dimRed (version 0.2.3)

FruchtermanReingold-class: Fruchterman Reingold Graph Layout

Description

An S4 Class implementing the Fruchterman Reingold Graph Layout algorithm.

Arguments

Slots

fun

A function that does the embedding and returns a dimRedResult object.

stdpars

The standard parameters for the function.

General usage

Dimensionality reduction methods are S4 Classes that either be used directly, in which case they have to be initialized and a full list with parameters has to be handed to the @fun() slot, or the method name be passed to the embed function and parameters can be given to the ..., in which case missing parameters will be replaced by the ones in the @stdpars.

Parameters

ndim

The number of dimensions, defaults to 2. Can only be 2 or 3

knn

Reduce the graph to keep only the neares neighbors. Defaults to 100.

d

The distance function to determine the weights of the graph edges. Defaults to euclidean distances.

Implementation

Wraps around layout_with_fr, see there for details. The Fruchterman Reingold algorithm puts the data into a circle and puts connected points close to each other.

References

Fruchterman, T.M.J., Reingold, E.M., 1991. Graph drawing by force-directed placement. Softw: Pract. Exper. 21, 1129-1164. https://doi.org/10.1002/spe.4380211102

See Also

Other dimensionality reduction methods: AutoEncoder-class, DRR-class, DiffusionMaps-class, DrL-class, FastICA-class, HLLE-class, Isomap-class, KamadaKawai-class, LLE-class, MDS-class, NNMF-class, PCA-class, PCA_L1-class, UMAP-class, dimRedMethod-class, dimRedMethodList, kPCA-class, nMDS-class, tSNE-class

Examples

Run this code
# NOT RUN {
dat <- loadDataSet("Swiss Roll", n = 100)

## use the S4 Class directly:
fruchterman_reingold <- FruchtermanReingold()
pars <- fruchterman_reingold@stdpars
pars$knn <- 5
emb <- fruchterman_reingold@fun(dat, pars)

## simpler, use embed():
emb2 <- embed(dat, "FruchtermanReingold", knn = 5)

plot(emb, type = "2vars")

# }

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