supervoxel_cluster_time: cluster objects with a temporal constraint

In bbuchsbaum/neurocluster: Spatially contrained clustering for neuroimaging data

cluster objects with a temporal constraint

Description

cluster objects with a temporal constraint

Usage

supervoxel_cluster_time(
  feature_mat,
  K = min(nrow(feature_mat), 100),
  sigma1 = 1,
  sigma2 = TR * 3,
  iterations = 50,
  TR = 2,
  filter = list(lp = 0, hp = 0),
  use_medoid = FALSE,
  nreps = 5
)

Arguments

K	the number of clusters to find.
sigma1	the bandwidth of the heat kernel for computing similarity of the data vectors.
sigma2	the bandwidth of the heat kernel for computing similarity of the coordinate vectors. If this value is small, then relatively larger weights are given to nearby voxels. If is is large, then spatial weights will be less salient. A relatively large sigma1/sigma2 ratio weights data features more than spatial features, whereas as large sigma2/sigma1 ration does the opposite.
iterations	the maximum number of cluster iterations
use_medoid	whether to use the medoids to define cluster centroids

Examples

feature_mat <- matrix(rnorm(100*10), 100, 10)
library(future)
plan(multicore)
cres <- supervoxel_cluster_time(t(feature_mat), K=20)

bbuchsbaum/neurocluster documentation built on April 1, 2024, 8:43 p.m.