igraph-vs-attributes {igraph}

Query or set attributes of the vertices in a vertex sequence

Description

The $ operator is a syntactic sugar to query and set the attributes of the vertices in a vertex sequence.

Usage

## S3 replacement method for class 'igraph.vs'
x[[i]] <- value

## S3 replacement method for class 'igraph.vs'
x[i] <- value

## S3 method for class 'igraph.vs'
x$name

## S3 replacement method for class 'igraph.vs'
x$name <- value

V(x) <- value

Arguments

x

A vertex sequence. For ⁠V<-⁠ it is a graph.

i

Index.

value

New value of the attribute, for the vertices in the vertex sequence.

name

Name of the vertex attribute to query or set.

Details

The query form of $ is a shortcut for vertex_attr(), e.g. V(g)[idx]$attr is equivalent to vertex_attr(g, attr, V(g)[idx]).

The assignment form of $ is a shortcut for set_vertex_attr(), e.g. V(g)[idx]$attr <- value is equivalent to g <- set_vertex_attr(g, attr, V(g)[idx], value).

Value

A vector or list, containing the values of attribute name for the vertices in the vertex sequence. For numeric, character or logical attributes, it is a vector of the appropriate type, otherwise it is a list.

See Also

Other vertex and edge sequences: E(), V(), as_ids(), igraph-es-attributes, igraph-es-indexing, igraph-es-indexing2, igraph-vs-indexing, igraph-vs-indexing2, print.igraph.es(), print.igraph.vs()

Vertex, edge and graph attributes delete_edge_attr(), delete_graph_attr(), delete_vertex_attr(), edge_attr(), edge_attr<-(), edge_attr_names(), graph_attr(), graph_attr<-(), graph_attr_names(), igraph-attribute-combination, igraph-dollar, set_edge_attr(), set_graph_attr(), set_vertex_attr(), vertex_attr(), vertex_attr<-(), vertex_attr_names()

Examples

g <- make_(
  ring(10),
  with_vertex_(
    name = LETTERS[1:10],
    color = sample(1:2, 10, replace = TRUE)
  )
)
V(g)$name
V(g)$color
V(g)$frame.color <- V(g)$color

# color vertices of the largest component
largest_comp <- function(graph) {
  cl <- components(graph)
  V(graph)[which.max(cl$csize) == cl$membership]
}
g <- sample_(
  gnp(100, 2 / 100),
  with_vertex_(size = 3, label = ""),
  with_graph_(layout = layout_with_fr)
)
giant_v <- largest_comp(g)
V(g)$color <- "blue"
V(g)[giant_v]$color <- "orange"
plot(g)