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, (x, y if layout applied)

edges

Data frame with from, to, weight columns

directed

Logical indicating if network is directed

weights

Full n×n weight matrix (for to_matrix round-trip)

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

# From adjacency matrix
mat <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- as_cograph(mat)

# Direct $ access to core data
net$nodes      # nodes data frame
net$edges      # edges data frame
net$directed   # TRUE/FALSE

# Getter functions (recommended for programmatic use)
get_nodes(net)   # nodes data frame
get_edges(net)   # edges data frame (from, to, weight)
get_labels(net)  # character vector of labels
n_nodes(net)     # 3
n_edges(net)     # 3
cograph::is_directed(net) # FALSE (symmetric matrix)

# Setter functions
net <- set_nodes(net, data.frame(id = 1:3, label = c("A", "B", "C")))
net <- set_edges(net, data.frame(from = c(1,2), to = c(2,3), weight = c(0.5, 0.8)))
net <- set_layout(net, data.frame(x = c(0, 1, 0.5), y = c(0, 0, 1)))

# Plot it
splot(net)

# From igraph (if installed)
if (requireNamespace("igraph", quietly = TRUE)) {
  g <- igraph::make_ring(10)
  net <- as_cograph(g)
  splot(net)
}
mat <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), nrow = 3)
net <- to_cograph(mat)

cograph documentation built on April 1, 2026, 1:07 a.m.