Autoplot Method for SONG Models

Creates a ggplot2 plot of a "song_model" object. Requires ggplot2 to be installed.

Usage

autoplot.song_model(
  object,
  type = c("embedding", "codebook", "graph"),
  color_by = NULL,
  ...
)

Arguments

object

A "song_model" object.

type

Character. One of "embedding", "codebook", or "graph".

color_by

Optional vector for coloring points.

...

Ignored.

Value

A ggplot object.

References

Senanayake, D. A., Wang, W., Naik, S. H., & Halgamuge, S. (2021). Self-Organizing Nebulous Growths for Robust and Incremental Data Visualization. IEEE Transactions on Neural Networks and Learning Systems, 32(10), 4588–4602. doi:10.1109/TNNLS.2020.3023941

Examples

# \donttest{
if (requireNamespace("ggplot2", quietly = TRUE)) {
  model <- song(as.matrix(iris[, 1:4]), epochs = 5L, seed = 42)
  # Use songR::autoplot.song_model(model, color_by = iris$Species)
  # or ensure songR is loaded with library(songR) for dispatch
}
#> Epoch 1/5 | CVs: 3 | QE: 1.5296 | so_lr: 1.0000 | lr: 1.0000
#> Epoch 2/5 | CVs: 5 | QE: 0.8414 | so_lr: 0.8187 | lr: 0.8000
#> Epoch 3/5 | CVs: 9 | QE: 0.5442 | so_lr: 0.4493 | lr: 0.6000
#> Epoch 4/5 | CVs: 16 | QE: 0.4508 | so_lr: 0.1653 | lr: 0.4000
#> Epoch 5/5 | CVs: 25 | QE: 0.3978 | so_lr: 0.0408 | lr: 0.2000
#> Running UMAP dispersion step...
# }