FLIMplots {TIMP} | R Documentation |
Functions to plot FLIM results.
Description
Functions to plot FLIM results.
Usage
plotHistAmp(multimodel, t, i=1)
plotHistNormComp(multimodel, t, i=1)
plotIntenImage(multimodel, t, i=1, tit=c("Intensity Image"))
plotSelIntenImage(multimodel, t, i=1, tit=c("Region of Interest"),
cex=1)
plotTau(multimodel, t, i=1, tit=" < tau > ", plotoptions=kinopt(),
lifetimes=TRUE)
plotNormComp(multimodel, t, i=1)
Arguments
multimodel |
the |
t |
the |
i |
dataset index to make plot for |
tit |
Character vector giving the title |
plotoptions |
object of class |
cex |
A numerical value giving the amount by which plotting text and symbols should be magnified relative to the default |
lifetimes |
A logical value indicating whether the averages per-pixel should be for lifetimes or their inverse, decay rates. |
Value
No return value, called for side effects
Author(s)
Katharine M. Mullen, Sergey Laptenok, Ivo H. M. van Stokkum
See Also
Examples
##############################
## READ IN DATA, PREPROCESS DATA
##############################
## data representing only donor tagged
data("donorTagged")
D1 <- preProcess(c001, sel_time=c(25,230))
D2 <- preProcess(c003, sel_time=c(25,230))
## data representing donor-acceptor tagged
data("donorAcceptorTagged")
DA1 <- preProcess(cy005c, sel_time=c(25,230))
DA2 <- preProcess(cy006, sel_time=c(25,230))
##############################
## READ IN MEASURED IRF, PREPROCESS IRF
##############################
data("mea_IRF")
mea_IRF <- baseIRF(mea_IRF, 100, 150)[25:230]
##############################
## SPECIFY INITIAL MODEL
##############################
modelC <- initModel(mod_type = "kin",
## starting values for decays
kinpar=c(1.52, 0.36),
## numerical convolution algorithm to use
convalg = 2,
## measured IRF
measured_irf = mea_IRF,
lambdac = 650,
## shift of the irf is fixed
parmu = list(0), fixed = list(parmu=1),
## one component represents a pulse-following with the IRF shape
cohspec = list(type = "irf"),
## parallel kinetics
seqmod=FALSE,
## decay parameters are non-negative
positivepar=c("kinpar"),
title="Global CFP bi-exp model with pulse-follower")
##############################
## FIT MODEL FOR DONOR ONLY DATA
##############################
fitD <- fitModel(list(D1,D2),
list(modelC),
## estimate the linear coeefficients per-dataset
modeldiffs = list(linkclp=list(1,2)),
opt=kinopt(iter=1, linrange = 10,
addfilename = TRUE,
output = "pdf",
makeps = "globalD",
notraces = TRUE,
selectedtraces = seq(1, length(c001@x2), by=11),
summaryplotcol = 4, summaryplotrow = 4,
ylimspec = c(1, 2.5),
xlab = "time (ns)", ylab = "pixel number",
FLIM=TRUE))
##############################
## FIT MODEL FOR DONOR-ACCEPTOR DATA
##############################
fitDA <- fitModel(list(DA1,DA2),
list(modelC),
## estimate the linear coeefficients per-dataset
modeldiffs = list(linkclp=list(1,2)),
opt=kinopt(iter=1, linrange = 10,
addfilename = TRUE,
output = "pdf",
makeps = "globalDA",
notraces = TRUE,
selectedtraces = seq(1, length(c001@x2), by=11),
summaryplotcol = 4, summaryplotrow = 4,
ylimspec = c(1, 2.5),
xlab = "time (ns)", ylab = "pixel number",
FLIM=TRUE))
##############################
## COMPARE THE DECAY RATES
##############################
parEst(fitD)
parEst(fitDA)
##############################
## ADDITIONAL FIGURES
##############################
oldpar <- par(no.readonly = TRUE)
par(mfrow=c(2,2), mar=c(1,3,1,12))
par(cex=1.5)
plotIntenImage(fitD$currModel, fitD$currTheta, 1, tit="")
par(cex=1.5)
plotIntenImage(fitDA$currModel, fitD$currTheta, 1, tit="")
par(cex=1.5)
plotIntenImage(fitD$currModel, fitD$currTheta, 2, tit="")
par(cex=1.5)
plotIntenImage(fitDA$currModel, fitD$currTheta, 2, tit="")
par(oldpar)
###############
plo <- kinopt(ylimspec = c(.25,1.1), imagepal=grey(seq(1,0,length=100)))
par(mfrow=c(2,2), mar=c(1,3,1,12))
par(cex=1.5)
plotTau(fitD$currModel, fitD$currTheta, 1, tit="",plotoptions=plo,
lifetimes=FALSE)
par(cex=1.5)
plotTau(fitDA$currModel, fitD$currTheta, 1, tit="",plotoptions=plo,
lifetimes=FALSE)
par(cex=1.5)
plotTau(fitD$currModel, fitD$currTheta, 2, tit="",plotoptions=plo,
lifetimes=FALSE)
par(cex=1.5)
plotTau(fitDA$currModel, fitD$currTheta, 2, tit="", plotoptions=plo,
lifetimes=FALSE)
par(oldpar)
# end donttest
##############################
## CLEANUP GENERATED FILES
##############################
# This removes the files that were generated in this example
# (do not run this code if you wish to inspect the output)
file_list_cleanup = c('globalDA_paramEst.txt', 'globalDA_spec_dataset_1.txt',
'globalDA_spec_dataset_2.txt', 'globalD_paramEst.txt',
'globalD_spec_dataset_1.txt', 'globalD_spec_dataset_2.txt',
Sys.glob("*paramEst.txt"), Sys.glob("*.ps"), Sys.glob("Rplots*.pdf"))
# Iterate over the files and delete them if they exist
for (f in file_list_cleanup) {
if (file.exists(f)) {
unlink(f)
}
}
[Package TIMP version 1.13.6 Index]