\name{stitch-methods}
\docType{methods}
\alias{stitch-methods}
\alias{stitch}
\alias{stitch,xcmsRaw-method}
\alias{makeacqNum}
\alias{makeacqNum, xcmsRaw-method}

\title{Correct gaps in data}
\description{
  Fixes gaps in data due to calibration scans or lockmass.
}
\section{Methods}{
	\describe{
	\item{object = "xcmsRaw"}{
		\code{
		stitch(object, lockMass=numeric())
		}
		}
	}
	\describe{
	\item{object = "xcmsRaw"}{
	\code{
	makeacqNum(object, freq=numeric(), start=1)
		}
		}
	}

}

\arguments{
  \item{object}{An \code{\link{xcmsRaw-class}} object}
  \item{lockMass}{A dataframe of locations of the gaps}
  \item{freq}{The intervals of the lock mass scans}
  \item{start}{The starting lock mass scan location, default is 1}
}
\details{
	\code{makeacqNum} takes locates the gap using the starting lock mass scan and it's intervals. This data frame is then used in \code{stitch} to correct for the gap caused by the lock mass. Correction works by using scans from either side of the gap to fill it in.
}
\value{
	\code{stitch} A corrected \code{xcmsRaw-class} object
	\code{makeacqNum} A numeric vector of scan locations corresponding to lock Mass scans
}
\author{Paul Benton, \email{hpaul.benton08@imperial.ac.uk}}
\examples{
	\dontrun{library(xcms)
		library(faahKO) ## These files do not have this problem to correct for but just for an example
		cdfpath <- system.file("cdf", package = "faahKO")
		cdffiles <- list.files(cdfpath, recursive = TRUE, full.names = TRUE)
		xr<-xcmsRaw(cdffiles[1])
		xr
		##Lets assume that the lockmass starts at 1 and is every 100 scans
		lockMass<-xcms:::makeacqNum(xr, freq=100, start=1)
		ob<-stitch(xr, lockMass)
		ob
		
		#plot the old data before correction
		foo<-rawEIC(xr, m=c(200,210), scan=c(80,140))
		plot(foo$scan, foo$intensity, type="h")
		
		#plot the new corrected data to see what changed
		foo<-rawEIC(ob, m=c(200,210), scan=c(80,140))
		plot(foo$scan, foo$intensity, type="h")
	}
}
\keyword{manip}
\keyword{methods}