26 #ifndef GUM_MULTI_DIM_NOISY_OR_NET_H 27 #define GUM_MULTI_DIM_NOISY_OR_NET_H 51 template <
typename GUM_SCALAR >
61 GUM_SCALAR default_weight = (GUM_SCALAR)1.0);
121 virtual const std::string&
name()
const;
127 #ifndef GUM_NO_EXTERN_TEMPLATE_CLASS 132 template <
typename GUM_SCALAR >
gum is the global namespace for all aGrUM entities
Abstract base class for all multi dimensionnal containers.
Abstract base class for all multi dimensionnal Causal Independency models.
std::ostream & operator<<(std::ostream &output, const BayesNet< GUM_SCALAR > &bn)
Prints map's DAG in output using the Graphviz-dot format.
abstract class for Conditional Indepency Models
const std::string toString() const
Returns the real name of the multiDimArray.
virtual const std::string & name() const
Returns the real name of the multiDimArray.
virtual MultiDimContainer< GUM_SCALAR > * newFactory() const
This method creates a clone of this object, withouth its content (including variable), you must use this method if you want to ensure that the generated object has the same type than the object containing the called newFactory()
Set of pairs of elements with fast search for both elements.
class for NoisyOR-net implementation as multiDim
Class for assigning/browsing values to tuples of discrete variables.
MultiDimNoisyORNet(GUM_SCALAR external_weight, GUM_SCALAR default_weight=(GUM_SCALAR) 1.0)
Default constructor.
virtual ~MultiDimNoisyORNet()
Destructor.