# isolated: Find and remove isolated vertices In srdyal/diffusiontest: Analysis of Diffusion and Contagion Processes on Networks

## Description

Find and remove unconnected vertices from the graph.

## Usage

 ```1 2 3 4 5``` ```isolated(graph, undirected = getOption("diffnet.undirected", FALSE), self = getOption("diffnet.self", FALSE)) drop_isolated(graph, undirected = getOption("diffnet.undirected", FALSE), self = getOption("diffnet.self", FALSE)) ```

## Arguments

 `graph` Any class of accepted graph format (see `netdiffuseR-graphs`). `undirected` Logical scalar. When `TRUE` only the lower triangle of the adjacency matrix will considered (faster). `self` Logical scalar. When `TRUE` autolinks (loops, self edges) are allowed (see details).

## Value

When `graph` is an adjacency matrix:

 `isolated` an matrix of size n*1 with 1's where a node is isolated `drop_isolated` a modified graph excluding isolated vertices.

Otherwise, when `graph` is a list

 `isolated` an matrix of size n*T with 1's where a node is isolated `drop_isolated` a modified graph excluding isolated vertices.

## Author(s)

George G. Vega Yon

Other data management functions: `diffnet-class`, `edgelist_to_adjmat`, `egonet_attrs`, `survey_to_diffnet`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27``` ```# Generating random graph set.seed(123) adjmat <- rgraph_er() # Making nodes 1 and 4 isolated adjmat[c(1,4),] <- 0 adjmat[,c(1,4)] <- 0 adjmat # Finding isolated nodes iso <- isolated(adjmat) iso # Removing isolated nodes drop_isolated(adjmat) # Now with a dynamic graph graph <- rgraph_er(n=10, t=3) # Making 1 and 5 isolated graph <- lapply(graph, "[<-", i=c(1,5), j=1:10, value=0) graph <- lapply(graph, "[<-", i=1:10, j=c(1,5), value=0) graph isolated(graph) drop_isolated(graph) ```