For using the igraph C library
This glossary defines common terms used throughout the igraph documentation.
attribute: A piece of data associated with a vertex, an edge, or the graph itself. The igraph C library currently supports numeric, string and Boolean attribute values, and provides a means for implementing attribute handlers that support custom types.
adjacent: Two vertices are called adjacent if there is an edge connecting them. This term describes a vertex-to-vertex relation.
adjacency list: A data structure that associates a list of neighbours (i.e. adjacent vertices) to each vertex.
adjacency matrix: A
representation of a graph as a square matrix.
A_ij
gives the number of edge endpoints
connecting from the i
th vertex to the
j
th vertex. Conventionally, the diagonal of
the adjacency matrix of an undirected graph contains
twice the number of self-loops. All igraph
functions follow this convention unless noted otherwise.
biadjacency matrix: Analogous
to the adjacency matrix, but used for bipartite graphs. Element
B_ij
gives the number of edges from the
i
th vertex of the first group to the
j
th vertex of the second group.
bipartite graph: A graph whose vertices can be partitioned into two groups in such a way that connections are present only between members of different groups.
complete graph: Also called full graph within the context of igraph, a graph in which all pairs of vertices are connected to each other.
connected graph: A connected graph consists of a single component, in which any vertex is reachable from any other. In igraph, the null graph is not considered connected, as it has not one, but zero components.
edge: A connection between two vertices, also called a link. In igraph, edges are referred to by integer indices called edge IDs.
finalizer stack: A global stack used internally by igraph to keep track of currently allocated objects and their destructors, so that they can be automatically destroyed in case of an error.
game: Within igraph, this term is used for stochastic graph generators, i.e. functions that sample from random graph models.
graph or network: A set of vertices with connections between them. In igraph, graphs may carry associated data in the form of vertex, edge or graph attributes.
incident: An edge is called incident to the vertices that are its endpoints. This term describes a vertex-to-edge relation.
incidence list: A data structure that associates a list of incident edges to each vertex.
incidence matrix: A matrix describing the incidence relation between vertices (rows) and edges (columns).
membership vector: Membership
vectors are a means of encoding a partitioning of items, usually
vertices, into several groups. The i
th
element of the vector gives an integer identifier of the group
the i
th vertex belongs to. Membership vectors
are typically used to describe a vertex clustering obtained
through community detection, or by identifying the connected
components of a graph.
multi-edges or
parallel edges: More than one
edge connecting the same two vertices. In a directed graph,
a -> b, a -> b
are considered parallel
edges, but a -> b, a <- b
are not.
null graph: A graph with no vertices (and no edges).
self-loop, self-edge, or simply loop: An edge that connects a vertex to itself.
simple graph: A graph that does not have self-loops or multi-edges.
singleton graph: A graph having a single vertex. This term usually refers to a single vertex with no edges, but note that self-loops may in principle be present.
vertex: Graphs consist of vertices, also called nodes, that are connected to each other. In igraph, vertices are referred to by integer indices called vertex IDs.
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