Nothing
## plot profile matrix
setGeneric('csplotProf',function(object,...) standardGeneric('csplotProf'))
setMethod('csplotProf','chromatoSim',function(object,sampleID=NULL,...){
if(is.null(sampleID)) sampleID <- 1
p <- img(object,sampleID)
print(p)
})
## FIXME: With new qtinterface.
img <- function(object,sampleID){
require(ggplot2)
l2e(object@par,environment())
profile <- object@result$profile$a[[1]]
rt <- seq(rt_range[1],rt_range[2],rt_diff)
df <- data.frame(time=rep(rt,each=nrow(profile)),
mz=rep(mz_range[1]:mz_range[2],ncol(profile)),
int=as.numeric(profile))
df <- df[profile>500,] #FIXME:change 500 to a proper number
df[,'int'] <- log(df[,'int'])
p <- ggplot(df,aes(x=time,y=mz,fill=int))+geom_tile()
p <- p+scale_fill_gradient(limits=c(0,log(300000)),low='yellow',high='black')
p <- p+opts(legend.position='none')+scale_x_continuous(limits=c(0,3700))
p
}
## plot retention time match or drift diagnostic graphics
setGeneric('csplotRt',function(object,xlim=NULL,ylim=NULL,...) standardGeneric('csplotRt'))
setMethod('csplotRt','chromatoSim',function(object,xlim=NULL,ylim=NULL,...){
profile <- object@result$profile
Biobase::l2e(object@par,environment())
rt <- seq(rt_range[1],rt_range[2],rt_diff)
pflst <- do.call(c,profile)
pflst <- lapply(pflst,function(x) {x-missing})
rtlst <- do.call(c,object@result$rt)
poslst <- do.call(c,object@result$pos)
lst <- lapply(pflst,function(x) {apply(x,2,sum)})
n <- length(pflst)
if(is.null(xlim)) xlim=range(rt)
if(is.null(ylim)) ylim=range(lst)
df <- data.frame(rt=rep(rt,n),
intensity=unlist(lst),
group=rep(1:n,each=length(rt)))
p <- ggplot(data=df, aes(x=rt,y=intensity,group=factor(group),color=group))
p <- p+scale_x_continuous(limits=xlim)+
scale_y_continuous(limits=ylim)+
geom_line()
print(p)
})
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