trav_both {DiagrammeR} | R Documentation

## Traverse from one or more selected nodes onto neighboring nodes

### Description

From a graph object of class `dgr_graph` move from one or more nodes present in a selection to other nodes that are connected by edges, replacing the current nodes in the selection with those nodes traversed to. An optional filter by node attribute can limit the set of nodes traversed to.

### Usage

    trav_both(graph, conditions = NULL, copy_attrs_from = NULL,
      copy_attrs_as = NULL, agg = "sum", add_to_selection = FALSE)

### Arguments

`graph` | a graph object of class `dgr_graph`.
`conditions` | an option to use filtering conditions for the traversal.
`copy_attrs_from` | providing a node attribute name will copy those node attribute values to the traversed nodes. Any values extant on the nodes traversed to will be replaced.
`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 attribute name. If the attribute name provided in `copy_attrs_as` does not exist in the graph's ndf, the new node attribute will be created with the chosen name.
`agg` | if a node attribute is provided to `copy_attrs_from`, then an aggregation function is required since there may be cases where multiple edge attribute values will be passed onto the traversed node(s). To pass only a single value, the following aggregation functions can be used: `sum`, `min`, `max`, `mean`, or `median`.
`add_to_selection` | an option to either add the traversed to nodes to the active selection of nodes (`TRUE`) or switch the active selection entirely to those traversed to nodes (`FALSE`, the default case).

### Value

a graph object of class `dgr_graph`.

### Examples

    # Set a seed
    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"))

    # Create a data frame with node ID values
    # representing the graph edges (with `from`
    # and `to` columns), and, a set of numeric values
    df_edges <-
      data.frame(
        from = c(1, 1, 2, 2, 3),
        to = c(2, 3, 4, 5, 5),
        values = round(rnorm(5, 5), 2))

    # Create a data frame with node ID values
    # representing the graph nodes (with the `id`
    # columns), and, a set of numeric values
    df_nodes <-
      data.frame(
        id = 1:5,
        values = round(rnorm(5, 7), 2))

    # Join the data frame to the graph's internal
    # edge data frame (edf)
    graph <-
      graph %>%
      join_edge_attrs(df = df_edges) %>%
      join_node_attrs(df = df_nodes)

    # 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 node `3`
    # to adjacent nodes with no conditions on
    # the nodes traversed to
    graph %>%
      select_nodes_by_id(nodes = 3) %>%
      trav_both() %>%
      get_selection()

    # Traverse from node `2` to any adjacent
    # nodes, filtering to those nodes that have
    # numeric values less than `8.0` for
    # the `values` node attribute
    graph %>%
      select_nodes_by_id(nodes = 2) %>%
      trav_both(
        conditions = values < 8.0) %>%
      get_selection()

    # Traverse from node `5` to any adjacent
    # nodes, filtering to those nodes that
    # have a `type` attribute of `b`
    graph %>%
      select_nodes_by_id(nodes = 5) %>%
      trav_both(
        conditions = type == "b") %>%
      get_selection()

    # Traverse from node `2` to any adjacent
    # nodes, and use multiple conditions for the
    # traversal
    graph %>%
      select_nodes_by_id(nodes = 2) %>%
      trav_both(
        conditions =
          type == "a" &
          values > 8.0) %>%
      get_selection()

    # Traverse from node `2` to any adjacent
    # nodes, and use multiple conditions with
    # a single-length vector
    graph %>%
      select_nodes_by_id(nodes = 2) %>%
      trav_both(
        conditions =
          type == "a" | values > 8.0) %>%
      get_selection()

    # Traverse from node `2` to any adjacent
    # nodes, and use a regular expression as
    # a filtering condition
    graph %>%
      select_nodes_by_id(nodes = 2) %>%
      trav_both(
        conditions = grepl("..d", label)) %>%
      get_selection()

    # Create another simple graph to demonstrate
    # copying of node attribute values to traversed
    # nodes
    graph <-
      create_graph() %>%
      add_path(n = 5) %>%
      select_nodes_by_id(nodes = c(2, 4)) %>%
      set_node_attrs_ws(
        node_attr = value,
        value = 5)

    # 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 traversal from the inner nodes
    # (`2` and `4`) to their adjacent nodes (`1`,
    # `3`, and `5`) while also applying the node
    # attribute `value` to target nodes; node `3`
    # will obtain a `value` of 10 since a traversal
    # to `3` will occur from `2` and `4` (and
    # multiple values passed will be summed)
    graph <-
      graph %>%
      trav_both(
        copy_attrs_from = value,
        agg = "sum")

    # Show the graph's internal node data frame
    # after this change
    graph %>%
      get_node_df()

[Package DiagrammeR version 1.0.1 Index]