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use auto&& in for loops

release/4.3a0
Varun Agrawal 2022-12-24 10:17:01 +05:30
parent 0be2a679c0
commit b0235239ce
1 changed files with 8 additions and 8 deletions
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16
gtsam/hybrid/HybridBayesNet.cpp
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@ -33,8 +33,7 @@ DecisionTreeFactor::shared_ptr HybridBayesNet::discreteConditionals() const {
// the discrete conditionals added to it.
DecisionTreeFactor dtFactor;
for (size_t i = 0; i < this->size(); i++) {
HybridConditional::shared_ptr conditional = this->at(i);
for (auto &&conditional : *this) {
if (conditional->isDiscrete()) {
// Convert to a DecisionTreeFactor and add it to the main factor.
DecisionTreeFactor f(*conditional->asDiscreteConditional());
@ -104,6 +103,7 @@ void HybridBayesNet::updateDiscreteConditionals(
const DecisionTreeFactor::shared_ptr &prunedDecisionTree) {
KeyVector prunedTreeKeys = prunedDecisionTree->keys();
// Loop with index since we need it later.
for (size_t i = 0; i < this->size(); i++) {
HybridConditional::shared_ptr conditional = this->at(i);
if (conditional->isDiscrete()) {
@ -193,7 +193,7 @@ DiscreteConditional::shared_ptr HybridBayesNet::atDiscrete(size_t i) const {
GaussianBayesNet HybridBayesNet::choose(
const DiscreteValues &assignment) const {
GaussianBayesNet gbn;
for (const sharedConditional &conditional : *this) {
for (auto &&conditional : *this) {
if (conditional->isHybrid()) {
// If conditional is hybrid, select based on assignment.
GaussianMixture gm = *conditional->asMixture();
@ -216,7 +216,7 @@ GaussianBayesNet HybridBayesNet::choose(
HybridValues HybridBayesNet::optimize() const {
// Solve for the MPE
DiscreteBayesNet discrete_bn;
for (auto &conditional : *this) {
for (auto &&conditional : *this) {
if (conditional->isDiscrete()) {
discrete_bn.push_back(conditional->asDiscreteConditional());
}
@ -236,10 +236,10 @@ VectorValues HybridBayesNet::optimize(const DiscreteValues &assignment) const {
}
/* ************************************************************************* */
HybridValues HybridBayesNet::sample(HybridValues& given,
HybridValues HybridBayesNet::sample(HybridValues &given,
std::mt19937_64 *rng) const {
DiscreteBayesNet dbn;
for (const sharedConditional &conditional : *this) {
for (auto &&conditional : *this) {
if (conditional->isDiscrete()) {
// If conditional is discrete-only, we add to the discrete Bayes net.
dbn.push_back(conditional->asDiscreteConditional());
@ -261,7 +261,7 @@ HybridValues HybridBayesNet::sample(std::mt19937_64 *rng) const {
}
/* ************************************************************************* */
HybridValues HybridBayesNet::sample(HybridValues& given) const {
HybridValues HybridBayesNet::sample(HybridValues &given) const {
return sample(given, &kRandomNumberGenerator);
}
@ -283,7 +283,7 @@ AlgebraicDecisionTree<Key> HybridBayesNet::error(
AlgebraicDecisionTree<Key> error_tree(0.0);
// Iterate over each conditional.
for (const sharedConditional &conditional : *this) {
for (auto &&conditional : *this) {
if (conditional->isHybrid()) {
// If conditional is hybrid, select based on assignment and compute error.
GaussianMixture::shared_ptr gm = conditional->asMixture();