Periodic Rotation for Functional Data — periodic.rotate • fdars

Circularly rotate each curve so that its global maximum is at a canonical grid position. This is useful as a pre-processing step before elastic alignment of periodic functional data (e.g., data on $[0, 2\pi]$ where $f(0) = f(2\pi)$).

Usage

periodic.rotate(fdataobj, target.pos = NULL)

Arguments

fdataobj: An object of class 'fdata'.
target.pos: Target grid index for the global maximum. If NULL (default), uses floor(ncol(fdataobj$data) / 4).

Value

A list with components:

fdataobj: fdata of rotated curves
shifts: integer vector of circular shifts applied to each curve

References

Srivastava, A. and Klassen, E. (2016). Functional and Shape Data Analysis. Springer.

Examples

# Periodic sinusoidal curves with random circular shifts
argvals <- seq(0, 2 * pi, length.out = 100)
data <- matrix(0, 10, 100)
for (i in 1:10) {
  shift <- sample(0:99, 1)
  idx <- ((seq_len(100) - 1 + shift) %% 100) + 1
  data[i, ] <- sin(argvals[idx])
}
fd <- fdata(data, argvals = argvals)
rot <- periodic.rotate(fd)