\name{plot.peaksDataset}

\alias{plot}
\alias{.plotpA}
\alias{.plotpD}
\alias{.plotcA}

\title{Plotting functions for GCMS data objects}

\description{Store the raw data and optionally, information regarding signal peaks for a number of GCMS runs}

\usage{
.plotpD(object,runs=1:length(object@rawdata),mzind=1:nrow(object@rawdata[[1]]),
               mind=NULL,plotSampleLabels=TRUE,calcGlobalMax=FALSE,peakCex = 0.8,plotPeaks=TRUE,
			   plotPeakBoundaries=FALSE,plotPeakLabels=FALSE,plotMergedPeakLabels=TRUE,mlwd=3,
			   usePeaks=TRUE,plotAcrossRuns=FALSE,overlap=F,rtrange=NULL,cols=NULL,thin=1,
			   max.near=median(object@rawrt[[1]]),how.near=50,scale.up=1,...)
			   
.plotpA(object,xlab="Peaks - run 1",ylab="Peaks - run 2",plotMatches=TRUE,matchPch=19,matchLwd=3,
               matchCex=.5,matchCol="black",col=colorpanel(50,"black","blue","white"),
			   breaks=seq(0,1,length=51),...)
			   
.plotcA(object,alignment=1,...)
}

\arguments{

\item{object}{a \code{peaksDataset}, \code{peaksAlignment} or \code{clusterAlignment} object.}

\item{runs}{for \code{peaksDataset} only: set of run indices to plot}

\item{mzind}{for \code{peaksDataset} only: set of mass-to-charge indices to sum over (default, all)}

\item{mind}{for \code{peaksDataset} only: matrix of aligned indices}

\item{plotSampleLabels}{for \code{peaksDataset} only: logical, whether to display sample labels}

\item{calcGlobalMax}{for \code{peaksDataset} only: logical, whether to calculate an overall maximum for scaling}

\item{peakCex}{character expansion factor for peak labels}

\item{plotPeaks}{for \code{peaksDataset} only: logical, whether to plot hashes for each peak}

\item{plotPeakBoundaries}{for \code{peaksDataset} only: logical, whether to display peak boundaries}

\item{plotPeakLabels}{for \code{peaksDataset} only: logical, whether to display peak labels}

\item{plotMergedPeakLabels}{for \code{peaksDataset} only: logical, whether to display 'merged' peak labels}

\item{mlwd}{for \code{peaksDataset} only: line width of lines indicating the alignment}

\item{usePeaks}{for \code{peaksDataset} only: logical, whether to plot alignment of peaks (otherwise, scans)}

\item{plotAcrossRuns}{for \code{peaksDataset} only: logical, whether to plot across peaks when unmatched peak is given}

\item{overlap}{for \code{peaksDataset} only: logical, whether to plot TIC/XICs overlapping}

\item{rtrange}{for \code{peaksDataset} only: vector of length 2 giving start and end of the X-axis}

\item{cols}{for \code{peaksDataset} only: vector of colours (same length as the length of runs)}

\item{thin}{for \code{peaksDataset} only: when \code{usePeaks=FALSE}, plot the alignment lines every \code{thin} values}

\item{max.near}{for \code{peaksDataset} only: where to look for maximum}

\item{how.near}{for \code{peaksDataset} only: how far away from \code{max.near} to look}

\item{scale.up}{for \code{peaksDataset} only: a constant factor to scale the TICs}

\item{plotMatches}{for \code{peaksDataset} only: logical, whether to plot matches}

\item{xlab}{for \code{peaksAlignment} and \code{clusterAlignment} only: x-axis label}

\item{ylab}{for \code{peaksAlignment} and \code{clusterAlignment} only: y-axis label}

\item{matchPch}{for \code{peaksAlignment} and \code{clusterAlignment} only: match plotting character}

\item{matchLwd}{for \code{peaksAlignment} and \code{clusterAlignment} only: match line width}

\item{matchCex}{for \code{peaksAlignment} and \code{clusterAlignment} only: match character expansion factor}

\item{matchCol}{for \code{peaksAlignment} and \code{clusterAlignment} only: match colour}

\item{col}{for \code{peaksAlignment} and \code{clusterAlignment} only: vector of colours for colourscale}

\item{breaks}{for \code{peaksAlignment} and \code{clusterAlignment} only: vector of breaks for colourscale}

\item{alignment}{for \code{peaksAlignment} and \code{clusterAlignment} only: the set of alignments to plot}

\item{...}{further arguments passed to the \code{plot} or \code{image} command}

}


\details{
For \code{peakDataset} objects, each TIC is scale to the maximum value (as specified by the \code{how.near} and \code{max.near} values).  The many parameters gives considerable flexibility of how the TICs can be visualized.

For \code{peakAlignment} objects, the similarity matrix is plotted and optionally, the set of matching peaks.  \code{clusterAlignment} objects are just a collection of all pairwise \code{peakAlignment} objects.
}

\author{Mark Robinson}


\references{

Mark D Robinson (2008).  Methods for the analysis of gas chromatography - mass spectrometry data \emph{PhD dissertation} University of Melbourne.

}

\seealso{
\code{\link{plotImage}}, \code{\link{peaksDataset}}
}

\examples{
require(gcspikelite)

# paths and files
gcmsPath<-paste(.find.package("gcspikelite"),"data",sep="/")
cdfFiles<-dir(gcmsPath,"CDF",full=TRUE)
eluFiles<-dir(gcmsPath,"ELU",full=TRUE)

# read data
pd<-peaksDataset(cdfFiles[1:3],mz=seq(50,550),rtrange=c(7.5,8.5))

# image plot
plot(pd,rtrange=c(7.5,8.5),plotPeaks=TRUE,plotPeakLabels=TRUE)
}

\keyword{classes}