Plot a SONG Model

Visualize a "song_model" as a scatter plot of the embedding, the codebook, or the codebook graph with edges.

Usage

# S3 method for class 'song_model'
plot(x, type = c("embedding", "codebook", "graph"), color_by = NULL, ...)

Arguments

x

A "song_model" object.

type

Character. One of "embedding" (all input points in embedding space), "codebook" (coding vectors only), or "graph" (coding vectors with edges drawn). Default: "embedding".

color_by

Optional vector (factor or numeric) of length equal to the number of input points (for "embedding") or coding vectors (for "codebook" and "graph") used to color the points.

...

Additional arguments passed to plot.

Value

Invisible NULL.

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

See also

song, autoplot.song_model

Examples

model <- song(as.matrix(iris[, 1:4]), epochs = 5L, seed = 42)
#> 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...
plot(model, color_by = iris$Species)