WormTensor (version 0.1.2)

AllGenerics_component: Components for WormTensor object

Description

These are generic methods for WormTensor

Usage

worm_membership(object, k)
worm_clustering(
  object,
  algorithm = c("MCMI", "OINDSCAL", "CSPA"),
  num.iter = 30,
  thr = 1e-10,
  verbose = FALSE
)
worm_evaluate(object, labels = NULL)
worm_visualize(
  object,
  out.dir = tempdir(),
  algorithm = c("tSNE", "UMAP"),
  seed = 1234,
  tsne.dims = 2,
  tsne.perplexity = 15,
  tsne.verbose = FALSE,
  tsne.max_iter = 1000,
  umap.n_neighbors = 15,
  umap.n_components = 2,
  silhouette.summary = FALSE
)

Arguments

object

WormTensor object

k

Assumed number of clusters

algorithm

Dimensional reduction methods

num.iter

The upper limit of iterations (Default value is 30)

thr

The lower limit of relative change in estimates (Default value is 1E-10)

verbose

Control message

labels

Labels for external evaluation

out.dir

Output directory (default: tempdir())

seed

Arguments passed to set.seed (default: 1234)

tsne.dims

Output dimensionality (default: 2)

tsne.perplexity

Perplexity paramete (default: 15)

tsne.verbose

logical; Whether progress updates should be printed (default: TRUE)

tsne.max_iter

The number of iterations (default: 1000)

umap.n_neighbors

The size of local neighborhood (default: 15)

umap.n_components

The dimension of the space to embed into (default: 2)

silhouette.summary

logical; If true a summary of cluster silhouettes are printed.