22#include <gtsam/discrete/DecisionTree-inl.h>
58 using shared_ptr = boost::shared_ptr<GaussianMixture>;
118 std::vector<GaussianConditional::shared_ptr> &&conditionals);
131 const std::vector<GaussianConditional::shared_ptr> &conditionals);
142 const std::string &s =
"GaussianMixture\n",
143 const KeyFormatter &formatter = DefaultKeyFormatter)
const override;
154 size_t nrComponents()
const;
167 boost::shared_ptr<GaussianMixtureFactor> likelihood(
171 const Conditionals &conditionals()
const;
208 double error(
const HybridValues &values)
const override;
225 double logProbability(
const HybridValues &values)
const override;
228 double evaluate(
const HybridValues &values)
const override;
232 return evaluate(values);
259 friend class boost::serialization::access;
260 template <
class Archive>
261 void serialize(Archive &ar,
const unsigned int ) {
262 ar &BOOST_SERIALIZATION_BASE_OBJECT_NVP(
BaseFactor);
264 ar &BOOST_SERIALIZATION_NVP(conditionals_);
Decision Tree for use in DiscreteFactors.
specialized key for discrete variables
A set of GaussianFactors, indexed by a set of discrete keys.
Base class for conditional densities.
Conditional Gaussian Base class.
Global functions in a separate testing namespace.
Definition chartTesting.h:28
FastVector< Key > KeyVector
Define collection type once and for all - also used in wrappers.
Definition Key.h:86
void print(const Matrix &A, const string &s, ostream &stream)
print without optional string, must specify cout yourself
Definition Matrix.cpp:156
std::set< DiscreteKey > DiscreteKeysAsSet(const DiscreteKeys &discreteKeys)
Return the DiscreteKey vector as a set.
Definition GaussianMixture.cpp:221
std::function< std::string(Key)> KeyFormatter
Typedef for a function to format a key, i.e. to convert it to a string.
Definition Key.h:35
std::function< double(const Assignment< Key > &, double)> prunerFunc(const DecisionTreeFactor &prunedDecisionTree, const HybridConditional &conditional)
Helper function to get the pruner functional.
Definition HybridBayesNet.cpp:66
A manifold defines a space in which there is a notion of a linear tangent space that can be centered ...
Definition concepts.h:30
Template to create a binary predicate.
Definition Testable.h:111
A helper that implements the traits interface for GTSAM types.
Definition Testable.h:151
An algebraic decision tree fixes the range of a DecisionTree to double.
Definition AlgebraicDecisionTree.h:38
An assignment from labels to value index (size_t).
Definition Assignment.h:37
A discrete probabilistic factor.
Definition DecisionTreeFactor.h:45
DiscreteKeys is a set of keys that can be assembled using the & operator.
Definition DiscreteKey.h:39
A map from keys to values.
Definition DiscreteValues.h:34
A conditional of gaussian mixtures indexed by discrete variables, as part of a Bayes Network.
Definition GaussianMixture.h:55
double logNormalizationConstant() const override
The log normalization constant is max of the the individual log-normalization constants.
Definition GaussianMixture.h:161
double operator()(const HybridValues &values) const
Evaluate probability density, sugar.
Definition GaussianMixture.h:231
GaussianMixture()=default
Default constructor, mainly for serialization.
Base class for truly hybrid probabilistic factors.
Definition HybridFactor.h:52
HybridValues represents a collection of DiscreteValues and VectorValues.
Definition HybridValues.h:38
Definition Conditional.h:64
boost::shared_ptr< This > shared_ptr
shared_ptr to this class
Definition GaussianConditional.h:46
VectorValues represents a collection of vector-valued variables associated each with a unique integer...
Definition VectorValues.h:74