morphers: Functions to generate alternate representations of graphs

In tidygraph: A Tidy API for Graph Manipulation

Functions to generate alternate representations of graphs

Description

These functions are meant to be passed into morph() to create a temporary alternate representation of the input graph. They are thus not meant to be called directly. See below for detail of each morpher.

Usage

to_linegraph(graph)

to_subgraph(graph, ..., subset_by = NULL)

to_subcomponent(graph, node)

to_split(graph, ..., split_by = NULL)

to_components(graph, type = "weak", min_order = 1)

to_largest_component(graph, type = "weak")

to_complement(graph, loops = FALSE)

to_local_neighborhood(graph, node, order = 1, mode = "all")

to_dominator_tree(graph, root, mode = "out")

to_minimum_spanning_tree(graph, weights = NULL)

to_random_spanning_tree(graph)

to_shortest_path(graph, from, to, mode = "out", weights = NULL)

to_bfs_tree(graph, root, mode = "out", unreachable = FALSE)

to_dfs_tree(graph, root, mode = "out", unreachable = FALSE)

to_simple(graph, remove_multiples = TRUE, remove_loops = TRUE)

to_contracted(graph, ..., simplify = TRUE)

to_unfolded_tree(graph, root, mode = "out")

to_directed(graph)

to_undirected(graph)

to_hierarchical_clusters(graph, method = "walktrap", weights = NULL, ...)

Arguments

graph	A tbl_graph
...	Arguments to pass on to filter(), group_by(), or the cluster algorithm (see igraph::cluster_walktrap(), igraph::cluster_leading_eigen(), and igraph::cluster_edge_betweenness())
subset_by, split_by	Whether to create subgraphs based on nodes or edges
node	The center of the neighborhood for to_local_neighborhood() and the node to that should be included in the component for to_subcomponent()
type	The type of component to split into. Either 'weak' or 'strong'
min_order	The minimum order (number of vertices) of the component. Components below this will not be created
loops	Should loops be included. Defaults to FALSE
order	The radius of the neighborhood
mode	How should edges be followed? 'out' only follows outbound edges, 'in' only follows inbound edges, and 'all' follows all edges. This parameter is ignored for undirected graphs.
root	The root of the tree
weights	Optional edge weights for the calculations
from, to	The start and end node of the path
unreachable	Should the search jump to a node in a new component when stuck.
remove_multiples	Should edges that run between the same nodes be reduced to one
remove_loops	Should edges that start and end at the same node be removed
simplify	Should edges in the contracted graph be simplified? Defaults to TRUE
method	The clustering method to use. Either 'walktrap', 'leading_eigen', or 'edge_betweenness'

Value

A list of tbl_graphs

Functions

• to_linegraph(): Convert a graph to its line graph. When unmorphing node data will be merged back into the original edge data. Edge data will be ignored.

• to_subgraph(): Convert a graph to a single subgraph. ... is evaluated in the same manner as filter. When unmorphing all data in the subgraph will get merged back.

• to_subcomponent(): Convert a graph to a single component containing the specified node

• to_split(): Convert a graph into a list of separate subgraphs. ... is evaluated in the same manner as group_by. When unmorphing all data in the subgraphs will get merged back, but in the case of split_by = 'edges' only the first instance of node data will be used (as the same node can be present in multiple subgraphs).

• to_components(): Split a graph into its separate components. When unmorphing all data in the subgraphs will get merged back.

• to_largest_component(): Create a new graph only consisting of it's largest component. If multiple largest components exists, the one with containing the node with the lowest index is chosen.

• to_complement(): Convert a graph into its complement. When unmorphing only node data will get merged back.

• to_local_neighborhood(): Convert a graph into the local neighborhood around a single node. When unmorphing all data will be merged back.

• to_dominator_tree(): Convert a graph into its dominator tree based on a specific root. When unmorphing only node data will get merged back.

• to_minimum_spanning_tree(): Convert a graph into its minimum spanning tree/forest. When unmorphing all data will get merged back.

• to_random_spanning_tree(): Convert a graph into a random spanning tree/forest. When unmorphing all data will get merged back

• to_shortest_path(): Limit a graph to the shortest path between two nodes. When unmorphing all data is merged back.

• to_bfs_tree(): Convert a graph into a breath-first search tree based on a specific root. When unmorphing only node data is merged back.

• to_dfs_tree(): Convert a graph into a depth-first search tree based on a specific root. When unmorphing only node data is merged back.

• to_simple(): Collapse parallel edges and remove loops in a graph. When unmorphing all data will get merged back

• to_contracted(): Combine multiple nodes into one. ... is evaluated in the same manner as group_by. When unmorphing all data will get merged back.

• to_unfolded_tree(): Unfold a graph to a tree or forest starting from multiple roots (or one), potentially duplicating nodes and edges.

• to_directed(): Make a graph directed in the direction given by from and to

• to_undirected(): Make a graph undirected

• to_hierarchical_clusters(): Convert a graph into a hierarchical clustering based on a grouping

Examples

# Compute only on a subgraph of every even node
create_notable('meredith') %>%
  morph(to_subgraph, seq_len(graph_order()) %% 2 == 0) %>%
  mutate(neighbour_count = centrality_degree()) %>%
  unmorph()

tidygraph documentation built on June 22, 2024, 11:32 a.m.