class Table

Hugin uses Tables for representing the conditional probability and utility potentials of individual Nodes, the probability and utility potentials on separators and Cliques of JunctionTrees, evidence potentials, etc

Public Methods

virtual ~Table()
Release the memory resources used by the application-owned Table object
double getCovariance(int config, ContinuousChanceNode *node1, ContinuousChanceNode *node2) throw(HAPI::ExceptionHugin)
Return the covariance of the conditional distribution
std::vector <double> getData() const throw(HAPI::ExceptionHugin)
Retrieve a vector holding the actual discrete data
double getMean(int config, ContinuousChanceNode *node) throw(HAPI::ExceptionHugin)
Return the mean value of the conditional probability distribution
int getSize() const throw(HAPI::ExceptionHugin)
Return the size of this table
double getVariance(int config, ContinuousChanceNode *node) throw(HAPI::ExceptionHugin)
Return the variance of the conditional probability distribution
void reorderNodes(const NodeList& order) throw(HAPI::ExceptionHugin)
Reorder the node list of this table to follow the order of the members in the NodeList
void setData(const std::vector<double>& data) throw(HAPI::ExceptionHugin)
Set the table data to be a copy of the parameter

Documentation

Hugin uses Tables for representing the conditional probability and utility potentials of individual Nodes, the probability and utility potentials on separators and Cliques of JunctionTrees, evidence potentials, etc.

A potential is a function from the state space of a set of variables into the set of real numbers. A Table is a representation of a potential.

virtual ~Table()
Release the memory resources used by the application-owned Table object

double getCovariance(int config, ContinuousChanceNode *node1, ContinuousChanceNode *node2) throw(HAPI::ExceptionHugin)
Return the covariance of the conditional distribution. The covariance of the conditional distribution of the continuous nodes node1 and node2 given the discrete state configuration config.

Returns:
A double-precision real value.
Parameters:
config - int - Index of the discrete configuration.
node1 - ContinuousChanceNode*
node2 - ContinuousChanceNode*

std::vector <double> getData() const throw(HAPI::ExceptionHugin)
Retrieve a vector holding the actual discrete data. This vector is a one-dimensional (row-major) representation of the multi-dimensional array.

Returns:
A Standard C++ Library vector of doubles.

double getMean(int config, ContinuousChanceNode *node) throw(HAPI::ExceptionHugin)
Return the mean value of the conditional probability distribution. The mean value of the conditional probability distribution of the continuous chance node node given the discrete state configuration config is returned.

Returns:
A double-precision real value.
Parameters:
config - int - Index of the discrete configuration.
node - ContinuousChanceNode*

int getSize() const throw(HAPI::ExceptionHugin)
Return the size of this table.

Returns:
int

double getVariance(int config, ContinuousChanceNode *node) throw(HAPI::ExceptionHugin)
Return the variance of the conditional probability distribution. The variance of the conditional probability of the continuous node node given the discrete state configuration config.

Returns:
A double-precision real value.
Parameters:
config - int - Index of the discrete configuration.
node - ContinuousChanceNode*

void reorderNodes(const NodeList& order) throw(HAPI::ExceptionHugin)
Reorder the node list of this table to follow the order of the members in the NodeList. order must be a permutation of the node list of this table.

Parameters:
order - NodeList

void setData(const std::vector<double>& data) throw(HAPI::ExceptionHugin)
Set the table data to be a copy of the parameter.

Parameters:
data - vector<double>

This class has no child classes.

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