```
SingleWarp <- function(ref, sample, beta, L = 40, lambda.smooth = 0, deg = 3,
lambda.bspline, kappa, max_it_Bspline) {
# specific parameters: for polynomial warping: beta for B spline
# warping: m, t, w0, L, deg, lambda.bspline, kappa, max_it
m <- length(ref)
t <- 1:m
sample0 <- sample
sel0 <- 1:m
# e.g. if you don't warp the extremities, you can set sel0 =
# 7700:25000;
t <- t[sel0]
t <- t - min(t) + 0.5
ref <- ref[sel0]
sample <- sample[sel0]
m <- length(ref)
# From here, we stop using sel0. We just ignore t, ref and sample out
# of sel0.
# POLYNOMIAL WARPING -------------------------------------------------
# smoothing
if (lambda.smooth == 0) {
smooth.sample <- sample
smooth.ref <- ref
} else {
# Start with parametric warp, after heavy smoothing
smooth.sample <- ptw::difsm(sample, lambda.smooth)
smooth.ref <- ptw::difsm(ref, lambda.smooth)
}
# Warp with polynomials, 1, v, ..., v^K
pw.out <- PolyWarp(ref = smooth.ref, sample = smooth.sample, beta = beta)
w <- pw.out$w # warping function
sel <- pw.out$sel # selected indices in spectrum
beta <- pw.out$beta # polynomial coefficients
if (lambda.smooth == 0) {
# It has not been smoothed
sample[sel] <- pw.out$warped
} else {
# We warp the non-smooth sample
interp.out <- Interpol(w, sample)
sel <- interp.out$s
sample[sel] <- interp.out$f
}
if (L >= 1) {
# BSPLINE WARPING -------------------------------------------------
bw.out <- BsplineWarp(ref = ref, sample = sample, m = m, t = t,
w0 = w, L = L, deg = deg, lambda.bspline = lambda.bspline,
kappa = kappa, max_it = max_it_Bspline)
w <- bw.out$w
sel <- bw.out$sel
alpha <- bw.out$alpha
sample[sel] <- bw.out$warped
}
# Change the part of sample we have not ignored
sample0[sel0] <- sample
return(list(warped = sample0, w = w))
}
```

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