Explanation and analysis

This tools aimed to provide some different views on the Bayesian network in order to explore its qualitative and/or quantitave behaviours.

class pyAgrum.JunctionTreeGenerator

JunctionTreeGenerator is use to generate junction tree or binary junction tree from bayesian networks.

Available ructors:

JunctionTreeGenerator() -> JunctionTreeGenerator

binaryJoinTree(JunctionTreeGenerator self, UndiGraph g, PyObject * partial_order=None)

binaryJoinTree(JunctionTreeGenerator self, DAG dag, PyObject * partial_order=None) -> CliqueGraph binaryJoinTree(JunctionTreeGenerator self, BayesNet bn, PyObject * partial_order=None) -> CliqueGraph

Computes the binary joint tree for its parameters. If the first parameter is a graph, the heurisitcs assume that all the node have the same domain size (2). If given, the heuristic takes into account the partial order for its elimination order.

Parameters:

• g (pyAgrum.UndiGraph) – a undirected graph
• dag (pyAgrum.DAG) – a dag
• bn (pyAgrum.BayesNet) – a BayesianNetwork
• partial_order (List[List[int]]) – a partial order among the nodeIDs

Returns:

the current binary joint tree

Return type:

pyAgrum.CliqueGraph

eliminationOrder(JunctionTreeGenerator self, UndiGraph g, PyObject * partial_order=None)

eliminationOrder(JunctionTreeGenerator self, DAG dag, PyObject * partial_order=None) -> PyObject eliminationOrder(JunctionTreeGenerator self, BayesNet bn, PyObject * partial_order=None) -> PyObject

Computes the elimination for its parameters. If the first parameter is a graph, the heurisitcs assume that all the node have the same domain size (2). If given, the heuristic takes into account the partial order for its elimination order.

Parameters:

• g (pyAgrum.UndiGraph) – a undirected graph
• dag (pyAgrum.DAG) – a dag
• bn (pyAgrum.BayesNet) – a BayesianNetwork
• partial_order (List[List[int]]) – a partial order among the nodeIDs

Returns:

the current elimination order.

Return type:

pyAgrum.CliqueGraph

junctionTree(JunctionTreeGenerator self, UndiGraph g, PyObject * partial_order=None)

junctionTree(JunctionTreeGenerator self, DAG dag, PyObject * partial_order=None) -> CliqueGraph junctionTree(JunctionTreeGenerator self, BayesNet bn, PyObject * partial_order=None) -> CliqueGraph

Computes the junction tree for its parameters. If the first parameter is a graph, the heurisitcs assume that all the node have the same domain size (2). If given, the heuristic takes into account the partial order for its elimination order.

Parameters:

• g (pyAgrum.UndiGraph) – a undirected graph
• dag (pyAgrum.DAG) – a dag
• bn (pyAgrum.BayesNet) – a BayesianNetwork
• partial_order (List[List[int]]) – a partial order among the nodeIDs

Returns:

the current junction tree.

Return type:

pyAgrum.CliqueGraph

class pyAgrum.EssentialGraph(*args)

Proxy of C++ pyAgrum.EssentialGraph class.

arcs(EssentialGraph self)

Returns:The lisf of arcs in the EssentialGraph Return type:list

children(EssentialGraph self, int id)

Parameters:id (int) – the id of the parent Returns:the set of all the children Return type:Set

edges(EssentialGraph self)

Returns:the list of the edges Return type:List

ids()

Deprecated method in pyAgrum>0.12.0. See nodes instead.

mixedGraph(EssentialGraph self)

Returns:the mixed graph Return type:pyAgrum.MixedGraph

neighbours(EssentialGraph self, int id)

Parameters:id (int) – the id of the checked node Returns:The set of edges adjacent to the given node Return type:Set

nodes(EssentialGraph self)

parents(EssentialGraph self, int id)

Parameters:id – The id of the child node Returns:the set of the parents ids. Return type:Set

size(EssentialGraph self)

Returns:the number of nodes in the graph Return type:int

sizeArcs(EssentialGraph self)

Returns:the number of arcs in the graph Return type:int

sizeEdges(EssentialGraph self)

Returns:the number of edges in the graph Return type:int

sizeNodes(EssentialGraph self)

Returns:the number of nodes in the graph Return type:int

skeleton(EssentialGraph self)

toDot(EssentialGraph self)

Returns:a friendly display of the graph in DOT format Return type:str

class pyAgrum.MarkovBlanket(*args)

Proxy of C++ pyAgrum.MarkovBlanket class.

arcs(MarkovBlanket self)

Returns:the list of the arcs Return type:List

children(MarkovBlanket self, int id)

Parameters:id (int) – the id of the parent Returns:the set of all the children Return type:Set

hasSameStructure(MarkovBlanket self, DAGmodel other)

Parameters:pyAgrum.DAGmodel – a direct acyclic model Returns:True if all the named node are the same and all the named arcs are the same Return type:bool

mb(MarkovBlanket self)

Returns:a copy of the directed graph Return type:pyAgrum.DiGraph

nodes(MarkovBlanket self)

Returns:the set of ids Return type:set

parents(MarkovBlanket self, int id)

Parameters:id – The id of the child node Returns:the set of the parents ids. Return type:Set

size(MarkovBlanket self)

Returns:the number of nodes in the graph Return type:int

sizeArcs(MarkovBlanket self)

Returns:the number of arcs in the graph Return type:int

sizeNodes(MarkovBlanket self)

Returns:the number of nodes in the graph Return type:int

toDot(MarkovBlanket self)

Returns:a friendly display of the graph in DOT format Return type:str