# netUtils

#### Network utility functions

netUtils is a collection of tools for network analysis that may not deserve a package on their own and/or are missing from other network packages.

## Installation

You can install the development version of netUtils with:

```
# install.packages("remotes")
remotes::install_github("schochastics/netUtils")
```

## Functions

*(The functions listed below are just a sample of the available methods)*

most functions only support igraph objects

**helper/convenience functions**

`biggest_component()`

extract the biggest connected component of a network.

`delete_isolates()`

delete vertices with degree zero.

`bipartite_from_data_frame()`

create a two mode network from a data frame.

`clique_vertex_mat()`

compute the clique vertex matrix

`graph_cartesian()`

computes the Cartesian product of two graphs

`graph_direct()`

computes the direct (or tensor) product of graphs

**methods**

`graph_kpartite()`

create a random k-partite network.

`triad_census_attr()`

calculate triad census with vertex attributes.

`structural_equivalence()`

finds structurally equivalent vertices.

`core_periphery()`

to fit a discrete core periphery model.

`sample_coreseq()`

creates a random graph with given coreness sequence.

`fast_clique()`

to calculate cliques with MACE (sometimes faster than igraph)

`sample_pa_homophilic()`

to create a preferential attachment graph with two groups of nodes