tidygraph (version 1.1.2)

pair_measures: Calculate node pair properties

Description

This set of functions can be used for calculations that involve node pairs. If the calculateable measure is not symmetric the function will come in two flavours, differentiated with _to/_from suffix. The *_to() functions will take the provided node indexes as the target node (recycling if necessary). For the *_from() functions the provided nodes are taken as the source. As for the other wrappers provided, they are intended for use inside the tidygraph framework and it is thus not necessary to supply the graph being computed on as the context is known.

Usage

node_adhesion_to(nodes)

node_adhesion_from(nodes)

node_cohesion_to(nodes)

node_cohesion_from(nodes)

node_distance_to(nodes, mode = "out", weights = NA, algorithm = "automatic")

node_distance_from(nodes, mode = "out", weights = NA, algorithm = "automatic")

node_cocitation_with(nodes)

node_bibcoupling_with(nodes)

node_similarity_with(nodes, mode = "out", loops = FALSE, method = "jaccard")

node_max_flow_to(nodes, capacity = NULL)

node_max_flow_from(nodes, capacity = NULL)

Arguments

nodes

The other part of the node pair (the first part is the node defined by the row). Recycled if necessary.

mode

How should edges be followed? If 'all' all edges are considered, if 'in' only inbound edges are considered, and if 'out' only outbound edges are considered

weights

The weights to use for calculation

algorithm

The distance algorithms to use. By default it will try to select the fastest suitable algorithm. Possible values are "automatic", "unweighted", "dijkstra", "bellman-ford", and "johnson"

loops

Should loop edges be considered

method

The similarity measure to calculate. Possible values are: "jaccard", "dice", and "invlogweighted"

capacity

The edge capacity to use

Value

A numeric vector of the same length as the number of nodes in the graph

Functions

Examples

Run this code
# NOT RUN {
# Calculate the distance to the center node
create_notable('meredith') %>%
  mutate(dist_to_center = node_distance_to(node_is_center()))
# }

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