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.

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

#> # A tbl_graph: 12 nodes and 24 edges
#> #
#> # An undirected simple graph with 1 component
#> #
#> # Node Data: 12 x 1 (active)
#> neighborhood
#> <list>
#> 1 <int [4]>
#> 2 <int [4]>
#> 3 <int [4]>
#> 4 <int [4]>
#> 5 <int [4]>
#> 6 <int [4]>
#> # … with 6 more rows
#> #
#> # Edge Data: 24 x 2
#> from to
#> <int> <int>
#> 1 6 7
#> 2 7 8
#> 3 8 9
#> # … with 21 more rows

#> # A tibble: 12 x 2
#> n_neighbors degree
#> <dbl> <dbl>
#> 1 4 4
#> 2 4 4
#> 3 4 4
#> 4 4 4
#> 5 4 4
#> 6 4 4
#> 7 4 4
#> 8 4 4
#> 9 4 4
#> 10 4 4
#> 11 4 4
#> 12 4 4