cgb_smooth: Apply a precomputed CGB graph to volumetric data
In neuroim2: Data Structures for Brain Imaging Data
cgb_smooth R Documentation
Apply a precomputed CGB graph to volumetric data
Description
Apply a precomputed CGB graph to volumetric data
Usage
cgb_smooth(x, graph, passes = 1L, lambda = 1)
Arguments
x
A NeuroVec (4D) or NeuroVol (3D).
graph
Graph list returned by cgb_make_graph.
passes
Number of smoothing passes (>=1). Each pass multiplies by
W; if lambda < 1 a simple diffusion blend
(1 - lambda)I + lambda W is applied per pass.
lambda
Blend factor in [0,1] controlling diffusion strength.
Value
Smoothed object of the same class as x.
neuroim2 documentation built on April 16, 2026, 5:07 p.m.
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| cgb_smooth | R Documentation |
Apply a precomputed CGB graph to volumetric data
Description
Apply a precomputed CGB graph to volumetric data
Usage
cgb_smooth(x, graph, passes = 1L, lambda = 1)
Arguments
x |
A |
graph |
Graph list returned by |
passes |
Number of smoothing passes (>=1). Each pass multiplies by
|
lambda |
Blend factor in |
Value
Smoothed object of the same class as x.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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