add methods for centrality and centralization, for igraph and network objects
v_degree
v_betweenness
v_closeness
v_stress
v_eccentricity

e_betweenness
e_* ???

g_eccentricity
g_closeness
g_density
g_degree
g_betweenness
g_diameter
g_reciprocity
g_transitivity
g_stress

Indien mogelijk, geef de optie om het plotten van de mediaan of de mean te onderdrukken.

snafun::stat_plot_gof_as_btergm

Per maksim:

"Would it also be possible to introduce some manual graph creation/node addition/edge addition functions to "SNAfun" by next year? During the first lab, we start with basics, paying quite a bit of attention to the manual creation of graphs (e.g., using the "graph.formula" function). "

add vertices = NULL argument!!!!!
add directed = F argument???

check if bipartite construction works easily or whether this should be a separate function

add:

• is_bipartite
  for both network and igraph objects

same as sna::gcor(), but for more than 2 graphs and consistent API for network and igraph

add functions to set, get (=show), and remove:

• vertex attributes
• edge attributes
• graph attributes

that works for both igraph and network objects.

The (unwritten and not-yet-well-developed) api for our package has the "make_" verb. Therefore, it would be preferable to use make_* here too.
Perhaps make_*_from_dfs would work, as I will probably create make_igraph_from_dfs and make_network_from_dfs as well, so that would be consistent in naming.

Add a function (here or as a separate script) to test that students have a proper installation of all packages for our course, with all required dependencies, required versions (incl. R and Rstudio), location of folders on the machine, and all works well (esp. check that the packages that embed C work well on the student's machine--ergm, btergm, igraph, others?).

snafun is new and contains many useful functions
update the cheatsheet so students can see how to do things in snafun in addition to what is already in the cheatsheet

Add:

• find_isolates()
• remove_isolates()
• contract_isolates()

currently, the output is sometimes nice and sometimes messy.

Currently plot_weighted_graph takes class matrix.

Implement plots also for weighted graph of class

• igraph
• network
• data.frame

methods for generating random graphs, either with fixed edge prob or fixed density

similar to

igraph::any_multiple()
multiples <- igraph::which_multiple() |> which()

add generic count_* methods, including:

• count_vertices()
• count_nodes()
• count_dyads() (=dyad census)
• count_triads() (=triad census)

all for network, igraph, matrix, data.frame

similar to

sna::efficiency()
igraph::global_efficiency()