Network Wrangling Verbs

cograph provides verbs for reshaping a network. Each verb accepts any supported input (matrix, edge list, igraph, statnet network, tna model, cograph_network) and takes its options as named arguments. The result is a cograph_network, or the input format when keep_format = TRUE. as.data.frame() returns the edge or node table of a result.

Value

Each verb returns a cograph_network, except split_components(), which returns a list of them. With keep_format = TRUE a matrix, igraph, statnet network or tna input comes back in that format. An edge-list data frame comes back as a cograph_network with a warning.

Selecting

filter_nodes(), select_nodes(): Keep nodes by expression, name, index, top-N, neighborhood or component.
filter_edges(), select_edges(): Keep edges by expression, endpoints, bridges, mutuality or top-N.
select_neighbors(), select_component(), select_top(), select_k_core(): Named shorthands for the common selections.
split_components(): One network per connected component.

Weights

threshold_edges(): Keep edges by weight, count, proportion or density.
binarize(): Replace weights with 0/1.
symmetrize(): Combine opposite arcs into one edge.
normalize_weights(): Rescale by row, column, maximum, total, or to [0, 1].
invert_weights(): Turn similarities into distances.

Structure

to_undirected(), to_directed(), reverse_edges(): Change directedness.
remove_isolates(): Drop nodes with no edges.
contract_nodes(): Collapse groups of nodes into one.
spanning_tree(), complement_network(): Derived graphs.
reorder_nodes(), rename_nodes(): Change node order or labels without changing the network.
simplify(): Merge duplicate edges and drop loops. It returns the input format.

Editing

add_nodes(), remove_nodes(), add_edges(), remove_edges(): Add and remove.
mutate_nodes(), mutate_edges(): Compute and store attributes.
bind_networks(): Union, intersection or difference of two networks.

Conversion and access

as_cograph(), to_matrix(), to_igraph(), to_network(), to_df(), and as.data.frame() on a cograph_network (see as.data.frame.cograph_network).

Semantics

Filtering edges does not remove nodes, as in igraph::delete_edges() and tidygraph. Nodes left without edges raise a cograph_isolates_created warning. They are dropped by remove_isolates() or by keep_isolates = FALSE in the verbs that have that argument.
The weight matrix of an undirected result is symmetric, so the result is still detected as undirected downstream.
Node groups, estimation data, layout coordinates and the original source type are carried through the verbs.
Unknown node names, out-of-range or fractional indices, unknown measure names and a malformed between raise a cograph_bad_selection error. The name argument of select_nodes() is an exception. Unknown names in it are skipped, and a warning is given when no node matches.

ego_networks(), shortest_paths(), disparity_filter(), detect_communities(), summarize_clusters(), aggregate_layers().

Examples

as.data.frame(threshold_edges(regulation_net, minimum = 0.2))
#>          from       to weight
#> 1       Adapt  Explore   0.28
#> 2     Discuss  Explore   0.30
#> 3       Share     Plan   0.21
#> 4    Evaluate  Monitor   0.33
#> 5       Share  Monitor   0.49
#> 6    Evaluate    Adapt   0.43
#> 7       Share    Adapt   0.39
#> 8     Explore  Reflect   0.35
#> 9     Discuss  Reflect   0.35
#> 10 Synthesize  Reflect   0.42
#> 11       Plan  Discuss   0.40
#> 12      Adapt  Discuss   0.34
#> 13       Plan Evaluate   0.49
#> 14     Create Evaluate   0.39
#> 15       Plan   Create   0.20
#> 16    Monitor   Create   0.37
#> 17    Explore    Share   0.27
#> 18       Plan    Share   0.36
#> 19     Create    Share   0.23