pcvr (version 1.2.0)

net.plot: Visualizing igraph networks

Description

Easy igraph visualization with pcv.net output

Usage

net.plot(
  net,
  fill = "strength",
  shape = NULL,
  size = 3,
  edgeWeight = "emd",
  edgeFilter = NULL
)

Value

Returns a ggplot of a network.

Arguments

net

Network object similar to that returned from pcv.net, having dataframes named "edges" and "nodes"

fill

Variable name(s) from the nodes data to be used to color points. By default "strength" is used.

shape

Optional discrete variable name(s) from the nodes data to be used to change the shape of points. If this variable is numeric it will be coerced to character.

size

Size of points, defaults to 3.

edgeWeight

Edge dataframe column to weight connections between nodes. Defaults to "emd" for compatability with pcv.emd.

edgeFilter

How should edges be filtered? This can be either a numeric (0.5) in which case it is taken as a filter where only edges with values greater than or equal to that number are kept or a character string ("0.5") in which case the strongest X percentage of edges are kept. This defaults to NULL which does no filtering, although that should not be considered the best standard behaviour. See details.

Examples

library(extraDistr)
dists <- list(
  rmixnorm = list(mean = c(70, 150), sd = c(15, 5), alpha = c(0.3, 0.7)),
  rnorm = list(mean = 90, sd = 3)
)
x <- mvSim(
  dists = dists, n_samples = 5, counts = 1000,
  min_bin = 1, max_bin = 180, wide = TRUE
)
emd_df <- pcv.emd(x,
  cols = "sim", reorder = c("group"), mat = FALSE,
  plot = FALSE, parallel = 1
)
net <- pcv.net(emd_df, meta = "group")
net.plot(net)
net.plot(net, edgeFilter = "0.25")
net.plot(net,
  edgeFilter = 0.25, fill = c("degree", "group"),
  shape = c("degree", "group")
)
net.plot(net,
  edgeFilter = 0.25, fill = c("degree", "group"),
  shape = c("degree")
)