ssinterp: ssinterp

In gjmvanboxtel/eegr: Electrophysiological data analysis

ssinterp

Description

Spherical spline interpolation of sensor locations

Usage

ssinterp(
  src,
  dest,
  lambda = 1e-05,
  order = 4,
  type = c("spline", "slap"),
  tol = 1e-07
)

Arguments

src	source sensor positions, specified as a data frame (or coerceable to a data frame), with 3 columns labeled x, y, and z.
dest	destination sensor positions, specified as a data frame (or coerceable to a data frame) with 3 columns labeled x, y, and z.
lambda	regularization parameter for smoothing the estimates, specified as a numeric scalar value. Default: 1e-5.
order	order of the polynomial interpolation to use, specified as a positive integer scalar value. Default: 4
type	character string specifying which interpolation method to use. One of "spline" - spherical spline interpolation) or "slap" - surface Laplacian (CSD). Default: "spline"
tol	tolerance for the Legendre polynomial approximation, specified as a numeric scalar value. Default: 1e-7.

Value

linear mapping matrix between old and new coordinates; a matrix with as many rows as the number of rows in dest and as many columns as the number of rows in src

Author(s)

Matlab code 2009 by Jason D.R. Farquhar ([e-mail]), adapted 2014 by Kay Robbins. R code by Geert van Boxtel, [e-mail]

References

Perrin, F., Pernier, J., Bertrand, O., & Echallier, J. F. (1989). Spherical splines for scalp potential and current density mapping. Electroencephalography and clinical neurophysiology, 72(2), 184-187.

Examples

src <- matrix(runif(300), 100, 3)
src[, 3] <- abs(src[, 3])
dest <- matrix(runif(90), 30, 3)
dest[, 3] <- abs(dest[, 3])
W <- ssinterp(src, dest)

gjmvanboxtel/eegr documentation built on May 20, 2023, 4:26 a.m.