| as_adj_list1 | Adjacency list |
| as_adj_weighted | weighted dense adjacency matrix |
| as_multi_adj | Convert a list of graphs to an adjacency matrices |
| biggest_component | helper function |
| bipartite_from_data_frame | two-mode network from a data.frame |
| clique_vertex_mat | Clique Vertex Matrix |
| core_periphery | Discrete core-periphery model |
| delete_isolates | helper function |
| dyad_census_attr | dyad census with node attributes |
| fast_cliques | Find Cliques, maximal or not, fast |
| graph_cartesian | Cartesian product of two graphs |
| graph_cor | Graph correlation |
| graph_cor.array | Graph correlation |
| graph_cor.default | Graph correlation |
| graph_cor.igraph | Graph correlation |
| graph_cor.matrix | Graph correlation |
| graph_direct | Direct product of two graphs |
| graph_from_multi_edgelist | Multiple networks from a single edgelist with a typed attribute |
| graph_kpartite | k partite graphs |
| graph_to_sage | convert igraph object to sage format |
| helpers | helper function |
| reciprocity_cor | Reciprocity correlation coefficient |
| sample_coreseq | Generate random graphs with a given coreness sequence |
| sample_lfr | LFR benchmark graphs |
| sample_pa_homophilic | Homophilic random graph using BA preferential attachment model |
| split_graph | split graph |
| str.igraph | Print graphs to terminal |
| structural_equivalence | Maximal Structural Equivalence |
| triad_census_attr | triad census with node attributes |