mark_nodes | R Documentation |
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(.data)
node_is_isolate(.data)
node_is_core(.data)
node_is_random(.data, size = 1)
node_is_max(node_measure, ranks = 1)
node_is_min(node_measure, ranks = 1)
.data |
An object of a
|
size |
The number of nodes to select (as TRUE). |
node_measure |
An object created by a |
ranks |
The number of ranks of max or min to return.
For example, |
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
Other marks:
is()
,
mark_ties
node_is_cutpoint(ison_brandes)
node_is_isolate(ison_brandes)
node_is_core(ison_brandes)
node_is_random(ison_brandes, 2)
node_is_max(node_degree(ison_brandes))
node_is_min(node_degree(ison_brandes))
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