`igraphHRG` objects can be printed to the screen in two forms: as a tree or as a list, depending on the `type` argument of the print function. By default the `auto` type is used, which selects `tree` for small graphs and `simple` (=list) for bigger ones. The `tree` format looks like this:

``````Hierarchical random graph, at level 3:
g1        p=   0
'- g15    p=0.33  1
'- g13 p=0.88  6  3  9  4  2  10 7  5  8
'- g8     p= 0.5
'- g16 p= 0.2  20 14 17 19 11 15 16 13
'- g5  p=   0  12 18  ``````

This is a graph with 20 vertices, and the top three levels of the fitted hierarchical random graph are printed. The root node of the HRG is always vertex group #1 (‘`g1`’ in the the printout). Vertex pairs in the left subtree of `g1` connect to vertices in the right subtree with probability zero, according to the fitted model. `g1` has two subgroups, `g15` and `g8`. `g15` has a subgroup of a single vertex (vertex 1), and another larger subgroup that contains vertices 6, 3, etc. on lower levels, etc. The `plain` printing is simpler and faster to produce, but less visual:

``````Hierarchical random graph:
g1  p=0.0 -> g12 g10   g2  p=1.0 -> 7 10      g3  p=1.0 -> g18 14
g4  p=1.0 -> g17 15    g5  p=0.4 -> g15 17    g6  p=0.0 -> 1 4
g7  p=1.0 -> 11 16     g8  p=0.1 -> g9 3      g9  p=0.3 -> g11 g16
g10 p=0.2 -> g4 g5     g11 p=1.0 -> g6 5      g12 p=0.8 -> g8 8
g13 p=0.0 -> g14 9     g14 p=1.0 -> 2 6       g15 p=0.2 -> g19 18
g16 p=1.0 -> g13 g2    g17 p=0.5 -> g7 13     g18 p=1.0 -> 12 19
g19 p=0.7 -> g3 20``````

It lists the two subgroups of each internal node, in as many columns as the screen width allows.

## Usage

``````# S3 method for class 'igraphHRG'
print(x, type = c("auto", "tree", "plain"), level = 3, ...)``````

## Arguments

x

`igraphHRG` object to print.

type

How to print the dendrogram, see details below.

level

The number of top levels to print from the dendrogram.

...

Other hierarchical random graph functions: `consensus_tree()`, `fit_hrg()`, `hrg()`, `hrg-methods`, `hrg_tree()`, `predict_edges()`, `print.igraphHRGConsensus()`, `sample_hrg()`