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Cluster4d using FLASH-3D method

Source: R/cluster4d.R
cluster4d_flash3d.Rd

Wrapper for FLASH-3D algorithm with standardized interface.

Usage

cluster4d_flash3d(
  vec,
  mask,
  n_clusters = 100,
  spatial_weight = 0.25,
  max_iterations = 4,
  verbose = FALSE,
  lambda_t = NULL,
  bits = 64,
  dctM = 16,
  ...
)

Arguments

vec

A NeuroVec instance supplying the 4D data (x, y, z, time) to cluster

mask

A NeuroVol mask 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 scale 2 / (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

max_iterations

Positive finite integer iteration limit for iterative methods. It is inactive for "snic", "slice_msf", and "commute"; supplying it explicitly for those methods is an error.

verbose

Print progress messages. Default FALSE.

lambda_t

Optional finite non-negative temporal weight for Hamming distance. When omitted, it is 1 - spatial_weight, so the unified interface preserves both feature-only and spatial-only endpoints.

bits

Hash length (64 or 128)

dctM

Number of DCT coefficients

...

Additional parameters passed to supervoxels_flash3d

Value

A cluster4d_result object