Add logDensity and evaluate to GaussianBN and HybridBN #1352
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Member
dellaert
commented
Dec 28, 2022
dellaert
commented
- Add logDensity and evaluate to GaussianBN and HybridBN
- Added a test to make sure pdf integrates to 1 for 1D GaussianConditionals
- Added a test of sampling to do a Monte Carlo estimate of variance
- Also:
- renamed asDiscreteConditional to asDiscrete to be consistent
- changed the static cast to a dynamic cast for more elegant code
# Conflicts: # gtsam/hybrid/HybridBayesNet.cpp # gtsam/hybrid/tests/testHybridBayesNet.cpp
| boost::make_shared<GaussianMixture>(*gaussianMixture); | ||
| prunedGaussianMixture->prune(*decisionTree); | ||
| auto prunedGaussianMixture = boost::make_shared<GaussianMixture>(*gm); | ||
| prunedGaussianMixture->prune(*decisionTree); // imperative :-( |
There was a problem hiding this comment.
Should make an issue for this? There may have been a reason why I (a Lisp lover) made this imperative, so it'll be good to re-examine this now.
| } | ||
|
|
||
| /* ************************************************************************* */ | ||
| GaussianBayesNet HybridBayesNet::choose( | ||
| const DiscreteValues &assignment) const { | ||
| GaussianBayesNet gbn; | ||
| for (auto &&conditional : *this) { | ||
| if (conditional->isHybrid()) { | ||
| if (auto gm = conditional->asMixture()) { |
There was a problem hiding this comment.
I feel this is less readable just to save 1 line of code, but okay.
| } | ||
| } | ||
|
|
||
| DiscreteValues mpe = DiscreteFactorGraph(discrete_bn).optimize(); | ||
|
|
||
| // Given the MPE, compute the optimal continuous values. | ||
| GaussianBayesNet gbn = this->choose(mpe); | ||
| GaussianBayesNet gbn = choose(mpe); |
There was a problem hiding this comment.
I generally like using this because:
- Specifies this is a class method similar to
selfin python. - Auto-complete works better.
| @@ -284,23 +300,20 @@ AlgebraicDecisionTree<Key> HybridBayesNet::error( | |||
|
|
|||
| // Iterate over each conditional. | |||
| for (auto &&conditional : *this) { | |||
| if (conditional->isHybrid()) { | |||
| if (auto gm = conditional->asMixture()) { | |||
There was a problem hiding this comment.
Again, this is more clever but sacrifices readability...
varunagrawal
approved these changes
Dec 29, 2022
# for free
to join this conversation on GitHub.
Already have an account?
# to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.