An S4 class that contains all information on a single network. In this representation a network is composed of nodes which must be identified uniquely by and ID. Each node is described by variables stored in a data.frame. The node neighborhood matrix describes strength of links between the nodes of the network. The class is constructed by the sp_network_nodes() function.

# S4 method for sp_network_nodes
dat(object)

# S4 method for sp_network_nodes
dat(object) <- value

# S4 method for sp_network_nodes
id(object)

# S4 method for sp_network_nodes
id(object) <- value

# S4 method for sp_network_nodes
neighborhood(object)

# S4 method for sp_network_nodes
neighborhood(object) <- value

# S4 method for sp_network_nodes
nnodes(object)

Arguments

object

A sp_network_nodes-class

value

An object to replace the existing id/data/neighborhood

Slots

network_id

A character that serves as an identifier for the network

nnodes

A numeric that indicates the number of nodes in the network

node_data

A data.frame that contains all information describing the nodes

node_neighborhood

A matrix that describes the neighborhood relations of the nodes

See also

Examples

## access the data describing the nodes new_dat <- dat(germany_net) # access the id of the network germany_net2 <- germany_net id(germany_net2)
#> [1] "ge"
id(germany_net2) <- "Germany" # access the neighborhood matrix of the nodes neighborhood(germany_net)
#> 16 x 16 sparse Matrix of class "dgCMatrix" #> #> SH . 0.5000000 0.5000000 . . . . . #> HH 0.2 . 0.2000000 0.2000000 0.2000000 0.2000000 . . #> MV 0.2 0.2000000 . . 0.2000000 0.2000000 0.2000000 . #> NW . 0.2500000 . . 0.2500000 . . 0.2500000 #> HB . 0.1428571 0.1428571 0.1428571 . 0.1428571 . 0.1428571 #> BB . 0.1428571 0.1428571 . 0.1428571 . 0.1428571 . #> BE . . 0.2500000 . . 0.2500000 . . #> RP . . . 0.2000000 0.2000000 . . . #> NI . . . 0.1250000 0.1250000 0.1250000 . 0.1250000 #> ST . . . . 0.1428571 0.1428571 0.1428571 . #> SN . . . . . 0.2500000 0.2500000 . #> SL . . . . . . . 0.2500000 #> HE . . . . . . . 0.1428571 #> TH . . . . . . . . #> BW . . . . . . . . #> BY . . . . . . . . #> #> SH . . . . . . . #> HH . . . . . . . #> MV . . . . . . . #> NW 0.2500000 . . . . . . #> HB 0.1428571 0.1428571 . . . . . #> BB 0.1428571 0.1428571 0.1428571 . . . . #> BE . 0.2500000 0.2500000 . . . . #> RP 0.2000000 . . 0.2000000 0.2000000 . . #> NI . 0.1250000 . 0.1250000 0.1250000 0.1250000 . #> ST 0.1428571 . 0.1428571 . 0.1428571 0.1428571 . #> SN . 0.2500000 . . . 0.2500000 . #> SL 0.2500000 . . . 0.2500000 . 0.2500000 #> HE 0.1428571 0.1428571 . 0.1428571 . 0.1428571 0.1428571 #> TH 0.1666667 0.1666667 0.1666667 . 0.1666667 . 0.1666667 #> BW . . . 0.2500000 0.2500000 0.2500000 . #> BY . . . . 0.3333333 0.3333333 0.3333333 #> #> SH . #> HH . #> MV . #> NW . #> HB . #> BB . #> BE . #> RP . #> NI . #> ST . #> SN . #> SL . #> HE 0.1428571 #> TH 0.1666667 #> BW 0.2500000 #> BY .
# access the number of nodes inside the network nnodes(germany_net)
#> [1] 16