These functions return logical vectors the length of the nodes in a network identifying which hold certain properties.
node_is_cutpoint()
and node_is_isolate()
are useful for identifying
nodes that are in particular positions in the network.
More can be added here.
node_is_max()
and node_is_min()
are more generally useful
for converting the results from some node measure into a mark-class object.
They can be particularly useful for highlighting which node or nodes
are key because they minimise or, more often, maximise some measure.
node_is_cutpoint(object)
node_is_isolate(object)
node_is_core(object)
node_is_random(object, size = 1)
node_is_max(node_measure, ranks = 1)
node_is_min(node_measure, ranks = 1)
An object of a migraph-consistent class:
matrix (adjacency or incidence) from {base}
R
edgelist, a data frame from {base}
R or tibble from {tibble}
igraph, from the {igraph}
package
network, from the {network}
package
tbl_graph, from the {tidygraph}
package
The number of nodes to select (as TRUE).
An object created by a node_
measure.
The number of ranks of max or min to return.
For example, ranks = 3
will return TRUE for nodes with
scores equal to any of the top (or, for node_is_min()
, bottom)
three scores.
By default, ranks = 1
.
node_is_cutpoint()
: Returns logical of which nodes cut
or act as articulation points in a network,
increasing the number of connected components in a graph when removed.
node_is_isolate()
: Returns logical of which nodes are isolates,
with neither incoming nor outgoing ties.
node_is_core()
: Returns logical of which nodes are members
of the core of the network.
node_is_random()
: Returns a logical vector
indicating a random selection of nodes as TRUE.
node_is_max()
: Returns logical of which nodes
hold the maximum of some measure
node_is_min()
: Returns logical of which nodes
hold the minimum of some measure
node_is_cutpoint(ison_brandes)
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
#> 1 FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE
node_is_isolate(ison_brandes)
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
#> 1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
node_is_core(ison_brandes)
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
#> 1 FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE
node_is_random(ison_brandes, 2)
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
#> 1 FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE
node_is_max(node_degree(ison_brandes))
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
#> 1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE
node_is_min(node_degree(ison_brandes))
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
#> 1 TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE