to_py_graph

character vector specifying the attribute name where level
information is stored in <code>net</code>.

lvl_attr

should nodes be relabelled with statnet <code>vertex.names</code> or
igraph nodal attribute <code>name</code>

relabel

whether the graph shall be treated as a directed graph. Per
default (<code>NULL</code>), this is determined automatically using the structure
of the provided network object

directed

The function <code>motifr::is.directed</code> is used to determine whether the
provided network is directed (if <code>directed = FALSE</code>).

Tools for motif analysis in multi-level networks.
Multi-level networks combine multiple networks in one, e.g.
social-ecological networks. Motifs are small configurations of nodes
and edges (subgraphs) occurring in networks. 'motifr' can visualize
multi-level networks, count multi-level network motifs and compare
motif occurrences to baseline models. It also identifies contributions
of existing or potential edges to motifs to find critical or missing
edges. The package is in many parts an R wrapper for the excellent
'SESMotifAnalyser' 'Python' package written by Tim Seppelt.

to_py_graph: Translate multi-level statnet or igraph network object to Python networkx object

Description

Usage

Arguments

Value

Details

Examples