graph: Utilities to manipulate graphs

In bnlearn: Bayesian Network Structure Learning, Parameter Learning and Inference

Utilities to manipulate graphs

Description

Check and manipulate graph-related properties of an object of class bn.

Usage

# check whether the graph is acyclic/completely directed.
acyclic(x, directed = FALSE, debug = FALSE)
directed(x)
# check whether there is a path between two nodes.
path.exists(x, from, to, direct = TRUE, underlying.graph = FALSE, debug = FALSE)
# build the skeleton or a complete orientation of the graph.
skeleton(x)
pdag2dag(x, ordering)
# build a subgraph spanning a subset of nodes.
subgraph(x, nodes)

Arguments

x	an object of class bn. skeleton(), acyclic(), directed() and path.exixsts() also accept objects of class bn.fit.
from	a character string, the label of a node.
to	a character string, the label of a node (different from from).
direct	a boolean value. If FALSE ignore any arc between from and to when looking for a path.
underlying.graph	a boolean value. If TRUE the underlying undirected graph is used instead of the (directed) one from the x argument.
ordering	the labels of all the nodes in the graph; their order is the node ordering used to set the direction of undirected arcs.
nodes	the labels of the nodes that induce the subgraph.
directed	a boolean value. If TRUE only completely directed cycles are considered; otherwise undirected arcs will also be considered and treated as arcs present in both directions.
debug	a boolean value. If TRUE a lot of debugging output is printed; otherwise the function is completely silent.

Value

acyclic(), path() and directed() return a boolean value.
skeleton(), pdag2dag() and subgraph() return an object of class bn.

Author(s)

Marco Scutari

References

Bang-Jensen J, Gutin G (2009). Digraphs: Theory, Algorithms and Applications. Springer, 2nd edition.

Examples

data(learning.test)
cpdag = pc.stable(learning.test)

acyclic(cpdag)
directed(cpdag)
dag = pdag2dag(cpdag, ordering = LETTERS[1:6])
dag
directed(dag)
skeleton(dag)

bnlearn documentation built on Sept. 11, 2024, 8:27 p.m.