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undo change in GaussianMixture

release/4.3a0
Varun Agrawal 2024-08-20 15:26:04 -04:00
parent 6b1d89d0a7
commit 6d9fc8e5f2
1 changed files with 22 additions and 22 deletions
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44
gtsam/hybrid/GaussianMixture.cpp
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@ -71,23 +71,26 @@ GaussianMixture::GaussianMixture(
Conditionals(discreteParents, conditionals)) {} Conditionals(discreteParents, conditionals)) {}
/* *******************************************************************************/ /* *******************************************************************************/
GaussianBayesNetTree GaussianMixture::asGaussianBayesNetTree() const { // TODO(dellaert): This is copy/paste: GaussianMixture should be derived from
auto wrap = [](const GaussianConditional::shared_ptr &gc) { // GaussianMixtureFactor, no?
if (gc) { GaussianFactorGraphTree GaussianMixture::add(
return GaussianBayesNet{gc}; const GaussianFactorGraphTree &sum) const {
} else { using Y = GaussianFactorGraph;
return GaussianBayesNet(); auto add = [](const Y &graph1, const Y &graph2) {
} auto result = graph1;
result.push_back(graph2);
return result;
}; };
return {conditionals_, wrap}; const auto tree = asGaussianFactorGraphTree();
return sum.empty() ? tree : sum.apply(tree, add);
} }
/* *******************************************************************************/ /* *******************************************************************************/
GaussianFactorGraphTree GaussianMixture::asGaussianFactorGraphTree() const { GaussianFactorGraphTree GaussianMixture::asGaussianFactorGraphTree() const {
auto wrap = [](const GaussianBayesNet &gbn) { auto wrap = [](const GaussianConditional::shared_ptr &gc) {
return GaussianFactorGraph(gbn); return GaussianFactorGraph{gc};
}; };
return {this->asGaussianBayesNetTree(), wrap}; return {conditionals_, wrap};
} }
/* /*
@ -108,18 +111,15 @@ GaussianBayesNetTree GaussianMixture::add(
} }
/* *******************************************************************************/ /* *******************************************************************************/
// TODO(dellaert): This is copy/paste: GaussianMixture should be derived from GaussianBayesNetTree GaussianMixture::asGaussianBayesNetTree() const {
// GaussianMixtureFactor, no? auto wrap = [](const GaussianConditional::shared_ptr &gc) {
GaussianFactorGraphTree GaussianMixture::add( if (gc) {
const GaussianFactorGraphTree &sum) const { return GaussianBayesNet{gc};
using Y = GaussianFactorGraph; } else {
auto add = [](const Y &graph1, const Y &graph2) { return GaussianBayesNet();
auto result = graph1; }
result.push_back(graph2);
return result;
}; };
const auto tree = asGaussianFactorGraphTree(); return {conditionals_, wrap};
return sum.empty() ? tree : sum.apply(tree, add);
} }
/* *******************************************************************************/ /* *******************************************************************************/