# local_graph

##### Measures based on the neighborhood of each node

These functions wraps a set of functions that all measures quantities of the local neighborhood of each node. They all return a vector or list matching the node position.

##### Usage

`local_size(order = 1, mode = "all", mindist = 0)`local_members(order = 1, mode = "all", mindist = 0)

local_triangles()

local_ave_degree(weights = NULL)

local_transitivity(weights = NULL)

##### Arguments

- order
Integer giving the order of the neighborhood.

- mode
Character constant, it specifies how to use the direction of the edges if a directed graph is analyzed. For ‘out’ only the outgoing edges are followed, so all vertices reachable from the source vertex in at most

`order`

steps are counted. For ‘"in"’ all vertices from which the source vertex is reachable in at most`order`

steps are counted. ‘"all"’ ignores the direction of the edges. This argument is ignored for undirected graphs.- mindist
The minimum distance to include the vertex in the result.

- weights
Weight vector. If the graph has a

`weight`

edge attribute, then this is used by default. If this argument is given, then vertex strength (see`strength`

) is used instead of vertex degree. But note that`knnk`

is still given in the function of the normal vertex degree. Weights are are used to calculate a weighted degree (also called`strength`

) instead of the degree.

##### Value

A numeric vector or a list (for `local_members`

) with elements
corresponding to the nodes in the graph.

##### Functions

`local_size`

: The size of the neighborhood in a given distance from the node. (Note that the node itself is included unless`mindist > 0`

). Wraps`igraph::ego_size()`

.`local_members`

: The members of the neighborhood of each node in a given distance. Wraps`igraph::ego()`

.`local_triangles`

: The number of triangles each node participate in. Wraps`igraph::count_triangles()`

.`local_ave_degree`

: Calculates the average degree based on the neighborhood of each node. Wraps`igraph::knn()`

.`local_transitivity`

: Calculate the transitivity of each node, that is, the propensity for the nodes neighbors to be connected. Wraps`igraph::transitivity()`

##### Examples

```
# NOT RUN {
# Get all neighbors of each graph
create_notable('chvatal') %>%
activate(nodes) %>%
mutate(neighborhood = local_members(mindist = 1))
# These are equivalent
create_notable('chvatal') %>%
activate(nodes) %>%
mutate(n_neighbors = local_size(mindist = 1),
degree = centrality_degree()) %>%
as_tibble()
# }
```

*Documentation reproduced from package tidygraph, version 1.1.2, License: MIT + file LICENSE*