netsummary_plot: Network summary plots

In nethist: Network Histograms

Network summary plots

Description

Draw a network summary plot proposed by Maugis et al. (2017). To count k-cycles, Alon et al. (1997) is used.

Usage

netsummary_plot(
  A,
  subsample_sizes = NA,
  max_cycle_order = 4,
  n_rep = NA,
  n_subsample_sizes = 11,
  alpha = 0.05,
  y_max = NA,
  save_plot = FALSE,
  filename = "myplot.pdf",
  width = 7,
  height = 5,
  max_subsample_size = 250,
  ...
)

violin_netsummary(A, ...)

Arguments

A	an adjacency matrix, igraph object, or network object to draw a network summary plot. It must be an undirected and simple graph.
subsample_sizes	a numeric vector of vertex subsample sizes. If NA, the subsample size is selected automatically.
max_cycle_order	an integer value of the maximum cycle size. Must be ⁠>=3⁠ and ⁠<=7⁠.
n_rep	an integer value of subsampling replication. If NA, n_rep is automatically selected by alpha.
n_subsample_sizes	number of different subsample sizes for automatic selection. It is only used when subsample_sizes = NA.
alpha	a pre-specified level used in determining n_rep and subsample_sizes when they are not specified. It must be in (0,1). Default is 0.05. Smaller alpha gives larger n_rep and subsample_sizes.
y_max	Upper limit of y-axis of the plot. Must be 0 < y_max <= 1. If NA, the upper limit is automatically selected.
save_plot	A logical indicating whether to save the generated figure. If TRUE, the plot is saved via ggplot2::ggsave() using the specified file name. Otherwise, the plot is displayed.
filename	file name to save the generated figure.
width	a numeric value of the width of the generated figure in inch. It is only used when save_plot = TRUE.
height	a numeric value of the height of the generated figure in inch. It is only used when save_plot = TRUE.
max_subsample_size	integer. Upper bound on the automatically selected subsample size. Larger values improve statistical accuracy but increase computation time. Default is 250.
...	Pass R, Ns, y.max, or save.plot via the renamed arguments n_rep, n_subsample_sizes, y_max, and save_plot instead.

Details

Vertex sampling is done by simple random sampling without replacement.

The automatically selected subsample size is capped at max_subsample_size to limit computation time.

Each violin shows the distribution of the subsampled statistic, and a dot marks the mean.

The following input classes are supported: base::matrix, Matrix::dgCMatrix, igraph::igraph, network::network.

Value

A ggplot object. Printed as a side effect when save_plot = FALSE. Returns the plot invisibly when save_plot = TRUE.

References

Maugis et al. (2017). Topology reveals universal features for network comparison. arXiv: 1705.05677

Alon et al. (1997). Finding and counting given length cycles. Algorithmica 17, 209–223 (1997). https://doi.org/10.1007/BF02523189

Examples

{
set.seed(2022)
#Generating Erdos-Renyi graph
n <- 400
#igraph object
A <- igraph::sample_gnp(n, 0.05)
netsummary_plot(A)
}

#sparse adjacency matrix
A2 <- igraph::as_adjacency_matrix(A)
netsummary_plot(A2)

#dense adjacency matrix
A2 <- igraph::as_adjacency_matrix(A, sparse = FALSE)
netsummary_plot(A2)

#user-specified n_rep and subsample_sizes
netsummary_plot(A, n_rep = 500, subsample_sizes = 150)

#user-specified alpha
netsummary_plot(A, alpha = 0.1)

#network object
if (requireNamespace("network", quietly = TRUE)) {
  A3 <- network::as.network(igraph::as_adjacency_matrix(A, sparse = FALSE))
  netsummary_plot(A3)
}

#user-specified max_subsample_size
netsummary_plot(A, max_subsample_size = 100)

#saving the plot with user-specified file name
netsummary_plot(A, save_plot = TRUE,
                filename = file.path(tempdir(), "myfig.pdf"))

nethist documentation built on Oct. 25, 2026, 5:07 p.m.