalsList);
gtsam::GaussianMixtureFactor* likelihood(const gtsam::VectorValues &frontals) const;
void print(string s = "GaussianMixture\n", void print(string s = "GaussianMixture\n",
const gtsam::KeyFormatter& keyFormatter = const gtsam::KeyFormatter& keyFormatter =
gtsam::DefaultKeyFormatter) const; gtsam::DefaultKeyFormatter) const;
@ -104,7 +105,7 @@ class HybridBayesTree {
gtsam::DefaultKeyFormatter) const; gtsam::DefaultKeyFormatter) const;
}; };
#include <gtsam/hybrid/HybridBayesTree.h> #include <gtsam/hybrid/HybridBayesNet.h>
class HybridBayesNet { class HybridBayesNet {
HybridBayesNet(); HybridBayesNet();
void add(const gtsam::HybridConditional& s); void add(const gtsam::HybridConditional& s);
@ -113,6 +114,11 @@ class HybridBayesNet {
void addDiscrete(const gtsam::DiscreteConditional* s); void addDiscrete(const gtsam::DiscreteConditional* s);
void emplaceMixture(const gtsam::GaussianMixture& s); void emplaceMixture(const gtsam::GaussianMixture& s);
void emplaceMixture(const gtsam::KeyVector& continuousFrontals,
const gtsam::KeyVector& continuousParents,
const gtsam::DiscreteKeys& discreteParents,
const std::vector<gtsam::GaussianConditional::shared_ptr>&
conditionalsList);
void emplaceGaussian(const gtsam::GaussianConditional& s); void emplaceGaussian(const gtsam::GaussianConditional& s);
void emplaceDiscrete(const gtsam::DiscreteConditional& s); void emplaceDiscrete(const gtsam::DiscreteConditional& s);
void emplaceDiscrete(const gtsam::DiscreteKey& key, string spec); void emplaceDiscrete(const gtsam::DiscreteKey& key, string spec);
@ -162,9 +168,8 @@ class HybridGaussianFactorGraph {
void push_back(const gtsam::HybridBayesNet& bayesNet); void push_back(const gtsam::HybridBayesNet& bayesNet);
void push_back(const gtsam::HybridBayesTree& bayesTree); void push_back(const gtsam::HybridBayesTree& bayesTree);
void push_back(const gtsam::GaussianMixtureFactor* gmm); void push_back(const gtsam::GaussianMixtureFactor* gmm);
void push_back(gtsam::DecisionTreeFactor* factor);
void add(gtsam::DecisionTreeFactor* factor); void push_back(gtsam::JacobianFactor* factor);
void add(gtsam::JacobianFactor* factor);
bool empty() const; bool empty() const;
void remove(size_t i); void remove(size_t i);

4
gtsam/hybrid/tests/testGaussianMixture.cpp
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@ -148,9 +148,7 @@ static GaussianMixture createSimpleGaussianMixture() {
GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 0.5)); GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 0.5));
const auto conditional1 = boost::make_shared<GaussianConditional>( const auto conditional1 = boost::make_shared<GaussianConditional>(
GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 3)); GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 3));
const auto gm = GaussianMixture::FromConditionals( return GaussianMixture({Z(0)}, {X(0)}, {mode}, {conditional0, conditional1});
{Z(0)}, {X(0)}, {mode}, {conditional0, conditional1});
return gm;
} }
/* ************************************************************************* */ /* ************************************************************************* */

4
gtsam/hybrid/tests/testHybridBayesNet.cpp
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@ -88,8 +88,8 @@ TEST(HybridBayesNet, evaluateHybrid) {
// Create hybrid Bayes net. // Create hybrid Bayes net.
HybridBayesNet bayesNet; HybridBayesNet bayesNet;
bayesNet.emplaceGaussian(continuousConditional); bayesNet.emplaceGaussian(continuousConditional);
bayesNet.emplaceMixture(GaussianMixture::FromConditionals( GaussianMixture gm({X(1)}, {}, {Asia}, {conditional0, conditional1});
{X(1)}, {}, {Asia}, {conditional0, conditional1})); bayesNet.emplaceMixture(gm); // copy :-(
bayesNet.emplaceDiscrete(Asia, "99/1"); bayesNet.emplaceDiscrete(Asia, "99/1");
// Create values at which to evaluate. // Create values at which to evaluate.

5
python/gtsam/tests/test_HybridBayesNet.py
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@ -42,14 +42,13 @@ class TestHybridBayesNet(GtsamTestCase):
conditional1 = GaussianConditional(X(1), [2], I_1x1, model1) conditional1 = GaussianConditional(X(1), [2], I_1x1, model1)
dkeys = DiscreteKeys() dkeys = DiscreteKeys()
dkeys.push_back(Asia) dkeys.push_back(Asia)
gm = GaussianMixture.FromConditionals([X(1)], [], dkeys, gm = GaussianMixture([X(1)], [], dkeys, [conditional0, conditional1])
[conditional0, conditional1]) #
# Create hybrid Bayes net. # Create hybrid Bayes net.
bayesNet = HybridBayesNet() bayesNet = HybridBayesNet()
bayesNet.addGaussian(gc) bayesNet.addGaussian(gc)
bayesNet.addMixture(gm) bayesNet.addMixture(gm)
bayesNet.addDiscrete(Asia, "99/1") bayesNet.emplaceDiscrete(Asia, "99/1")
# Create values at which to evaluate. # Create values at which to evaluate.
values = HybridValues() values = HybridValues()