trav_out_node {DiagrammeR} | R Documentation

## Traverse from one or more selected edges onto adjacent, outward nodes

### Description

From a graph object of class `dgr_graph` with an active selection of edges move opposite to the edge direction to connected nodes, replacing the current edge selection with those nodes traversed to. An optional filter by node attribute can limit the set of nodes traversed to.

### Usage

    trav_out_node(graph, conditions = NULL, copy_attrs_from = NULL,
      copy_attrs_as = NULL, agg = "sum")

### Arguments

`graph` | a graph object of class `dgr_graph`.
`conditions` | an option to use filtering conditions for the traversal.
`copy_attrs_from` | providing an edge attribute name will copy those edge attribute values to the traversed nodes. If the edge attribute already exists, the values will be merged to the traversed nodes; otherwise, a new node attribute will be created.
`copy_attrs_as` | if an edge attribute name is provided in `copy_attrs_from`, this option will allow the copied attribute values to be written under a different node 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 an edge 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`.

### 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 the
    # edge `1`->`3` to the attached node
    # in the direction of the edge; here, no
    # conditions are placed on the nodes
    # traversed to
    graph %>%
      select_edges(
        from = 1,
          to = 3) %>%
      trav_out_node() %>%
      get_selection()

    # Traverse from edges `2`->`5` and
    # `3`->`5` to the attached node along
    # the direction of the edge; here, the
    # traversals lead to different nodes
    graph %>%
      select_edges(
        from = 2,
          to = 5) %>%
      select_edges(
        from = 3,
          to = 5) %>%
      trav_out_node() %>%
      get_selection()

    # Traverse from the edge `1`->`3`
    # to the attached node where the edge
    # is outgoing, this time filtering
    # numeric values greater than `7.0` for
    # the `values` node attribute
    graph %>%
      select_edges(
        from = 1,
          to = 3) %>%
      trav_out_node(
        conditions = values > 7.0) %>%
      get_selection()

    # Traverse from the edge `1`->`3`
    # to the attached node where the edge
    # is outgoing, this time filtering
    # numeric values less than `7.0` for
    # the `values` node attribute (the
    # condition is not met so the original
    # selection of edge `1`->`3` remains)
    graph %>%
      select_edges(
        from = 1,
          to = 3) %>%
      trav_out_node(
        conditions = values < 7.0) %>%
      get_selection()

    # Traverse from the edge `1`->`2`
    # to node `2`, using multiple conditions
    graph %>%
      select_edges(
        from = 1,
          to = 2) %>%
      trav_out_node(
        conditions =
          grepl(".*d$", label) |
          values < 6.0) %>%
      get_selection()

    # Create another simple graph to demonstrate
    # copying of edge attribute values to traversed
    # nodes
    graph <-
      create_graph() %>%
      add_node() %>%
      select_nodes() %>%
      add_n_nodes_ws(
        n = 2,
        direction = "from") %>%
      clear_selection() %>%
      select_nodes_by_id(nodes = 2) %>%
      set_node_attrs_ws(
        node_attr = value,
        value = 8) %>%
      clear_selection() %>%
      select_edges_by_edge_id(edges = 1) %>%
      set_edge_attrs_ws(
        edge_attr = value,
        value = 5) %>%
      clear_selection() %>%
      select_edges_by_edge_id(edges = 2) %>%
      set_edge_attrs_ws(
        edge_attr = value,
        value = 5) %>%
      clear_selection() %>%
      select_edges()

    # Show the graph's internal edge data frame
    graph %>%
      get_edge_df()

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

    # Perform a traversal from the edges to
    # the central node (`1`) while also applying
    # the edge attribute `value` to the node (in
    # this case summing the `value` of 5 from
    # both edges before adding as a node attribute)
    graph <-
      graph %>%
      trav_out_node(
        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]