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#' Traverse from one or more selected nodes onto adjacent, outward edges
#'
#' @description
#'
#' From a graph object of class `dgr_graph` move to outgoing edges from a
#' selection of one or more selected nodes, thereby creating a selection of
#' edges. An optional filter by edge attribute can limit the set of edges
#' traversed to.
#'
#' This traversal function makes use of an active selection of nodes. After the
#' traversal, depending on the traversal conditions, there will either be a
#' selection of edges or no selection at all.
#'
#' Selections of nodes can be performed using the following node selection
#' (`select_*()`) functions: [select_nodes()], [select_last_nodes_created()],
#' [select_nodes_by_degree()], [select_nodes_by_id()], or
#' [select_nodes_in_neighborhood()].
#'
#' Selections of nodes can also be performed using the following traversal
#' (`trav_*()`) functions: [trav_out()], [trav_in()], [trav_both()],
#' [trav_out_node()], [trav_in_node()], [trav_out_until()], or
#' [trav_in_until()].
#'
#' @inheritParams render_graph
#' @param conditions An option to use filtering conditions for the traversal.
#' @param copy_attrs_from Providing a node attribute name will copy those node
#' attribute values to the traversed edges. If the edge attribute already
#' exists, the values will be merged to the traversed edges; otherwise, a new
#' edge attribute will be created.
#' @param copy_attrs_as If a node attribute name is provided in
#' `copy_attrs_from`, this option will allow the copied attribute values to be
#' written under a different edge attribute name. If the attribute name
#' provided in `copy_attrs_as` does not exist in the graph's edf, the new edge
#' attribute will be created with the chosen name.
#'
#' @return A graph object of class `dgr_graph`.
#'
#' @examples
#' # Set a seed
#' suppressWarnings(RNGversion("3.5.0"))
#' set.seed(23)
#'
#' # Create a simple graph
#' graph <-
#' create_graph() %>%
#' add_n_nodes(
#' n = 2,
#' type = "a",
#' label = c("asd", "iekd")) %>%
#' add_n_nodes(
#' n = 3,
#' type = "b",
#' label = c("idj", "edl", "ohd")) %>%
#' add_edges_w_string(
#' edges = "1->2 1->3 2->4 2->5 3->5",
#' rel = c(NA, "A", "B", "C", "D")) %>%
#' set_node_attrs(
#' node_attr = values,
#' values = c(2.3, 4.7, 9.4,
#' 8.3, 6.3))
#'
#' # Create a data frame with node ID values
#' # representing the graph edges (with `from`
#' # and `to` columns), and, a set of numeric values
#' df <-
#' data.frame(
#' from = c(1, 1, 2, 2, 3),
#' to = c(2, 3, 4, 5, 5),
#' values = round(rnorm(5, 5), 2))
#'
#' # Join the data frame to the graph's internal
#' # edge data frame (edf)
#' graph <-
#' graph %>%
#' join_edge_attrs(
#' df = df)
#'
#' # Show the graph's internal node data frame
#' graph %>% get_node_df()
#'
#' # Show the graph's internal edge data frame
#' graph %>% get_edge_df()
#'
#' # Perform a simple traversal from nodes to
#' # outbound edges with no conditions on the
#' # nodes traversed to
#' graph %>%
#' select_nodes_by_id(nodes = 1) %>%
#' trav_out_edge() %>%
#' get_selection()
#'
#' # Traverse from node `1` to any outbound
#' # edges, filtering to those edges that have
#' # NA values for the `rel` edge attribute
#' graph %>%
#' select_nodes_by_id(nodes = 1) %>%
#' trav_out_edge(
#' conditions = is.na(rel)) %>%
#' get_selection()
#'
#' # Traverse from node `3` to any outbound
#' # edges, filtering to those edges that have
#' # numeric values greater than `5.0` for
#' # the `rel` edge attribute
#' graph %>%
#' select_nodes_by_id(nodes = 3) %>%
#' trav_out_edge(
#' conditions = values > 5.0) %>%
#' get_selection()
#'
#' # Traverse from node `1` to any outbound
#' # edges, filtering to those edges that
#' # have values equal to `A` for the `rel`
#' # edge attribute
#' graph %>%
#' select_nodes_by_id(nodes = 1) %>%
#' trav_out_edge(
#' conditions = rel == "A") %>%
#' get_selection()
#'
#' # Traverse from node `2` to any outbound
#' # edges, filtering to those edges that
#' # have values in the set `B` and `C` for
#' # the `rel` edge attribute
#' graph %>%
#' select_nodes_by_id(nodes = 2) %>%
#' trav_out_edge(
#' conditions = rel %in% c("B", "C")) %>%
#' get_selection()
#'
#' # Traverse from node `2` to any
#' # outbound edges, and use multiple
#' # conditions for the traversal
#' graph %>%
#' select_nodes_by_id(nodes = 2) %>%
#' trav_out_edge(
#' conditions =
#' rel %in% c("B", "C") &
#' values >= 5.0) %>%
#' get_selection()
#'
#' # Traverse from node `2` to any
#' # outbound edges, and use multiple
#' # conditions
#' graph %>%
#' select_nodes_by_id(nodes = 2) %>%
#' trav_out_edge(
#' conditions =
#' rel %in% c("B", "C") |
#' values > 6.0) %>%
#' get_selection()
#'
#' # Traverse from node `2` to any outbound
#' # edges, and use a regular expression as
#' # a filtering condition
#' graph %>%
#' select_nodes_by_id(nodes = 2) %>%
#' trav_out_edge(
#' conditions = grepl("B|C", rel)) %>%
#' get_selection()
#'
#' # Perform a traversal from all nodes to
#' # their outgoing edges and, while doing
#' # so, copy the `label` node attribute
#' # to any of the nodes' incoming edges
#' graph <-
#' graph %>%
#' select_nodes() %>%
#' trav_out_edge(
#' copy_attrs_from = label)
#'
#' # Show the graph's internal edge
#' # data frame after this change
#' graph %>% get_edge_df()
#'
#' @export
trav_out_edge <- function(
graph,
conditions = NULL,
copy_attrs_from = NULL,
copy_attrs_as = NULL
) {
# Get the time of function start
time_function_start <- Sys.time()
# Validation: Graph object is valid
check_graph_valid(graph)
# Validation: Graph contains nodes
check_graph_contains_nodes(graph)
# Validation: Graph contains edges
check_graph_contains_edges(graph)
# Validation: Graph object has valid node selection
check_graph_contains_node_selection(
graph,
c("Any traversal requires an active selection.",
"This type of traversal requires a selection of nodes."))
# Get the requested `copy_attrs_from`
copy_attrs_from <-
rlang::enquo(copy_attrs_from) %>% rlang::get_expr() %>% as.character()
# Get the requested `copy_attrs_as`
copy_attrs_as <-
rlang::enquo(copy_attrs_as) %>% rlang::get_expr() %>% as.character()
if (length(copy_attrs_from) == 0) {
copy_attrs_from <- NULL
}
if (length(copy_attrs_as) == 0) {
copy_attrs_as <- NULL
}
if (!is.null(copy_attrs_as) && !is.null(copy_attrs_from)) {
if (copy_attrs_as == copy_attrs_from) {
copy_attrs_as <- NULL
}
}
# Get the selection of nodes as the starting
# nodes for the traversal
starting_nodes <- graph$node_selection$node
# Get the graph's node data frame
ndf <- graph$nodes_df
# Get the graph's edge data frame
edf <- graph$edges_df
# Find all edges that lead away from the
# starting nodes and remove edges that
# are loops
valid_edges <-
edf %>%
dplyr::filter(from %in% starting_nodes) %>%
dplyr::filter(to != from)
# If no rows returned, then there are no
# valid traversals, so return the same graph
# object without modifying the selection
if (nrow(valid_edges) == 0) {
return(graph)
}
# If traversal conditions are provided then
# pass in those conditions and filter the
# data frame of `valid_edges`
if (!rlang::quo_is_null(rlang::enquo(conditions))) {
valid_edges <- dplyr::filter(.data = valid_edges, {{ conditions }})
}
# If no rows returned, then there are no
# valid traversals, so return the same graph
# object without modifying the selection
if (nrow(valid_edges) == 0) {
return(graph)
}
# If the option is taken to copy node attribute
# values to the traversed edges, perform the join
# operation
if (!is.null(copy_attrs_from)) {
ndf_2 <-
ndf %>%
dplyr::filter(id %in% starting_nodes) %>%
dplyr::select("id", !!enquo(copy_attrs_from))
if (!is.null(copy_attrs_as)) {
if (copy_attrs_as %in% c("id", "from", "to")) {
cli::cli_abort(
"Copied attributes should not overwrite either of the `id`, `from`, or `to` edge attributes.")
}
colnames(ndf_2)[2] <- copy_attrs_from <- copy_attrs_as
}
# If node attribute doesn't exist in the edf,
# perform a full join
if (!(copy_attrs_from %in% colnames(edf))) {
edges <-
ndf_2 %>%
dplyr::right_join(edf, c("id" = "from")) %>%
dplyr::rename(from = "id.y") %>%
dplyr::relocate("id", "from", "to", "rel")
}
# If the node attribute exists as a column in the edf
if (copy_attrs_from %in% colnames(edf)) {
edges <-
ndf_2 %>%
dplyr::right_join(edf, c("id" = "from")) %>%
dplyr::rename(from = "id") %>%
dplyr::rename(id = "id.y")
# Get column numbers that end with ".x" or ".y"
split_var_x_col <-
grep("\\.x$", colnames(edges))
split_var_y_col <-
grep("\\.y$", colnames(edges))
# Selectively merge in values to the existing
# edge attribute column
for (i in seq_len(nrow(edges))) {
if (!is.na(edges[i, split_var_x_col])) {
edges[i, split_var_y_col] <- edges[i, split_var_x_col]
}
}
# Rename the ".y" column
colnames(edges)[split_var_y_col] <- colnames(ndf_2)[2]
# Drop the ".x" column
edges <- edges[-split_var_x_col]
# Reorder columns
edges <-
edges %>%
dplyr::relocate("id", "from", "to", "rel")
}
# Update the graph's internal node data frame
graph$edges_df <- edges
}
# Get the name of the function
fcn_name <- get_calling_fcn()
# Add the edge information to the active selection
# of edges in `graph$edge_selection`
graph$edge_selection <-
replace_graph_edge_selection(
graph = graph,
edge_id = valid_edges$id,
from_node = valid_edges$from,
to_node = valid_edges$to)
# Replace `graph$node_selection` with an empty df
graph$node_selection <- create_empty_nsdf()
# Update the `graph_log` df with an action
graph$graph_log <-
add_action_to_log(
graph_log = graph$graph_log,
version_id = nrow(graph$graph_log) + 1L,
function_used = fcn_name,
time_modified = time_function_start,
duration = graph_function_duration(time_function_start),
nodes = nrow(graph$nodes_df),
edges = nrow(graph$edges_df))
# Write graph backup if the option is set
if (graph$graph_info$write_backups) {
save_graph_as_rds(graph = graph)
}
graph
}
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