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Decompose a network object into base R components

Source: R/decompose_rs.R
decompose_statnet.Rd

decompose_statnet (also available as decompose_network) extracts the adjacency matrix and any vertex/edge attributes from a network object (from the statnet suite), returning them in a standardized list format.

Usage

decompose_statnet(ntwk, weight = NULL)

decompose_network(ntwk, weight = NULL)

Arguments

ntwk

A network object (class "network") to be decomposed.

weight

Character string specifying the edge attribute to use as weights in the adjacency matrix. If NULL (default), the unweighted adjacency matrix is returned with 1s for edges and 0s for non-edges.

Value

A list containing four elements:

  • adj_mat: The adjacency matrix extracted from the network object

    • For unipartite networks: Square matrix of dimension n×n

    • For bipartite networks: Full square matrix of dimension (n₁+n₂)×(n₁+n₂)

    • Values are edge weights if specified, otherwise 0/1

  • ndata: A data frame of vertex attributes, or NULL if none exist

    • Always includes an 'actor' column with vertex names

    • Additional columns for each vertex attribute (excluding system attributes)

  • ddata: A data frame of edge attributes, or NULL if none exist

    • Columns 'from' and 'to' specify edge endpoints using vertex names

    • Additional columns for each edge attribute

  • weight: The edge attribute name used for weights, if provided

Details

The function handles both unipartite and bipartite networks appropriately:

Network type detection:

  • Bipartite networks are identified using is.bipartite()

  • The bipartite partition size is retrieved from the 'bipartite' network attribute

Vertex naming:

The function checks for existing vertex names in the 'vertex.names' attribute. If names are just the default numeric sequence (1, 2, 3, ...), they are treated as missing. Default names are assigned when needed:

  • Unipartite networks: "a1", "a2", ..., "an"

  • Bipartite networks: "r1", "r2", ... for first partition; "c1", "c2", ... for second partition

Matrix extraction:

Unlike igraph's bipartite handling, the network package returns the full adjacency matrix even for bipartite networks. The function:

  • Extracts the full matrix using as.matrix.network.adjacency()

  • For bipartite networks, the matrix has dimension (n₁+n₂)×(n₁+n₂) with the first n₁ rows/columns for the first partition

Attribute handling:

System attributes ('vertex.names' and 'na') are excluded from the vertex attribute data frame. All user-defined vertex and edge attributes are preserved.

Note

For longitudinal networks with changing actor composition, explicitly set vertex names before decomposition to ensure consistent actor identification across time periods.

The adjacency matrix format differs between this function and decompose_igraph for bipartite networks: this function returns the full square matrix while decompose_igraph returns only the rectangular bipartite portion.

Edge directions are preserved in the adjacency matrix according to the network's directed/undirected property.

Author

Cassy Dorff, Shahryar Minhas