Nothing

```
## grouper functions called by .binPeaks
## .grouperStrict
## strict grouping function
## Don't allow peaks of one sample in the same bin.
##
## params:
## mass: double, sorted mass
## intensities: double, corresponding intensities
## samples: double, corresponding sample id numbers
## tolerance: double, maximal deviation of a peak position to be
## considered as same peak
##
## returns:
## NA if further splitting is needed
## meanMass (double) if all criteria are matched
##
.grouperStrict <- function(mass, intensities, samples, tolerance) {
## don't accept two or more peaks of the same sample
if (anyDuplicated(samples)) {
return(NA)
}
meanMass <- mean(mass)
## all peaks in range?
if (any(abs(mass - meanMass) / meanMass > tolerance)) {
return(NA)
}
meanMass
}
## .grouperRelaxed
## relaxed grouping function (more than one peak of one sample per bin possible)
## choose highest peak in range.
##
## params:
## mass: double, sorted mass
## intensities: double, corresponding intensities
## samples: double, corresponding sample id numbers
## tolerance: double, maximal deviation of a peak position to be
## considered as same peak
## meanMass: double, mean of mass (new peak position)
##
## returns:
## NA if further splitting is needed
## meanMass (double) if all criteria are matched
##
.grouperRelaxed <- function(mass, intensities, samples, tolerance) {
meanMass <- mean(mass)
## all peaks in range?
if (any(abs(mass - meanMass) / meanMass > tolerance)) {
return(NA)
}
## choose highest peak in duplicates
if (anyDuplicated(samples)) {
s <- sort.int(intensities, decreasing=TRUE, index.return=TRUE)
samples <- samples[s$ix]
noDup <- !duplicated(samples)
noDup[s$ix] <- noDup
## replace mass corresponding to highest intensity
mass[noDup] <- mean(mass[noDup])
return(mass)
}
meanMass
}
## .grouperRelaxedHighestAtReference
## relaxed grouping function (more than one peak of one sample per bin possible)
## Choose highest test sample peaks in range around a reference peak.
##
## params:
## mass: double, sorted mass
## intensities: double, corresponding intensities
## samples: double, corresponding sample id numbers (1==reference)
## tolerance: double, maximal deviation of a peak position to be
## considered as same peak
## nomatch: return value if no reference peak found, mass for original mass, 0L
## for `determineWarpingFunctions`
##
## returns:
## NA if further splitting is needed
## meanMass (double) if all criteria are matched else 0
##
.grouperRelaxedHighestAtReference <- function(mass, intensities, samples,
tolerance, nomatch=mass) {
## any reference peaks in current samples?
ref <- samples == 1L
nRef <- sum(ref)
if (nRef == 0L) {
## no reference peak
return(nomatch)
} else if (nRef > 1L) {
## too many reference peaks => further splitting needed
return(NA)
}
## only one mass should left as reference mass
meanMass <- mass[ref]
## all peaks in range?
if (any(abs(mass - meanMass) / meanMass > tolerance)) {
return(NA)
}
## choose highest peak in duplicates
if (anyDuplicated(samples)) {
s <- sort.int(intensities, decreasing=TRUE, index.return=TRUE)
samples <- samples[s$ix]
noDup <- !duplicated(samples)
noDup[s$ix] <- noDup
## replace mass corresponding to highest intensity
mass[] <- nomatch
mass[noDup] <- meanMass
return(mass)
}
meanMass
}
```

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