R/tbl_graph.R

Defines functions tbl_vars.tbl_graph set_edge_attributes set_node_attributes set_graph_data.grouped_tbl_graph set_graph_data.tbl_graph set_graph_data as_tbl_graph.tbl_graph is_forest is_tree describe_graph print.morphed_tbl_graph cat_subtle print.tbl_graph is.tbl_graph as_tbl_graph.default as_tbl_graph tbl_graph

Documented in as_tbl_graph as_tbl_graph.default is.tbl_graph tbl_graph

#' A data structure for tidy graph manipulation
#'
#' The `tbl_graph` class is a thin wrapper around an `igraph` object that
#' provides methods for manipulating the graph using the tidy API. As it is just
#' a subclass of `igraph` every igraph method will work as expected. A
#' `grouped_tbl_graph` is the equivalent of a `grouped_df` where either the
#' nodes or the edges has been grouped. The `grouped_tbl_graph` is not
#' constructed directly but by using the [group_by()] verb. After creation of a
#' `tbl_graph` the nodes are activated by default. The context can be changed
#' using the [activate()] verb and affects all subsequent operations. Changing
#' context automatically drops any grouping. The current active context can
#' always be extracted with [as_tibble()], which drops the graph structure and
#' just returns a `tbl_df` or a `grouped_df` depending on the state of the
#' `tbl_graph`. The returned context can be overriden by using the `active`
#' argument in [as_tibble()].
#'
#' @details
#' Constructors are provided for most data structures that resembles networks.
#' If a class provides an [igraph::as.igraph()] method it is automatically
#' supported.
#'
#' @param nodes A `data.frame` containing information about the nodes in the
#' graph. If `edges$to` and/or `edges$from` are characters then they will be
#' matched to the column named according to `node_key` in nodes, if it exists.
#' If not, they will be matched to the first column.
#'
#' @param edges A `data.frame` containing information about the edges in the
#' graph. The terminal nodes of each edge must either be encoded in a `to` and
#' `from` column, or in the two first columns, as integers. These integers refer to
#' `nodes` index.
#'
#' @param x An object convertible to a `tbl_graph`
#'
#' @param directed Should the constructed graph be directed (defaults to `TRUE`)
#'
#' @param node_key The name of the column in `nodes` that character represented
#' `to` and `from` columns should be matched against. If `NA` the first column
#' is always chosen. This setting has no effect if `to` and `from` are given as
#' integers.
#'
#' @param mode In case `directed = TRUE` should the edge direction be away from
#' node or towards. Possible values are `"out"` (default) or `"in"`.
#'
#' @param ... Arguments passed on to the conversion function
#'
#' @return A `tbl_graph` object
#'
#' @examples
#' rstat_nodes <- data.frame(name = c("Hadley", "David", "Romain", "Julia"))
#' rstat_edges <- data.frame(from = c(1, 1, 1, 2, 3, 3, 4, 4, 4),
#'                             to = c(2, 3, 4, 1, 1, 2, 1, 2, 3))
#' tbl_graph(nodes = rstat_nodes, edges = rstat_edges)
#' @export
#'
tbl_graph <- function(nodes = NULL, edges = NULL, directed = TRUE, node_key = 'name') {
  as_tbl_graph(list(nodes = nodes, edges = edges), directed = directed, node_key = node_key)
}
#' @rdname tbl_graph
#' @export
as_tbl_graph <- function(x, ...) {
  UseMethod('as_tbl_graph')
}
#' @describeIn tbl_graph Default method. tries to call [igraph::as.igraph()] on the input.
#' @export
#' @importFrom igraph as.igraph
as_tbl_graph.default <- function(x, ...) {
  rlang::try_fetch(
    as_tbl_graph(as.igraph(x)),
    error = function(cnd) cli::cli_abort('No support for {.cls {class(x)}} objects', parent = cnd)
  )
}
#' @rdname tbl_graph
#' @export
is.tbl_graph <- function(x) {
  inherits(x, 'tbl_graph')
}
#' @importFrom tibble trunc_mat
#' @importFrom tools toTitleCase
#' @importFrom rlang as_quosure sym
#' @importFrom pillar style_subtle
#' @export
print.tbl_graph <- function(x, ...) {
  arg_list <- list(...)
  arg_list[['useS4']] <- NULL
  graph_desc <- describe_graph(x)
  not_active <- if (active(x) == 'nodes') 'edges' else 'nodes'
  top <- do.call(trunc_mat, modifyList(arg_list, list(x = as_tibble(x), n = 6)))
  top$summary[1] <- paste0(top$summary[1], ' (active)')
  names(top$summary)[1] <- toTitleCase(paste0(substr(active(x), 1, 4), ' data'))
  bottom <- do.call(trunc_mat, modifyList(arg_list, list(x = as_tibble(x, active = not_active), n = 3)))
  names(bottom$summary)[1] <- toTitleCase(paste0(substr(not_active, 1, 4), ' data'))
  cat_subtle('# A tbl_graph: ', gorder(x), ' nodes and ', gsize(x), ' edges\n', sep = '')
  cat_subtle('#\n')
  cat_subtle('# ', graph_desc, '\n', sep = '')
  cat_subtle('#\n')
  print(top)
  cat_subtle('#\n')
  print(bottom)
  invisible(x)
}

cat_subtle <- function(...) cat(pillar::style_subtle(paste0(...)))

#' @export
print.morphed_tbl_graph <- function(x, ...) {
  graph <- attr(x, '.orig_graph')
  cat('# A tbl_graph temporarily morphed to a ', gsub('_', ' ', sub('to_', '', attr(x, '.morpher'))), ' representation\n', sep = '')
  cat('# \n')
  cat('# Original graph is ', tolower(describe_graph(graph)), '\n', sep = '')
  cat('# consisting of ', gorder(graph), ' nodes and ', gsize(graph), ' edges\n', sep = '')
}
#' @importFrom igraph is_simple is_directed is_bipartite is_connected is_dag gorder
describe_graph <- function(x) {
  if (gorder(x) == 0) return('An empty graph')
  prop <- list(simple = is_simple(x), directed = is_directed(x),
                  bipartite = is_bipartite(x), connected = is_connected(x),
                  tree = is_tree(x), forest = is_forest(x), DAG = is_dag(x))
  desc <- c()
  if (prop$tree || prop$forest) {
    desc[1] <- if (prop$directed) 'A rooted' else 'An unrooted'
    desc[2] <- if (prop$tree) 'tree' else paste0('forest with ', count_components(x), ' trees')
  } else {
    desc[1] <- if (prop$DAG) 'A directed acyclic' else if (prop$bipartite) 'A bipartite' else if (prop$directed) 'A directed' else 'An undirected'
    desc[2] <- if (prop$simple) 'simple graph' else 'multigraph'
    n_comp <- count_components(x)
    desc[3] <- paste0('with ' , n_comp, ' component', if (n_comp > 1) 's' else '')
  }
  paste(desc, collapse = ' ')
}
#' @importFrom igraph is_connected is_simple gorder gsize is_directed
is_tree <- function(x) {
  is_connected(x) && is_simple(x) && (gorder(x) - gsize(x) == 1)
}
#' @importFrom igraph is_connected is_simple gorder gsize count_components is_directed
is_forest <- function(x) {
  !is_connected(x) && is_simple(x) && (gorder(x) - gsize(x) - count_components(x) == 0)
}
#' @export
as_tbl_graph.tbl_graph <- function(x, ...) {
  x
}
set_graph_data <- function(x, value, active) {
  UseMethod('set_graph_data')
}
set_graph_data.tbl_graph <- function(x, value, active = NULL) {
  if (is.null(active)) active <- active(x)
  switch(
    active,
    nodes = set_node_attributes(x, value),
    edges = set_edge_attributes(x, value),
    cli::cli_abort('Unknown active element: {.val {active}}. Only nodes and edges supported')
  )
}
set_graph_data.grouped_tbl_graph <- function(x, value, active = NULL) {
  x <- NextMethod()
  apply_groups(x, attributes(value))
}
#' @importFrom igraph vertex_attr<-
set_node_attributes <- function(x, value) {
  vertex_attr(x) <- as.list(value)
  x
}
#' @importFrom igraph edge_attr<-
set_edge_attributes <- function(x, value) {
  value <- value[, !names(value) %in% c('from', 'to')]
  edge_attr(x) <- as.list(value)
  x
}
#' @importFrom dplyr tbl_vars
#' @export
tbl_vars.tbl_graph <- function(x) {
  tbl_vars(as_tibble(x))
}
#' @export
dplyr::tbl_vars

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tidygraph documentation built on Feb. 16, 2023, 10:40 p.m.