as_cograph: Convert to Cograph Network

In cograph: Analysis and Visualization of Complex Networks

Convert to Cograph Network

Description

Creates a lightweight cograph_network object from various network inputs. The resulting object is a named list with all data accessible via $.

Usage

as_cograph(x, directed = NULL, simplify = FALSE, ...)

to_cograph(x, directed = NULL, ...)

Arguments

x	Network input. Can be: A square numeric matrix (adjacency/weight matrix) A data frame with edge list (from, to, optional weight columns) An igraph object A statnet network object A qgraph object A tna object An existing cograph_network object (returned as-is)
directed	Logical. Force directed interpretation. NULL for auto-detect.
simplify	Logical or character. If FALSE (default), every transition from tna sequence data is a separate edge. If TRUE or a string ("sum", "mean", "max", "min"), duplicate edges are aggregated.
...	Additional arguments (currently unused).

Details

The cograph_network format is designed to be:

• Lean: Only essential data stored, computed values derived on demand

• Modern: Uses named list elements instead of attributes for clean $ access

• Compatible: Works seamlessly with splot() and other cograph functions

Use getter functions for programmatic access: get_nodes, get_edges, get_labels, n_nodes, n_edges

Use setter functions to modify: set_nodes, set_edges, set_layout

Value

A cograph_network object: a named list with components:

nodes

Data frame with id, label, and optional layout or metadata columns

edges

Data frame with from, to, weight columns

directed

Logical indicating if network is directed

weights

Full n×n weight matrix when available for matrix/TNA round-trips, or NULL

data

Original estimation data (sequence matrix, edge list, etc.), or NULL

meta

Consolidated metadata list with sub-fields: source (input type string), layout (layout info list or NULL), tna (TNA metadata or NULL)

node_groups

Optional node groupings data frame

A cograph_network object. See as_cograph.

See Also

get_nodes to extract the nodes data frame, get_edges to extract edges as a data frame, n_nodes and n_edges for counts, is_directed to check directedness, splot for plotting

Examples

mat <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- as_cograph(mat)
get_nodes(net)
get_edges(net)
splot(net)
mat <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- to_cograph(mat)

cograph documentation built on May 31, 2026, 5:06 p.m.