NEWS.md
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)network
objects. Old conversion could mess up edge attributes.tibble
and dplyr
tibble
-like dimming of non-data text in printingphylo
to_subcomponent
morpher to work with a single component containing a specified nodenode_is_adjacent
to query which nodes are directly connected to a set of nodesfortify
method for tbl_graph
object for plotting as regular data with ggplot2
tbl_graph
from an adjacency list containing NULL
or NA
elements.convert
verb to perform both morph
and crystallise
in one go, returning a single tbl_graph
morph
the original data will be stored in .orig_data
instead of .data
to avoid conflicts with .data
argument in many tidyverse verbs (BREAKING)as_tbl_graph.data.frame
now recognises set tables (each column gives eachs rows membership to that set)with_graph
to allow computation of algorithms outside of verbsgraph_is_*
set of querying functions has been added that all returns logical scalars.%N>%
and %E>%
for activating nodes and edges respectively as part of the piping.mutate
now lets you reference created columns in graph algorithms so it behaves in line with expected mutate
behaviour. This has led to a slight performance decrease (millisecond scale). The old behaviour can be accessed using mutate_as_tbl
where the graph will only get updated in the end.bind_graphs
now work with a single tbl_graph
.register_graph_context
to allow the use of tidygraph algorithms in external functions.to_unfolded_tree
, to_directed
, and to_undirected
morphersnode_rank_*
family of algorithms for seriation of nodesto_hierarchical_clusters
morpher to work with hierarchical representations of community detection algorithms.group_*
algorithms now ensure that the groups are enumerated in descending order based on size, i.e. members of the largest group/community will always have 1
, etc.netrankr
resulting in 19 new centrality scores and a manual mode for composing new centrality scoresedge_is_[from|to|between|incident]()
to help find edges related to certain nodes