smooth: Generic Function for Smoothing a Surface or Associated Data

In bbuchsbaum/neurosurf: Data structures and IO for surface-based neuroimaging data

Generic Function for Smoothing a Surface or Associated Data

Description

The smooth function is a generic function designed to apply smoothing operations to various surface objects. The specific behavior of the function depends on the class of the object passed as the x argument. It can be used to smooth the geometry of a surface, the data associated with a surface, or other related operations depending on the method implemented for the object's class.

Usage

smooth(x, ...)

Arguments

x	The surface object to smooth. The specific class of x determines the type of smoothing applied.
...	Additional arguments passed to the specific method for smoothing the surface object.

Details

The smooth function provides a common interface for smoothing operations on different types of surface objects. The actual smoothing process varies based on the class of the object provided:

• For SurfaceGeometry objects, the function smooths the surface geometry, modifying the shape of the mesh to reduce noise.

• For NeuroSurface objects, the function smooths the data values associated with each vertex, preserving the surface geometry but producing a smoother dataset.

Users should refer to the specific method documentation for the class of object they are working with to understand the exact behavior and parameters.

See Also

smooth,SurfaceGeometry-method, smooth,NeuroSurface-method

Examples

## Not run: 
  # Smooth a SurfaceGeometry object
  smoothed_geom <- smooth(surface_geom_obj, type="taubin", lambda=0.7, iteration=10)

  # Smooth a NeuroSurface object's data
  smoothed_data_surface <- smooth(neuro_surf_obj, sigma=5)

## End(Not run)

bbuchsbaum/neurosurf documentation built on Aug. 29, 2024, 10:53 a.m.