1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58
|
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/structural.properties.R
\name{laplacian_matrix}
\alias{graph.laplacian}
\alias{laplacian_matrix}
\title{Graph Laplacian}
\usage{
laplacian_matrix(graph, normalized = FALSE, weights = NULL,
sparse = igraph_opt("sparsematrices"))
}
\arguments{
\item{graph}{The input graph.}
\item{normalized}{Whether to calculate the normalized Laplacian. See
definitions below.}
\item{weights}{An optional vector giving edge weights for weighted Laplacian
matrix. If this is \code{NULL} and the graph has an edge attribute called
\code{weight}, then it will be used automatically. Set this to \code{NA} if
you want the unweighted Laplacian on a graph that has a \code{weight} edge
attribute.}
\item{sparse}{Logical scalar, whether to return the result as a sparse
matrix. The \code{Matrix} package is required for sparse matrices.}
}
\value{
A numeric matrix.
}
\description{
The Laplacian of a graph.
}
\details{
The Laplacian Matrix of a graph is a symmetric matrix having the same number
of rows and columns as the number of vertices in the graph and element (i,j)
is d[i], the degree of vertex i if if i==j, -1 if i!=j and there is an edge
between vertices i and j and 0 otherwise.
A normalized version of the Laplacian Matrix is similar: element (i,j) is 1
if i==j, -1/sqrt(d[i] d[j]) if i!=j and there is an edge between vertices i
and j and 0 otherwise.
The weighted version of the Laplacian simply works with the weighted degree
instead of the plain degree. I.e. (i,j) is d[i], the weighted degree of
vertex i if if i==j, -w if i!=j and there is an edge between vertices i and
j with weight w, and 0 otherwise. The weighted degree of a vertex is the sum
of the weights of its adjacent edges.
}
\examples{
g <- make_ring(10)
laplacian_matrix(g)
laplacian_matrix(g, norm=TRUE)
laplacian_matrix(g, norm=TRUE, sparse=FALSE)
}
\author{
Gabor Csardi \email{csardi.gabor@gmail.com}
}
\keyword{graphs}
|