Marcelo Laia wrote:
> Hi,
>
> I have a data set like this:
>
> Mutant Rep Time OD
> 02H02 1 0 0.029
> 02H02 2 0 0.029
> 02H02 3 0 0.023
> 02H02 1 8 0.655
> 02H02 2 8 0.615
> 02H02 3 8 0.557
> 02H02 1 12 1.776
> 02H02 2 12 1.859
> 02H02 3 12 1.668
> 02H02 1 16 3.379
> 02H02 2 16 3.726
> 02H02 3 16 3.367
> 306 1 0 0.033
> 306 2 0 0.035
> 306 3 0 0.034
> 306 1 8 0.377
> 306 2 8 0.488
> 306 3 8 0.409
> 306 1 12 1.106
> 306 2 12 1.348
> 306 3 12 1.246
> 306 1 16 2.706
> 306 2 16 3.073
> 306 3 16 3.038
>
> I need to plot a graph OD over the time for each one mutant with error bars.
>
> I try the package sciplot, but this package is set up to handle
> factorial treatments, so the spacing in x-axis is fixed to be equal.
> Than, with it I got something like this:
>
> |
> |
> |
> |
> |
> +-----------------------------
> 0 8 12 16
>
> But, I would like spacing between 0 and 8 2-fold the spacign between 8
> and 12, like this:
>
> |
> |
> |
> |
> |
> +--------------------------------------
> 0 4 8 12 16
>
> Could you point me out another way to do this with out using sciplot?
> Any suggestion is very appreciated.
>
Hi Marcelo,
This might be a task for brkdn.plot in the plotrix package except for
the X positions. I have written a revision of the function as this will
be a useful enhancement and minimally tested it, so if you would like to
give it a try, here it is:
library(plotrix)
# here is the revised function, may have some line breaks
brkdn.plot<-function(vars,groups=NA,obs=NA,data,
mct="mean",md="std.error",
stagger=NA,dispbar=TRUE,
main="Breakdown plot",xlab=NA,ylab=NA,xaxlab=NA,
ylim=NA,type="b",pch=1,lty=1,col=par("fg"),...) {
if(is.na(obs)) {
if(is.na(groups))
stop("Must have at least one factor to subset data")
bygroup<-as.factor(data[[groups]])
grouplevels<-levels(bygroup)
ngroups<-length(grouplevels)
nobs<-length(vars)
obslevels<-1:nobs
}
else {
byobs<-as.factor(data[[obs]])
obslevels<-levels(byobs)
nobs<-length(obslevels)
if(is.numeric(unlist(data[obs])))
obs.pos<-unique(unlist(data[obs]))
else obs.pos<-1:nobs
if(is.na(groups)) {
ngroups<-length(vars)
grouplevels<-1:ngroups
}
else {
bygroup<-as.factor(data[[groups]])
grouplevels<-levels(bygroup)
ngroups<-length(grouplevels)
if(length(vars) > 1) {
warning("Group and observation present, only vars[1] plotted")
vars<-vars[1]
}
}
}
brkdn<-list(matrix(NA,nrow=ngroups,ncol=nobs),
matrix(NA,nrow=ngroups,ncol=nobs))
if(is.na(groups)) {
if(is.na(xlab)) xlab<-"Observation"
xat<-1:nobs
if(is.na(xaxlab[1])) xaxlab<-obslevels
for(group in 1:ngroups) {
for(ob in 1:nobs) {
brkdn[[1]][group,ob]<-
do.call(mct,list(unlist(subset(data[[vars[group]]],
data[[obs]] == obslevels[ob],vars[group])),na.rm=TRUE))
if(!is.na(md))
brkdn[[2]][group,ob]<-
do.call(md,list(unlist(subset(data[[vars[group]]],
data[[obs]] == obslevels[ob],vars[group])),na.rm=TRUE))
}
}
}
else {
if(is.na(obs)) {
if(is.na(xlab)) xlab<-"Variable"
xat<-1:length(vars)
if(is.na(xaxlab[1])) xaxlab<-vars
for(group in 1:ngroups) {
for(ob in 1:nobs) {
brkdn[[1]][group,ob]<-
do.call(mct,list(unlist(subset(data[[vars[ob]]],
data[[groups]] == grouplevels[group],vars[ob])),na.rm=TRUE))
if(!is.na(md))
brkdn[[2]][group,ob]<-
do.call(md,list(unlist(subset(data[[vars[ob]]],
data[[groups]] == grouplevels[group],vars[ob])),na.rm=TRUE))
}
}
}
else {
if(is.na(xlab)) xlab<-"Observation"
xat<-obs.pos
if(is.na(xaxlab[1])) xaxlab<-obslevels
for(group in 1:ngroups) {
for(ob in 1:nobs) {
brkdn[[1]][group,ob]<-
do.call(mct,list(unlist(subset(data,data[[groups]] ==
grouplevels[group] &
data[[obs]] == obslevels[ob],vars)),na.rm=TRUE))
if(!is.na(md))
brkdn[[2]][group,ob]<-
do.call(md,list(unlist(subset(data,data[[groups]] ==
grouplevels[group] &
data[[obs]] == obslevels[ob],vars)),na.rm=TRUE))
}
}
}
}
if(is.na(ylim[1])) {
if(is.na(md)) ylim<-range(brkdn[[1]])
else
ylim<-c(min(brkdn[[1]]-brkdn[[2]],na.rm=TRUE),
max(brkdn[[1]]+brkdn[[2]],na.rm=TRUE))
}
groupdiv<-ifelse(ngroups < 3,1,ngroups-2)
if(is.na(stagger)) stagger<-0.025-groupdiv*0.0025
if(is.na(ylab)) {
if(length(vars) == 1) ylab<-vars[1]
else ylab<-paste(vars,collapse=" and ")
}
plot(0,xlim=c(obs.pos[1]-0.5,obs.pos[nobs]+0.5),
main=main,xlab=xlab,ylab=ylab,ylim=ylim,
type="n",axes=FALSE,...)
box()
axis(1,at=xat,labels=xaxlab)
axis(2)
if(length(pch) < ngroups) pch<-rep(pch,length.out=ngroups)
if(length(col) < ngroups) col<-rep(col,length.out=ngroups)
if(length(lty) < ngroups) lty<-rep(lty,length.out=ngroups)
offinc<-stagger*diff(par("usr")[c(1,2)])
offset<-0
arrow.cap<-0.01-(groupdiv*0.001)
for(group in 1:ngroups) {
points(obs.pos+offset,brkdn[[1]][group,],type=type,
col=col[group],pch=pch[group],lty=lty[group])
if(dispbar)
dispbars(obs.pos+offset,brkdn[[1]][group,],brkdn[[2]][group,],
arrow.cap=arrow.cap,col=col[group])
offset<-ifelse(offset<0,-offset,-offset-offinc)
}
names(brkdn)<-c(mct,md)
return(brkdn)
}
# read in the data
ml.df<-read.csv("../ml.csv")
# call the new function
brkdn.plot("OD","Mutant","Time",ml.df,col=c(2,3))
Jim
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