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