add_growing_graph {DiagrammeR} | R Documentation

## Create a random growing graph with m edges added per step

### Description

To an existing graph object, add a graph built by adding `m` new edges at each time step (where a node is added).

### Usage

    add_growing_graph(graph, n, m = 1, citation = FALSE, type = NULL,
      label = TRUE, rel = NULL, node_aes = NULL, edge_aes = NULL,
      node_data = NULL, edge_data = NULL, set_seed = NULL)

### Arguments

`graph` | a graph object of class `dgr_graph`.
`n` | the number of nodes comprising the generated graph.
`m` | the number of edges added per time step.
`citation` | a logical value (default is `FALSE`) that governs whether a citation graph is to be created. This is where new edges specifically originate from the newly added node in the most recent time step.
`type` | an optional string that describes the entity type for all the nodes to be added.
`label` | a boolean value where setting to `TRUE` ascribes node IDs to the label and `FALSE` yields a blank label.
`rel` | an optional string for providing a relationship label to all edges to be added.
`node_aes` | an optional list of named vectors comprising node aesthetic attributes. The helper function `node_aes()` is strongly recommended for use here as it contains arguments for each of the accepted node aesthetic attributes (e.g., `shape`, `style`, `color`, `fillcolor`).
`edge_aes` | an optional list of named vectors comprising edge aesthetic attributes. The helper function `edge_aes()` is strongly recommended for use here as it contains arguments for each of the accepted edge aesthetic attributes (e.g., `shape`, `style`, `penwidth`, `color`).
`node_data` | an optional list of named vectors comprising node data attributes. The helper function `node_data()` is strongly recommended for use here as it helps bind data specifically to the created nodes.
`edge_data` | an optional list of named vectors comprising edge data attributes. The helper function `edge_data()` is strongly recommended for use here as it helps bind data specifically to the created edges.
`set_seed` | supplying a value sets a random seed of the `Mersenne-Twister` implementation.

### Examples

    # Create a random, growing
    # citation graph with 100
    # nodes, adding an edge after
    # each node addition
    growing_graph <-
      create_graph() %>%
      add_growing_graph(
        n = 100,
        m = 1,
        citation = TRUE,
        set_seed = 23)

    # Get a count of nodes
    growing_graph %>%
      count_nodes()

    # Get a count of edges
    growing_graph %>%
      count_edges()

[Package DiagrammeR version 1.0.1 Index]