# centr_clo_tmax: Theoretical maximum for closeness centralization In igraph: Network Analysis and Visualization

## Description

See `centralize` for a summary of graph centralization.

## Usage

 `1` ```centr_clo_tmax(graph = NULL, nodes = 0, mode = c("out", "in", "all", "total")) ```

## Arguments

 `graph` The input graph. It can also be `NULL`, if `nodes` is given. `nodes` The number of vertices. This is ignored if the graph is given. `mode` This is the same as the `mode` argument of `closeness`.

## Value

Real scalar, the theoretical maximum (unnormalized) graph closeness centrality score for graphs with given order and other parameters.

Other centralization related: `centr_betw_tmax()`, `centr_betw()`, `centr_clo()`, `centr_degree_tmax()`, `centr_degree()`, `centr_eigen_tmax()`, `centr_eigen()`, `centralize()`

## Examples

 ```1 2 3 4 5``` ```# A BA graph is quite centralized g <- sample_pa(1000, m = 4) centr_clo(g, normalized = FALSE)\$centralization %>% `/`(centr_clo_tmax(g)) centr_clo(g, normalized = TRUE)\$centralization ```

### Example output

```Attaching package: ‘igraph’

The following objects are masked from ‘package:stats’:

decompose, spectrum

The following object is masked from ‘package:base’:

union

 6.72441e-05
Warning message:
In centr_clo(g, normalized = FALSE) :
At centrality.c:2784 :closeness centrality is not well-defined for disconnected graphs
 6.72441e-05
Warning message:
In centr_clo(g, normalized = TRUE) :
At centrality.c:2784 :closeness centrality is not well-defined for disconnected graphs
```

igraph documentation built on Oct. 15, 2021, 5:06 p.m.