A tidy API for graph manipulation
tbl_graph()
when edge to
and from
where encoded as factorsresolution
argument to group_louvrain()
to mirror the igraph functionas_tbl_graph()
on an edge dataframe now only adds a name node attribute if
the edges are encoded as a character (#147)node_is_connected()
to test whether a node is connected to a set of
nodes (#165)play_erdos_renyi()
in favour of play_gnm()
and play_gnp()
(#152)slice_*()
functions from dplyr (#128)tidyr::replace_na()
and tidyr::drop_na()
(#114)edge_is_bridge()
for querying whether an edge is a bridge edge (#113)glimpse()
method for tbl_graph
and morphed_tbl_graph
objects
(#30)iterate_n()
and iterate_while()
to perform repeated modifications of
a graph for a specific number of times or until a condition no longer is met
(#43)focus()
/unfocus()
verbs to limit node and edge algorithms to a subset
while still keeping the full graph context (#18)graph_automorphisms()
gains a color
argument in line with capabilities in
igraphgraph_mean_dist()
now supports edge weights through a new weights
argumentto_largest_component()
morphergraph_is_eulerian()
and edge_rank_eulerian()
for eulerian path
calculationsto_random_spanning_tree()
morphermin_order
argument to to_components()
morpherrandom_walk_rank()
to perform random walks on the graphcentrality_harmonic()
+ deprecated centrality_closeness_harmonic()
.
The latter is an interface to netrankr while the former is a more efficient
and flexible igraph implementation.group_color()
as an interface to greedy_vertex_coloring()
in igraphgroup_leiden()
to interface with cluster_leiden()
in igraphgroup_fluid()
to interface with cluster_fluid_communities()
in igraphedge_is_feedback_arc()
to interface with feedback_arc_set()
in igraphgraph_efficiency()
and node_effeciency()
interfacing with
global_efficiency()
and local_efficiency()
in igraphgroup_edge_betweenness
, group_fast_greedy
, group_leading_eigen
and
group_walktrap
have a new argument n_groups
that controls the numbers of
groups computed. The argument expects an integer value and it is NULL
by
default.nodes
are used for matching
if the to
and from
columns in edges are character vectors during
construction (#89)bind_graph()
now accepts a list of graphs as its first argument (#88)graph_modularity()
for calculating modularity contingent on a node
grouping (#97)weight
edge attribute. weights = NULL
will always mean that no
edge weight is used (#106).map_local()
and siblings will now contain a
.central_node
node attribute that will identify the node from which the
local graph has been calculated (#107)