edgeData:attrData instance for edge attributes.nodeData:attrData instance for node attributes.graphData:list for graph-level
attributes. Only mandatory list item is edgemode which
indicates whether edges are "directed" or
"undirected"renderInfo:list of graph rendering information.signature(object = "graph"):A print method for
the graph.signature(object = "graph"): find all nodes
accessible from the specified node. signature(x = "graph"): compute the
complement of the supplied graph. The complement is defined with
respect to the complete graph on the nodes in x.
Currently this returns an object of class graphNEL.signature(object = "graph"): find the
connected components of a graph.signature(object = "graph", Nodes = "missing"):
find the degree of a node (number of coincident edges).signature(object = "graph", Nodes = "ANY"): as
above. signature(object = "MultiGraph", Nodes = "missing"):
find the degree of a node (number of coincident edges).signature(object = "graph"): execute a depth first
search on a graph starting with the specified node.signature(object="graph", which="character"):
return the edges indicated by which. which can be
missing in which case all edges are returned or it can be a
character vector with the node labels indicating the nodes whose
edge lists are wanted.signature(object="graph"): return the
edgemode for the graph. Currently this can be either
directed or undirected.signature(object="graph",
value="character"): set the edgemode
for the graph. Currently this can be either
directed or undirected.edges method.signature(x = "graph", y = "graph"): compute the
intersection of the two supplied graphs. They must have identical
nodes. Currently this returns an object of class
graphNEL. With edge weights of 1 for any matching edge.signature(from="character",
to="character"): Determine if edges exists between nodes.signature(object = "graph"): A boolean
that details if a graph is fully connected or not.TRUE if the graph object has
directed edges and FALSE otherwise.signature(x = "graph", y = "graph"): returns the
joining of two graphs. Nodes which are shared by both graphs will
have their edges merged. Note that edgeWeights for the resulting
graph are all set to 1. Users wishing to preserve weights in
a join operation must
perform addEdge operations on the resulting graph to restore weights.graph class to reset the node
labelssignature(object = "graph"): compute the
number of edges in a graph.signature(object = "graph"): compute the
number of nodes in a graph. plot,graph-method method in the Rgraphviz packagesignature(x = "graph", y = "graph"): compute the
union of the two supplied graphs. They must have identical
nodes. Currently this returns an object of class graphNEL.signature(object = "graph"): Returns a
vector of the edge names for this graph, using the format
tail\~head, where head is the name of the tail node
and head is the name of the head node.signature(object = "graph"): Updates old
instances of graph objects.degree returns either a named vector (names correspond to the
nodes in the graph) containing the degree for undirected graphs or a
list with two components, inDegree and outDegree for
directed graphs. connComp returns a list of the connected components. Each
element of this list contains the labels of all nodes in that
component.
For a directed graph or digraph the underlying
graph is the graph that results from removing all direction from
the edges. This can be achieved using the function ugraph.
A weakly connected component of a digraph is one that is
a connected component of the underlying graph. This is the default for
connComp. A digraph is strongly connected if
every two vertices are mutually reachable. A strongly connected
component of a digraph, D, is a maximal strongly
connected subdigraph of D. See the RBGL package for an
implementation of Trajan's algorithm to find strongly
connected components (strongComp).
In the graph implementation of connComp weak
connectivity is used. If the argument to connComp is a
directed graph then ugraph is called to create the
underlying undirected graph and that is used to compute connected
components. Users who want different behavior are encouraged to use
RBGL.
graphNEL-class, graphAM-class,
distGraph-class.
set.seed(123)
g1 <- randomGraph(letters[1:10], 1:4, p= 0.3)
numEdges(g1)
edgeNames(g1)
edges(g1)
edges(g1, c("a","d")) # those incident to 'a' or 'd'
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