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HAPI::Model Class Reference

List of all members.

Detailed Description

A Model is a compact description of a table.

A model consists of a list of discrete nodes and a set of expressions (one expresion per configuration of states in the nodes.

See also:
Expression

Node

NodeList


Public Member Functions

 Model (DiscreteChanceNode *belongsToNode, const NodeList &modelNodes)
 Construct a model over a discrete chance node given a set of Nodes.

 Model (UtilityNode *belongsToNode, const NodeList &modelNodes)
 Construct a model over a utility node given a set of Nodes.

 ~Model () throw ()
 Delete the Model.

ExpressiongetExpression (size_t index) const
 Return the Expression associated with a pecific configuration of the Nodes in the Model.

NodeList getNodes () const
 Return a NodeList containing the Nodes in Model.

void setExpression (size_t index, Expression *e)
 Associate an Expression with a specific configuration of the Model Nodes.

size_t size () const
 Return the number of configuration of the Nodes of Model.

void setNumberOfSamplesPerInterval (size_t count)
 Sets the number of values taken within each bounded interval of an interval parent when generating the conditional probability table for a node with interval parents.

size_t getNumberOfSamplesPerInterval () const
 Returns the number of values per interval used when generating the conditional probability table for a node with interval parents.


Member Function Documentation

size_t HAPI::Model::getNumberOfSamplesPerInterval  )  const
 

Returns the number of values per interval used when generating the conditional probability table for a node with interval parents.

Returns:
size_t specifying the number of samples per interval

void HAPI::Model::setNumberOfSamplesPerInterval size_t  count  ) 
 

Sets the number of values taken within each bounded interval of an interval parent when generating the conditional probability table for a node with interval parents.

When generating the conditional probability table for a node with interval nodes as parents, a number of values are taken within each bounded interval of an interval parent. By default, the interval is divided into 25 subintervals, and the midpoints of these subintervals are then used in the computation of the value of the child.

Parameters:
count The number of subintervals


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