nvd-plot {nevada} | R Documentation |
MDS Visualization of Network Distributions
Description
This function generates 2-dimensional plots of samples of networks via multi-dimensional scaling using all representations and distances included in the package.
Usage
## S3 method for class 'nvd'
autoplot(object, memberships = rep(1, length(object)), method = "mds", ...)
## S3 method for class 'nvd'
plot(x, method = "mds", ...)
Arguments
object , x |
A list containing two samples of network-valued data stored
as objects of class |
memberships |
An integer vector specifying the membership of each
network to a specific sample. Defaults to |
method |
A string specifying which dimensionality reduction method to
use for projecting the samples into the cartesian plane. Choices are
|
... |
Extra arguments to be passed to the plot function. |
Value
Invisibly returns a ggplot
object. In
particular, the data set computed to generate the plot can be retrieved via
$data
. This is a tibble
containing the following
variables:
-
V1
: the x-coordinate of each observation in the plane, -
V2
: the y-coordinate of each observation in the plane, -
Label
: the sample membership of each observation, -
Representation
: the type of matrix representation used to manipulate each observation, -
Distance
: the distance used to measure how far each observation is from the others.
Examples
gnp_params <- list(p = 1/3)
k_regular_params <- list(k = 8L)
x <- nvd(model = "gnp", n = 10L, model_params = gnp_params)
y <- nvd(model = "k_regular", n = 10L, model_params = k_regular_params)
mb <- c(rep(1, length(x)), rep(2, length(y)))
z <- as_nvd(c(x, y))
ggplot2::autoplot(z, memberships = mb)
plot(z, memberships = mb)