## File: morph.Rd

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r-cran-tidygraph 1.2.0-1
 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586878889 % Generated by roxygen2: do not edit by hand % Please edit documentation in R/morph.R \name{morph} \alias{morph} \alias{unmorph} \alias{crystallise} \alias{crystallize} \alias{convert} \title{Create a temporary alternative representation of the graph to compute on} \usage{ morph(.data, .f, ...) unmorph(.data) crystallise(.data) crystallize(.data) convert(.data, .f, ..., .select = 1, .clean = FALSE) } \arguments{ \item{.data}{A \code{tbl_graph} or a \code{morphed_tbl_graph}} \item{.f}{A morphing function. See \link{morphers} for a list of provided one.} \item{...}{Arguments passed on to the morpher} \item{.select}{The graph to return during \code{convert()}. Either an index or the name as created during \code{crystallise()}.} \item{.clean}{Should references to the node and edge indexes in the original graph be removed when using \code{convert}} } \value{ A \code{morphed_tbl_graph} } \description{ The \code{morph}/\code{unmorph} verbs are used to create temporary representations of the graph, such as e.g. its search tree or a subgraph. A morphed graph will accept any of the standard \code{dplyr} verbs, and changed to the data is automatically propagated to the original graph when unmorphing. Tidygraph comes with a range of \link{morphers}, but is it also possible to supply your own. See Details for the requirement for custom morphers. The \code{crystallise} verb is used to extract the temporary graph representation into a tibble containing one separate graph per row and a \code{name} and \code{graph} column holding the name of each graph and the graph itself respectively. \code{convert()} is a shorthand for performing both \code{morph} and \code{crystallise} along with extracting a single \code{tbl_graph} (defaults to the first). For morphs were you know they only create a single graph, and you want to keep it, this is an easy way. } \details{ It is only possible to change and add to node and edge data from a morphed state. Any filtering/removal of nodes and edges will not result in removal from the main graph. However, nodes and edges not present in the morphed state will be unaffected in the main graph when unmorphing (if new columns were added during the morhped state they will be filled with \code{NA}). Morphing an already morhped graph will unmorph prior to applying the new morph. During a morphed state, the mapping back to the original graph is stored in \code{.tidygraph_node_index} and \code{.tidygraph_edge_index} columns. These are accesible but protected, meaning that any changes to them with e.g. mutate will be ignored. Furthermore, if the morph results in the merging of nodes and/or edges the original data is stored in a \code{.data} column. This is protected as well. When supplying your own morphers the morphing function should accept a \code{tbl_graph} as its first input. The provided graph will already have nodes and edges mapped with a \code{.tidygraph_node_index} and \code{.tidygraph_edge_index} column. The return value must be a \code{tbl_graph} or a list of \code{tbl_graph}s and these must contain either a \code{.tidygraph_node_index} column or a \code{.tidygraph_edge_index} column (or both). Note that it is possible for the morph to have the edges mapped back to the original nodes and vice versa (e.g. as with \link{to_linegraph}). In that case the edge data in the morphed graph(s) will contain a \code{.tidygraph_node_index} column and or the node data a \code{.tidygraph_edge_index} column. If the morphing results in the collapse of multiple columns or edges the index columns should be converted to list columns mapping the new node/edge back to all the nodes/edges it represents. Furthermore the original node/edge data should be collapsed to a list of tibbles, with the row order matching the order in the index column element. } \examples{ create_notable('meredith') \%>\% mutate(group = group_infomap()) \%>\% morph(to_contracted, group) \%>\% mutate(group_centrality = centrality_pagerank()) \%>\% unmorph() }