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

# netUtils

Network utility functions

8/2/19

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:

## Functions

most functions only support igraph objects

**helper/convenience functions**

`biggest_component()`

extracts the biggest connected component of a network.

`delete_isolates()`

deletes vertices with degree zero.

`bipartite_from_data_frame()`

creates a two mode network from a data frame.

`graph_from_multi_edgelist()`

creates multiple graphs from a typed edgelist.

`clique_vertex_mat()`

computes the clique vertex matrix.

`graph_cartesian()`

computes the Cartesian product of two graphs.

`graph_direct()`

computes the direct (or tensor) product of graphs.

`str()`

extends str to work with igraph objects.

**methods**

`triad_census_attr()`

calculates triad census with vertex attributes.

`core_periphery()`

fits a discrete core periphery model.

`graph_kpartite()`

creates a random k-partite network.

`sample_coreseq()`

creates a random graph with given coreness sequence.

`sample_pa_homophilic()`

creates a preferential attachment graph with two groups of nodes.

`structural_equivalence()`

finds structurally equivalent vertices.

`fast_clique()`

computes cliques with MACE (faster than igraph for dense graphs).

**methods to use with caution**

*(this functions should only be used if you know what you are doing)*

`as_adj_list1()`

extracts the adjacency list faster, but less stable, from igraph objects.

`as_adj_weighted()`

extracts the dense weighted adjacency matrix fast.