Wrapper for commute_cluster with standardized interface.
Usage
cluster4d_commute(
vec,
mask,
n_clusters = 100,
spatial_weight = 0.5,
verbose = FALSE,
ncomp = NULL,
...
)Arguments
- vec
A
NeuroVecinstance supplying the 4D data (x, y, z, time) to cluster- mask
A
NeuroVolmask defining the voxels to include in clustering. Values must be finite. Voxels are included exactly when the mask value is strictly greater than zero; zero and negative values are excluded.- n_clusters
Finite integer target number of clusters (default 100), from one through the number of included mask voxels. Note that some methods may produce slightly different numbers of clusters due to algorithmic constraints.
- spatial_weight
Method-specific spatial control in
[0, 1]. For methods that define a convex feature/spatial blend, zero disables the spatial term and one disables the feature term. Other methods use the value as a bounded mapping to a native scale; their endpoints do not have that blend meaning. Default 0.5. This parameter is inactive for"rena"and"rena_plus"; supplying it explicitly for either method is an error. Maps to method-specific parameters:supervoxels:
alpha = 1 - spatial_weight(0 = all spatial, 1 = all feature)snic:
compactness = spatial_weight * 10(range 0-10)slic:
compactness = spatial_weight * 20(typical range 1-20)corr_slic/brs_slic: direct convex blend between correlation and scaled spatial distance
slice_msf:
compactness = spatial_weight * 10, followed by FH component scale2 / (compactness + 1). This changes the graph-segmentation scale; it is not a convex spatial/feature blend.flash3d:
lambda_s = spatial_weight(direct mapping)mcl: direct blend between feature and spatial edge similarities
- verbose
Print progress messages. Default FALSE.
- ncomp
Number of embedding components (defaults to sqrt(2K)).
- ...
Additional method-specific parameters. See method documentation for details.