Nothing

```
## Function to extract all peaks from the concentration profiles of an
## ALS object. For each sample, a list of matrices is returned,
## corresponding to the peaks found in each of the components.
getAllPeaks <- function(CList, span = NULL, eps = 1e-1) {
peakPositions <- lapply(CList,
function(Cmat)
lapply(1:ncol(Cmat),
function(ii)
findpeaks(Cmat[,ii], span = span)))
result <-
lapply(1:length(CList),
function(smpl) {
ptable <- lapply(1:length(peakPositions[[smpl]]),
function(cmpnd)
fitpeaks(CList[[smpl]][,cmpnd],
peakPositions[[smpl]][[cmpnd]]))
names(ptable) <- paste("Component",
1:length(peakPositions[[smpl]]))
ptable
})
names(result) <- names(peakPositions)
## sometimes NA values are returned, e.g. when a local max does not
## really correspond to a peak. Remove them!
result <- lapply(result,
function(smpl)
lapply(smpl,
function(pks)
pks[apply(pks, 1,
function(x)
!any(is.na(x))),,drop = FALSE]))
timepoints <- as.numeric(rownames(CList[[1]]))
tdiff <- median(diff(timepoints))
## convert results in indices to results in real time: the column
## mean must be replaced by the corresponding timepoints, and
## columns sd and FWHM must be multiplied by the difference between
## consecutive time points
output <- lapply(result,
function(smpl)
lapply(smpl,
function(cmpnd) {
x <- cmpnd
x[,1] <- timepoints[x[,1]]
x[,2:3] <- x[,2:3] * tdiff
x
}))
## only return those lines that have a width larger
## than zero. Sometimes we see zeros at sd, in those cases also area
## is zero. Perhaps we should check for empty matrices... let's see.
lapply(output,
function(sample)
lapply(sample,
function(peakmat)
peakmat[peakmat[,"sd"] > eps,, drop = FALSE]))
}
```

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