R/XPSQuantifyGUI.r
In GSperanza/RxpsG_2.3-1: Processing Tool for X-ray Photoelectron Spectroscopy Data
Defines functions
XPSQuant
Documented in
XPSQuant
#Function to perform quantifications on XPS spectra
#allowing selection of corelines and fit components
#for the computation of the atomic concentrations.
#XPSquantify and XPScalc used only by XPSMoveComponent.
#' @title XPSQuant
#' @description XPSQuant() performs the elemental quantification
#' for a selected XPS-Sample. Provides a userfriendly interface
#' with the list of Corelines of the selected XPS-Sample
#' Each Coreline can be count/omit from the elemental quantification.
#' If peak fitting is present also each of the fitting component
#' can be count/omit from the elemental quantification.
#' Finally also relative RSF of the coreline or individual fitting
#' components can be modified.
#' @examples
#' \dontrun{
#' XPSQuant()
#' }
#' @export
#'
XPSQuant <- function(){
#Extract PE from each slot @Info of the XPSSample spectra
RetrivePE <- function(CL=NULL){ #Retrieve the PE value from the CL coreline information slot
PEnergy <- NULL
if(is.null(CL)){
LL <- length(XPSSample)
for(ii in 1:LL){
info <- XPSSample[[ii]]@Info[1] #retrieve info containing PE value
xxx <- unlist(strsplit(info, "Pass energy"))[2] #extract PE value
PEnergy[ii] <- as.integer(gsub("\\D","", xxx)) # extract numeric characters from xxx = PE value
if(is.na(PEnergy[ii])){
txt <- paste("CoreLine ", XPSSample[[ii]]@Symbol, ": \nPass Energy unknown! Please provide the Pass Energy value", sep="")
PEwin <- gwindow("INPUT CORE-LINE PASS ENERGY", parent=c(50, 10), visible=FALSE) #
PEgroup1 <- ggroup(horizontal=FALSE, container=PEwin)
PElabel <- glabel(txt, container=PEgroup1)
font(PElabel) <- list(family="sans", size=12)
CL.PE <- gedit("", initial.msg="CoreLine Pass Energy ", container=PEgroup1)
gseparator(container=PEgroup1)
PEgroup2 <- ggroup(horizontal=TRUE, container=PEgroup1)
gbutton("OK", container=PEgroup2, handler=function(...){ #input spectrum name
PEnergy[ii] <<- as.integer(svalue(CL.PE))
XPSSample[[ii]]@Info[1] <<- paste(XPSSample[[ii]]@Info, " Pass energy ", PEnergy[ii], sep="")
dispose(PEwin)
})
gbutton("Cancel", container=PEgroup2, handler=function(...) dispose(PEwin))
visible(PEwin) <- TRUE
PEwin$set_modal(TRUE)
}
}
} else {
info <- CL@Info[1] #retrieve info containing PE value
xxx <- unlist(strsplit(info, "Pass energy"))[2] #extract PE value
PEnergy <- as.integer(gsub("\\D","", xxx)) # extract numeric characters from xxx = PE value
}
return(PEnergy)
}
CorrectPE <- function(CheckedCL, CK.PassE, SurPE, CLinePE){
idx <- which(CK.PassE == SurPE) #select all the corelines with PE==160. It is supposed that survey cannot be used for quantification. Only CL extracted from survey can be used
LL <- length(idx)
for (ii in 1:LL){
jj <- CheckedCL[idx[ii]]
info <- XPSSample[[jj]]@Info[1] #retrieve info containing PE value
xxx <- strsplit(info, "Pass energy") #extract PE value
PE <- strsplit(xxx[[1]][2], "Iris") #PE value
info <- paste(xxx[[1]][1],"Pass energy ", CLinePE, " Iris", PE[[1]][2], sep="")
XPSSample[[jj]]@Info[1] <<- info
assign(activeFName, XPSSample, envir=.GlobalEnv)
}
}
CalcNormCoeff <- function(CheckedCL, CK.PassE, SurIdx){
# CheckedCL = CoreLines selected for quantification
# CK.PassE = PE of CheckedCL
# SurIdx = index of the survey
# It is supposed that a coreline was extracted from the survey
# For elements extracted from survey at high PE the photoelectron collection efficiency
# is different from that of the corelines with low PE (higher energy resolution)
# Spectra acquired at different PE need a normalization coefficient
# Let us consider C1s extracted from survey(PE=160eV in KratosXPS) and C1s coreline (PE=20eV)
# Different PE leads to markedly different signal intensities.
# Let A1 = area of C1s at PE=160, A2 = area of C1s at PE=20
# It has discovered that a simple normalization for the PE: A1/160, A2/20 does not work
# In htis function a high resolution-Coreline (lower PE) is compared with the same spectrum
# from the survey and a proportion coeff. is computed
# This proportion coeff. is used to normalize Corelines acquired at different PE.
#variables
PassCL <- NULL
BaseLine <- NULL
X <- list()
Y <- list()
Area1 <- Area2 <- Area3 <- NULL
#------
CLinePE <- min(CK.PassE)
txt <- paste("Please Confirm if the Pass Energy of the High-Resolution Core Lines is ", as.character(CLinePE), sep="")
answ <- gconfirm(txt, title="CORE LINE PASS ENERGY", icon="info")
if (answ == FALSE){
winCL <- gwindow("CORE LINE PASS ENERGY", visible=FALSE)
size(winCL) <- c(250, 150)
groupCL <- ggroup(horizontal=FALSE, container=winCL)
labPE <- glabel(text="Please input the Pass Energy of the Core-Lines", container=groupCL)
PassE.CL <- gedit(initial.msg = "PE ?", handler=function(h, ...){
CLinePE <<- as.integer(svalue(PassE.CL))
}, container=groupCL)
gbutton(" OK ", handler=function(h, ...){
dispose(winCL)
}, container=groupCL)
visible(winCL) <- TRUE
winCL$set_modal(TRUE) #nothing can be done while running this macro
}
idx <- which(CK.PassE == CLinePE) #select all the corelines acquired at lower PE
CL.PE <- CheckedCL[idx] #CL.PE contains CL indexes which could be in sparse order
LL <- length(CL.PE)
MaxI <- NULL
#Now find the coreline with max intensity and compare this coreline
#with the same in the survey to compute the normalization factor
for(ii in 1:LL){ #Among the selected corelines finds the one with max intensity
MaxI[ii] <- max(XPSSample[[CL.PE[ii]]]@.Data[[2]]) #find the coreline with max intensity
}
idx <- which(MaxI == max(MaxI)) #index of the coreline with max intensity
idx <- CL.PE[idx] #index of the CL with max internsity and acquired with min PE
if(XPSSample[[SurIdx]]@units[1] != XPSSample[[idx]]@units[1]){
gmessage(msg="WARNING: Wide Spectrum and Core-Lines energy scale units are different. Check please!", title="WARNING", icon="warning")
NormCoeff <<- -1
return()
}
CLName <- XPSSample[[idx]]@Symbol
X[[1]] <- unlist(XPSSample[[idx]]@RegionToFit$x) #resume the abscissa
Y[[1]] <- unlist(XPSSample[[idx]]@RegionToFit$y)
LL <- length(X[[1]])
DY <- (Y[[1]][LL] - Y[[1]][1])/(LL-1) #energy step
for (ii in 1:LL){
BaseLine[ii] <- Y[[1]][1]+(ii-1)*DY #this is the linear baseline
}
# matplot(matrix(c(X[[1]], X[[1]]), ncol=2), matrix(c(Y[[1]], BaseLine), ncol=2), type="l", lty=1, col=c("black","red"))
Y[[1]] <- Y[[1]]-BaseLine
E_stp <- abs(X[[1]][2]-X[[1]][1])
Area1 <- sum(Y[[1]])*E_stp #Area of high resolution coreline
Xlim <- range(X[[1]]) #X range of the selected CL
Xlim <- sort(Xlim, decreasing=FALSE)
Xlim[1] <- Xlim[1]-2 #extend the CL X-range for higher PE (maybe PE=160eV)
Xlim[2] <- Xlim[2]+2 #extend the CL X-range for higher PE
if (XPSSample[[idx]]@Flags[1]==TRUE) {Xlim <- c(Xlim[2], Xlim[1])} #Binding energy scale
idx1 <- findXIndex(XPSSample[[SurIdx]]@.Data[[1]], Xlim[1])
idx2 <- findXIndex(XPSSample[[SurIdx]]@.Data[[1]], Xlim[2])
X[[2]] <- unlist(XPSSample[[SurIdx]]@.Data[[1]][idx1:idx2]) #X values of coreline extracted from survey
Y[[2]] <- unlist(XPSSample[[SurIdx]]@.Data[[2]][idx1:idx2]) #Y values of coreline extracted from survey
Ylim <- range(sapply(Y, sapply, range))
LL <- length(X[[2]])
BaseLine <- NULL
DY <- (Y[[2]][LL] - Y[[2]][1])/(LL-1) #energy step
for (ii in 1:LL){
BaseLine[ii] <- Y[[2]][1]+(ii-1)*DY #this is the linear baseline
}
# matplot(x=matrix(c(X[[2]], X[[2]]), ncol=2), y=matrix(c(Y[[2]], BaseLine), ncol=2), type="l", lty=1, col=c("black","red"))
Y[[2]] <- Y[[2]]-BaseLine
E_stp <- abs(X[[2]][2]-X[[2]][1])
Area2 <- sum(Y[[2]])*E_stp #Area of the coreline extracted from survey
NormCoeff <<- Area2/Area1
X[[3]] <- X[[2]]
Y[[3]] <- Y[[2]]/NormCoeff
Area3 <- sum(Y[[3]])*E_stp
cat("\n => Normalization coefficient: ", round(NormCoeff, 3))
#----- Graphics
if (XPSSample[[SurIdx]]@Flags[[1]]){ #Binding energy set
Xlim <- sort(Xlim, decreasing=TRUE)
} else {
Xlim <- sort(Xlim, decreasing=FALSE)
}
XLabel <- XPSSample[[SurIdx]]@units[1]
YLabel <- XPSSample[[SurIdx]]@units[2]
LL <- max(sapply(X, length))
X <- sapply(X, function(x) {length(x)<-LL #insert NAs if the length of X[] < LL
return(x)})
Y <- sapply(Y, function(x) {length(x)<-LL #insert NAs if the length of Y[] < LL
return(x)})
X <- matrix(unname(unlist(X)), ncol=3) #transform list in matrix
Y <- matrix(unname(unlist(Y)), ncol=3)
txt <- paste("Normalization coeff. computed on ", CLName, sep="")
matplot(x=X, y=Y, xlim=Xlim, type="l", lty=1, lw=1, col=c("black","green","red"), main=txt, xlab=XLabel, ylab=YLabel)
txt <- c("High res. CL", "Extracted CL ", "Normalized CL")
legend(x=Xlim[1], y=Ylim[2]/1.02, legend=txt, text.col=c("black","green","red"))
gmessage(msg="Check the graph: Black and Red spectra should have similar spectral areas", title="Compare HighRes and Normalized Spectra", icon="warning")
SurPE <- RetrivePE(XPSSample[[SurIdx]]) # Retrieve used for the survey
idx <- which(CK.PassE == SurPE)
idx <- CheckedCL[idx] #retrieve the index of the selected corelines having PE=SurPE.
for(ii in idx){
XPSSample[[ii]]@.Data[[2]] <<- XPSSample[[ii]]@.Data[[2]]/NormCoeff
XPSSample[[ii]]@RegionToFit$y <<- XPSSample[[ii]]@RegionToFit$y/NormCoeff
XPSSample[[ii]]@Baseline$y <<- XPSSample[[ii]]@Baseline$y/NormCoeff
XPSSample[[ii]]@RegionToFit$NormCoeff <<- NormCoeff
if(hasComponents(XPSSample[[ii]]) == TRUE) {
XPSSample[[ii]]@Components <<- sapply(XPSSample[[ii]]@Components, function(x) {
x@ycoor <- x@ycoor/NormCoeff
return(x) } )
XPSSample[[ii]]@Fit$y <<- XPSSample[[ii]]@Fit$y/NormCoeff
}
}
CorrectPE(CheckedCL, CK.PassE, SurPE, CLinePE)
return()
}
#XPScalc() function cannot be applied since here you can select fit components and their RSF
quant <- function(CoreLineComp){
N_CL <- length(CoreLineComp)
maxFitComp <- 0
for(ii in 1:length(CoreLineComp)){
LL <- length(CoreLineComp[[ii]])
if (LL > maxFitComp) { maxFitComp <- LL }
}
AreaCL <- rep(0,N_CL)
NormAreaCL <- rep(0,N_CL)
sumComp <- matrix(0,nrow=N_CL,ncol=maxFitComp) #define a zero matrix
AreaComp <- matrix(0,nrow=N_CL,ncol=maxFitComp)
maxNchar <- 0
TabTxt <<- ""
QTabTxt <<- ""
for(ii in 1:N_CL){
AreaCL[ii] <- 0
indx <- CoreLineIndx[ii]
if (svalue(CoreLineCK[[ii]])=="TRUE") { #if a coreline is selected
N_comp <- length(CoreLineComp[[ii]]) #this is the number of fit components
RSF <- XPSSample[[indx]]@RSF #Sensitivity factor of the coreline
E_stp <- abs(XPSSample[[indx]]@.Data[[1]][2]-XPSSample[[indx]]@.Data[[1]][1]) #energy step
if (RSF != 0) { #Sum is made only on components with RSF != 0 (Fit on Auger or VB not considered)
AreaCL[ii] <- sum(XPSSample[[indx]]@RegionToFit$y-XPSSample[[indx]]@Baseline$y)*E_stp #Integral undeer coreline spectrum
NormAreaCL[ii] <- AreaCL[ii]/RSF #Coreline contribution corrected for the relative RSF
} else {
AreaCL[ii] <- sum(XPSSample[[indx]]@RegionToFit$y-XPSSample[[indx]]@Baseline$y)*E_stp #if RSF not defined the integral under the coreline is considered
NormAreaCL[ii] <- AreaCL[ii]
}
txt <- as.character(round(AreaCL[ii], 2))
if (hasComponents(XPSSample[[indx]])) { #is fit present on the coreline?
for(jj in 1:N_comp){ #ii runs on CoreLines, jj runs on coreline fit components
comp <- CoreLineComp[[ii]][jj]
RSF <- XPSSample[[indx]]@Components[[comp]]@rsf
if (RSF!=0) { #if the RSF is lacking(es. Auger, VB spectra...) : it is not possible to make correction for the RSF...
sumComp[ii,jj] <- (sum(XPSSample[[indx]]@Components[[comp]]@ycoor)-sum(XPSSample[[indx]]@Baseline$y))*E_stp #simple area of the coreline
AreaComp[ii,jj] <- sumComp[ii,jj]/RSF #(area of the single component - area backgroound) corrected for the RSF
} else {
sumComp[ii,jj] <- (sum(XPSSample[[indx]]@Components[[comp]]@ycoor)-sum(XPSSample[[indx]]@Baseline$y))*E_stp #if RSF is not defined the simple spectral integral is computed
AreaComp[ii,jj] <- sumComp[ii,jj] #Component spectral integral
}
txt <- as.character(round(sumComp[ii,jj], 2))
Nch <- nchar(txt)
if (Nch > maxNchar) { maxNchar <- Nch } #calculate the max number of characters of numbers describing component areas
}
if (RSF != 0) { #summation only on components with RSF !=0 (no fit on Auger o VB
NormAreaCL[ii] <- sum(AreaComp[ii,])
AreaCL[ii] <- sum(sumComp[ii, ])
}
}
}
}
AreaTot <- sum(NormAreaCL)
sumTot <- sum(AreaCL)
txt <- as.character(round(sumTot, 2)) #print original integral area witout RSF corrections
maxNchar <- max(c(10,nchar(txt)+2))
lgth <- c(10, maxNchar, 8, 8, 8, 9) #width of table columns "Components", "Area", ", FWHM", "BE(eV)", "RSF", "TOT%"
totLgth <- sum(lgth)+1
cat("\n")
txt <- paste(" File Name:", XPSSample@Filename) #Filename
cell <- printCell("label",txt,CellB=" ",totLgth,"left") #call cellprint in modality LABEL alignment LEFT
QTabTxt <<- c(QTabTxt,cell,"\n") #add QTabTxt the information to compose the quant table
TabTxt <<- c(TabTxt,txt,"\n")
txt <- "-" #separator
cell <- printCell("separator", "-","",totLgth,"left") #call cellprint in modality SEPARATOR alignment LEFT
TabTxt <<- c(TabTxt, cell)
QTabTxt <<- c(QTabTxt,"\n")
TabTxt <<- c(TabTxt,"\n")
txt <- c("Components", "Area(cps)", "FWHM", "RSF", "BE(eV)", "TOT.(%)")
cell <- printCell("tableRow", txt, CellB=" ", lgth, "center")
QTabTxt <<- c(QTabTxt,cell,"\n")
TabTxt <<- c(TabTxt,cell,"\n")
cell <- printCell("separator", "-","",totLgth,"left")
TabTxt <<- c(TabTxt, cell)
QTabTxt <<- c(QTabTxt,"\n")
TabTxt <<- c(TabTxt,"\n")
for(ii in 1:N_CL){
indx <- CoreLineIndx[ii]
if (svalue(CoreLineCK[[ii]])=="TRUE") {
#PEAK data
Component <- names(CoreLineComp[ii])
Area <- sprintf("%1.2f", AreaCL[ii]) #round number to 2 decimals and trasform in string
RSF <- sprintf("%1.3f",XPSSample[[indx]]@RSF)
Mpos <- NULL
Mpos <- findMaxPos(XPSSample[[indx]]@RegionToFit) #Mpos[1]==position of spectrum max, Mpos[2]==spectrum max value
BE <- sprintf("%1.3f",Mpos[1])
if (RSF=="0.000") { #RSF not defined (es. Auger, VB spectra...) : cannot make correction for RSF
Conc <- sprintf("%1.2f",0)
} else {
Conc <- sprintf("%1.2f",100*NormAreaCL[ii]/AreaTot)
}
txt <- c(Component, Area, " ", RSF, BE, Conc ) #total concentration relative to the coreline: FWHM e BE not print
cell <- printCell("tableRow", txt, CellB=" ", lgth, "center")
QTabTxt <<- c(QTabTxt,cell,"\n") #this QTabTxt will appear in the Quant widget
cell <- printCell("tableRow", txt, CellB="|", lgth, "center")
TabTxt <<- c(TabTxt,cell,"\n") #this TabTxt will appear in the R consolle
#FIT COMPONENT's data
if (hasComponents(XPSSample[[indx]])) {
N_comp <- length(CoreLineComp[[ii]]) #number of fit components
for(jj in 1:N_comp){ #ii runs on the corelines, jj runs on the fit components
comp <- CoreLineComp[[ii]][jj]
Area <- sprintf("%1.2f",sumComp[ii,jj]) #area of component jj coreline ii
FWHM <- sprintf("%1.2f",XPSSample[[indx]]@Components[[comp]]@param[3,1]) #FWHM component ii
RSF <- sprintf("%1.3f",XPSSample[[indx]]@Components[[comp]]@rsf) #RSF component ii
BE <- sprintf("%1.2f",XPSSample[[indx]]@Components[[comp]]@param[2,1]) #BE component ii
if (RSF=="0.000") {
Conc <- sprintf("%1.2f",0)
} else {
Conc <- sprintf("%1.2f",100*AreaComp[ii,jj]/AreaTot) #Concentration component ii
}
txt <- c(comp, Area, FWHM, RSF, BE, Conc) #make string to print
cell <- printCell("tableRow", txt, CellB=" ", lgth, "center") #print string in modality TABLEROW
QTabTxt <<- c(QTabTxt,cell,"\n")
cell <- printCell("tableRow", txt, CellB="|", lgth, "center") #print string in modality TABLEROW
TabTxt <<- c(TabTxt,cell,"\n")
}
}
QTabTxt <<- c(QTabTxt,"\n")
TabTxt <<- c(TabTxt,"\n")
}
}
Font <- get("XPSSettings", envir=.GlobalEnv)[[1]][1]
FStyle <- get("XPSSettings", envir=.GlobalEnv)[[1]][2]
FSize <- get("XPSSettings", envir=.GlobalEnv)[[1]][3]
# svalue(QTable) <<- capture.output(cat("\n", QTabTxt))
insert(QTable, paste(QTabTxt, collapse=""))
font(QTable) <- list(weight="light", family=Font, style=FStyle, size=FSize)
cat("\n", TabTxt)
}
ResetComp <- function(ii){
indx <- CoreLineIndx[ii]
if (svalue(CoreLineCK[[ii]])=="FALSE") { #if the coreline is not selected the fit component are disabled
if (hasComponents(XPSSample[[indx]])) { #Does the coreline possess fitting components?
svalue(ComponentCK[[ii]]) <- ""
}
names(CoreLineComp)[ii] <<- ""
}
if (svalue(CoreLineCK[[ii]])=="TRUE") { #if the coreline is selected all the fitting components are selected
if (hasComponents(XPSSample[[indx]])) {
svalue(ComponentCK[[ii]]) <- names(XPSSample[[indx]]@Components)
}
names(CoreLineComp)[ii] <<- CoreLineNames[ii] #reset coreline name: it could be dropped if all fitting components are cancelled
}
}
SetRSF <- function(ii){
kk <- 1
for(ii in 1:NCoreLines){
Eq.RSF <- TRUE #Eq.RSF==TRUE means all RSF are equal
indx <- CoreLineIndx[ii]
LL=length(unlist(OrigCoreLinComp[ii])) #the list vectors may have different lengths (different N. Fit components)
if (LL > 0){ #The RSF may be changed then control the RSF of all the fit components
refRSF <- svalue(RSFCK[[kk]]) #set the referenceRSF as the first of the CorelineComponent
if (Eq.RSF == TRUE){ #if all Component RSF are equal set same value also in the Coreline RSF-Slot
XPSSample[[indx]]@RSF <<- as.numeric(refRSF)
}
for(jj in 1:LL){
newRSF <- svalue(RSFCK[[kk]])
if (newRSF != refRSF) { Eq.RSF <- FALSE } #at end of for Eq.RSF==TRUE means all RSF are equal
slot(XPSSample[[indx]]@Components[[jj]], "rsf") <<- as.numeric(newRSF) #load the new RSFR in the relative slot of the XPSSample
kk <- kk+1
}
}
if (LL == 0) {
newRSF <- svalue(RSFCK[[kk]])
XPSSample[[indx]]@RSF <<- as.numeric(newRSF) #load the new RSFR in the relative slot of the XPSSample
kk <- kk+1
}
}
}
CKHandlers <- function(){
for(ii in 1:NCoreLines){
#----HANDLER on Widget-CoreLineCK to call ResetComp()
if ((svalue(CoreLineCK[[ii]]) != CLChecked[ii]) && length(CLChecked[ii])>0) {
CLChecked[ii] <<- svalue(CoreLineCK[[ii]])
ResetComp(ii) #set/reset fit components
}
#----HANDLER on Widget-ComponentCK
tmp1 <- svalue(ComponentCK[[ii]])
tmp2 <- unlist(CoreLineComp[[ii]])
if(svalue(CoreLineCK[[ii]])==FALSE && is.null(tmp2)==TRUE) { #Coreline has only baseline is un-selected
tmp1 <- ""
tmp2 <- ""
svalue(CoreLineCK[[ii]]) <- FALSE
} else if(length(tmp1)==0 && length(tmp2)>0) { #Coreline with fit is un-selected
tmp1 <- ""
svalue(CoreLineCK[[ii]]) <- FALSE
CLChecked[ii] <<- FALSE
} else {
svalue(CoreLineCK[[ii]]) <- TRUE
CLChecked[ii] <<- TRUE
}
if(is.null(tmp2)=="TRUE") {
tmp2 <- ""
} # the correspondent coreline does NOT possess fitting components but only the BaseLine
if (all(tmp1==tmp2)==FALSE) { #if the two vector contain different elements
CoreLineComp[ii] <<- list(tmp1) #modify component [ii] of the list following the checkbox component selections
if (nchar(tmp1)==0) {
names(CoreLineComp)[ii] <<- ""
CLChecked[ii] <<- ""
}
if (nchar(tmp1) > 0) {
CoreLineComp <<- setNames(CoreLineComp, CoreLineNames)
}
}
}
}
#----MakeNb makes the notebook: a coreline for each notebook page
MakeNb <- function(){
kk <- 1
# CoreLineCK <- list() #define a list of Gwidget
# ComponentCK <- list()
# RSFCK <- list()
for(ii in 1:NCoreLines){
Qgroup[[ii]] <<- ggroup(label=CoreLineNames[ii], horizontal=TRUE, container=Qnb)
Qlayout[[ii]] <<- glayout(homogeneous=FALSE, spacing=3, container=Qgroup[[ii]])
NoComp <- "FALSE"
indx <- CoreLineIndx[ii]
tmp <- names(XPSSample[[indx]]@Components)
if (is.null(tmp)) { NoComp <- "TRUE" }
LL <- length(tmp) # the vector of the list may have different length (different N FitComp)
CoreLineComp <<- c(CoreLineComp, list(tmp)) #create a list containing the fit components of corelines
txt <- paste("CORE LINE", ii , sep="")
Qlayout[[ii]][1,1] <<- CLframe[[ii]] <<- gframe(text=txt, horizontal=FALSE, spacing=5, container=Qlayout[[ii]])
CoreLineCK[[ii]] <<- gcheckbox(CoreLineNames[ii], checked=CLChecked[ii], handler=function(h, ...){
ii <- svalue(Qnb) #set the ii value to the active notebook page
CKHandlers()
}, container=CLframe[[ii]]) #here CoreLineName is an array
Qlayout[[ii]][1,2] <<- CMPframe[[ii]] <- gframe(text="COMPONENTS", horizontal=FALSE, spacing=5, container=Qlayout[[ii]])
ComponentCK[[ii]] <<- gcheckboxgroup(unlist(CoreLineComp[ii]), checked=TRUE, handler=function(h,...){
ii <- svalue(Qnb) #set the ii value to the active notebook page
CKHandlers()
}, container=CMPframe[[ii]]) #here CoreLineName is an array
Qlayout[[ii]][1,3] <<- RSFframe[[ii]] <- gframe(text="RSF", horizontal=FALSE, spacing=5, container=Qlayout[[ii]])
if ( NoComp=="TRUE"){
ComponentCK[[ii]] <<- "" #NO fitting components only baseline
OldRSF <<- XPSSample[[indx]]@RSF
RSFCK[[kk]] <<- gedit(text=OldRSF, handler=NULL, container=RSFframe[[ii]])
kk <- kk+1
} else {
for(jj in 1:LL){
OldRSF <<- XPSSample[[indx]]@Components[[jj]]@rsf
RSFCK[[kk]] <<- gedit(text=OldRSF, handler=NULL, container=RSFframe[[ii]])
kk <- kk+1
}
}
}
CoreLineComp <<- setNames(CoreLineComp, CoreLineNames) #the list contains the names of the corelines and relative FitComponents
OrigCoreLinComp <<- CoreLineComp
ii <- NCoreLines+1
Qgroup[[ii]] <<- ggroup(label=" QUANTIFY ", horizontal=FALSE, container=Qnb)
Qlayout[[ii]] <<- glayout(homogeneous=FALSE, spacing=3, container=Qgroup[[ii]])
Qlayout[[ii]][1,1] <<- gbutton(" QUANTIFY ", handler=function(h,...){ #glayout is generated in MakeNB()
SetRSF()
#extract indexes of CoreLines selected for quantification
CheckedCL <- names(CoreLineComp)
CheckedCL <- CheckedCL[which(CheckedCL !="")]
CheckedCL <- sapply(CheckedCL, function(x) { x <- unlist(strsplit(x, "\\."))
x <- unname(x)
return(x)
})
CheckedCL <- as.integer(CheckedCL[1,])
#Control on the Pass Energies
CK.PassE <- PassE[CheckedCL] #extracts PE valued corresponding to the elements selected for quantification
idx <- unname(which(CK.PassE != CK.PassE[1])) #are the selected elements acquired at different PE?
is.NC <- TRUE #logic, TRUE if NormCoeff is already computed
idx <- CheckedCL[idx] #now idx correctly indicates the corelines
for(ii in idx){
if(length(XPSSample[[ii]]@RegionToFit) < 3){
is.NC <- FALSE} #NormCoeff not saved in ...RegionToFit@NormCoeff
}
if (length(idx) > 0 && is.NC == FALSE) { #selected elements are acquired at different PE and NormCoeff not computed
answ <- gconfirm(" Found spectra acquired at different Pass Energies. \n Do you want to quantify spectra EXTRACTED FROM SURVEY ?",
title="NORMALIZATION COEFFICIENT", icon="warning")
if (answ == TRUE){
#Control how many Survey spectra in XPSSample
SurIdx <<- grep("Survey", SpectList) #indexes of the names components == "Survey"
if (length(SurIdx) == 0) {
SurIdx <<- grep("survey", SpectList)
}
N_Survey <- length(SurIdx)
if (N_Survey > 1) {
txt <- paste(" Found ", N_Survey, " in the XPSSample ", activeFName, ": \n select the Survey used to extract the Core Lines", sep="")
gmessage(txt, title="SELECT SURVEY", icon="warning")
winCL <- gwindow("SELECT SURVEY", visible=FALSE)
size(winCL) <- c(250, 150)
groupCL <- ggroup(horizontal=FALSE, container=winCL)
CL_Names <- SpectList[SurIdx]
selectSur <- gradio(CL_Names, selected=1, horizontal=TRUE, container=groupCL)
gbutton(" OK ", handler=function(h, ...){
SurIdx <<- svalue(selectSur)
SurIdx <<- unlist(strsplit(SurIdx, "\\.")) #drop "NUMBER." at beginning of coreLine name
SurIdx <<- as.integer(SurIdx[1])
dispose(winCL)
}, container=groupCL)
visible(winCL) <- TRUE
winCL$set_modal(TRUE) #nothing can be done while running this macro
}
cat("\n => Compute the normalization coefficient")
CalcNormCoeff(CheckedCL, CK.PassE, SurIdx)
if(NormCoeff == -1){ #Found wide spectrum and corelines acquired using different energy units.
return()
}
} else {
gmessage("Spectra acquired at different PE cannot be used for quantification", title="QUANTIFICATION NOT ALLOWED", icon="warning")
return()
}
}
quant(CoreLineComp)
}, container = Qlayout[[ii]])
Qlayout[[ii]][1,2] <<- gbutton(" WRITE TO FILE ", handler=function(h,...){
Filename <- unlist(strsplit(QTabTxt[2], ":"))[2]
Filename <- unlist(strsplit(Filename, "\\."))[1]
Filename <- paste(Filename, "txt", sep="")
PathFile <- gfile(text = "", type = "save", initial.filename = "Filename", initial.dir = getwd())
NL <- length(QTabTxt)
if (is.null(PathFile)) {
gmessage(msg="File Name not defined. Please give the file name", title="NO FILENAME", icon="error")
return()
}
OutFile <- file(PathFile, open="wt")
for (ii in 1:NL){
writeLines(QTabTxt[ii], sep="", OutFile)
}
close(OutFile)
}, container = Qlayout[[ii]])
QTable <<- gtext(text="", wrap=FALSE, container = Qgroup[[ii]])
size(QTable) <<- c(550, 370)
svalue(QTable) <- ""
for (ii in (NCoreLines+1):1){
svalue(Qnb) <<- ii #refresh all pages until from the last to the first
}
return(CoreLineComp)
}
#----Reset vars resets variables to initial values
ResetVars <- function(){
XPSSample <<- get(activeFName, envir = .GlobalEnv) #load the active XPSSample dataFrame
XPSSampleList <<- XPSFNameList() #list of all XPSSamples
XPSSampleIdx <<- grep(activeFName,XPSSampleList)
SpectList <<- XPSSpectList(activeFName) #list of all CoreLines of the active XPSSample
PassE <<- RetrivePE() # Retrieve list of CoreLine Pass Energies
NormCoeff <<- 1
CoreLineNames <<- ""
CoreLineIndx <<- NULL
FitComp <<- ""
NComp <<- NULL
CoreLineComp <<- list()
OrigCoreLinComp <<- list()
CompChecked <<- NULL
CoreLineCK <<- list() #define a list of the selected CL for quantification
ComponentCK <<- list() #define the CL fit components selected CL for quantification
RSFCKv <- list()
Qgroup <<- list()
Qlayout <<- list()
CLframe <<- list()
CMPframe <<- list()
RSFframev <<- list()
QTable <<- list()
NCoreLines <<- length(SpectList)
NoFitFoundv <<- 0
NmaxFitCompv <<- 0
QTabTxt <<- "" #text containing Quantification results for the Qtable gtext()
TabTxt <<- "" #text containing Quantification results for the RStudio consolle
RegionToFit <- 0
jj <- 1
for(ii in 1:NCoreLines){
if (length(XPSSample[[ii]]@RegionToFit) > 0){ #a Baseline is defined
RegionToFit <- 1
CoreLineNames[jj] <<- SpectList[ii] #Save the coreline name where a baseline is defined
CoreLineIndx[jj] <<- ii #vector containing indexes of the corelines where a baseline is defined
jj <- jj+1
NFC <- length(XPSSample[[ii]]@Components)
if (NFC > NmaxFitComp) {NmaxFitComp <<- NFC}
}
}
if (RegionToFit == 0){
gmessage(msg="WARNING: NO FIT REGIONS DEFINED ON THIS XPS SAMPLE", title = "WARNING", icon = "warning")
return()
}
NCoreLines <<- length(CoreLineIndx) #now only the corelines with baseline are considered for the quantification
CLChecked <<- rep("TRUE",NCoreLines)
}
#---- variables ----
if (is.na(activeFName)){
gmessage("No data present: please load and XPS Sample", title="XPS SAMPLES MISSING", icon="error")
return()
}
XPSSample <- NULL
XPSSample <- get(activeFName, envir = .GlobalEnv) #load the active XPSSample
XPSSampleList <- XPSFNameList() #list of all XPSSamples
XPSSampleIdx <- grep(activeFName,XPSSampleList)
SpectList <- XPSSpectList(activeFName) #list of all the corelines of the active XPSSample
PassE <- RetrivePE() # Retrieve list of CoreLine Pass Energies
names(PassE) <- SpectList
NormCoeff <<- 1
CoreLineNames <- ""
CoreLineIndx <- NULL
FitComp <- ""
NComp <- NULL
CoreLineComp <- list()
OrigCoreLinComp <- list()
CompChecked <- NULL
CoreLineCK <- list() #define a list of the Gwidgets
ComponentCK <- list()
RSFCK <- list()
Qgroup <- list()
Qlayout <- list()
CLframe <- list()
CMPframe <- list()
RSFframe <- list()
QTable <- list()
NCoreLines <- length(SpectList)
NoFitFound <- 0
NmaxFitComp <- 0
QTabTxt <- "" #text containing Quantification results for the Qtable gtext()
TabTxt <- "" #text containing Quantification results for the RStudio consolle
RegionToFit <- 0
jj <- 1
for(ii in 1:NCoreLines){
if (length(XPSSample[[ii]]@RegionToFit) > 0){ #a baseline is defined
RegionToFit <- 1
CoreLineNames[jj] <- SpectList[ii] #Save the coreline name where a baseline is defined
CoreLineIndx[jj] <- ii #vector containing indexes of the corelines where a baseline is defined
jj <- jj+1
NFC <- length(XPSSample[[ii]]@Components)
if (NFC > NmaxFitComp) {NmaxFitComp <- NFC}
}
}
if (RegionToFit == 0){
gmessage(msg="WARNING: NO FIT REGIONS DEFINED ON THIS XPS SAMPLE", title = "WARNING", icon = "warning")
return()
}
NCoreLines <- length(CoreLineIndx) #now only the corelines with baseline are considered for the quantification
CLChecked <- rep("TRUE",NCoreLines)
#===== GUI =====
Qwin <- gwindow(" QUANTIFICATION FUNCTION ", visible=FALSE)
size(Qwin) <- c(280, 530)
QmainGroup <- ggroup(horizontal=FALSE, container=Qwin)
Qgrp0 <- ggroup(horizontal= TRUE, spacing=2, container=QmainGroup)
glabel(text="XPSSample", container=Qgrp0)
SelXPSData <- gcombobox(XPSSampleList, width=15, selected=XPSSampleIdx, handler=function(h, ...){
activeFName <<- svalue(SelXPSData)
ResetVars()
assign("activeSpectIndx", 1, envir=.GlobalEnv)
assign("activeSpectName", SpectList[1], envir=.GlobalEnv)
delete(Qframe1,Qnb)
Qnb <<- gnotebook(expand=TRUE, container = Qframe1)
add(Qframe1,Qnb)
CoreLineComp <<- MakeNb()
plot(XPSSample)
}, container=Qgrp0)
QReset <- gbutton(" RESET ", handler=function(h,...){
ResetVars()
delete(Qframe1,Qnb)
Qnb <<- gnotebook(expand=TRUE, container = Qframe1)
add(Qframe1,Qnb)
CoreLineComp <<- MakeNb()
plot(XPSSample)
}, container = Qgrp0)
QSave <- gbutton(" SAVE ", handler=function(h,...){
SetRSF()
assign(activeFName, XPSSample, .GlobalEnv) #save the fit parameters in the activeSample
XPSSaveRetrieveBkp("save")
}, container = Qgrp0)
QSaveExit <- gbutton(" SAVE & EXIT ", handler=function(h,...){
SetRSF()
assign(activeFName, XPSSample, .GlobalEnv) #save the fit parameters in the activeSample
dispose(Qwin)
XPSSaveRetrieveBkp("save")
}, container = Qgrp0)
Qframe1 <- gframe(text="Core Lines", spacing=5,horizontal=FALSE, container=QmainGroup)
Qnb <- gnotebook(expand=TRUE, container = Qframe1)
CoreLineComp <- MakeNb()
CoreLineComp <- setNames(CoreLineComp, CoreLineNames) #the list contains the names of the coreline and the relative FitComponents
OrigCoreLinComp <- CoreLineComp
visible(Qwin) <- TRUE
for(ii in (NCoreLines+1):1){ #reset nb pages from the last to the first
svalue(Qnb) <- ii
}
Qwin$set_modal(TRUE)
}
GSperanza/RxpsG_2.3-1 documentation built on Feb. 11, 2024, 5:09 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions XPSQuant
Documented in XPSQuant
#Function to perform quantifications on XPS spectra
#allowing selection of corelines and fit components
#for the computation of the atomic concentrations.
#XPSquantify and XPScalc used only by XPSMoveComponent.
#' @title XPSQuant
#' @description XPSQuant() performs the elemental quantification
#' for a selected XPS-Sample. Provides a userfriendly interface
#' with the list of Corelines of the selected XPS-Sample
#' Each Coreline can be count/omit from the elemental quantification.
#' If peak fitting is present also each of the fitting component
#' can be count/omit from the elemental quantification.
#' Finally also relative RSF of the coreline or individual fitting
#' components can be modified.
#' @examples
#' \dontrun{
#' XPSQuant()
#' }
#' @export
#'
XPSQuant <- function(){
#Extract PE from each slot @Info of the XPSSample spectra
RetrivePE <- function(CL=NULL){ #Retrieve the PE value from the CL coreline information slot
PEnergy <- NULL
if(is.null(CL)){
LL <- length(XPSSample)
for(ii in 1:LL){
info <- XPSSample[[ii]]@Info[1] #retrieve info containing PE value
xxx <- unlist(strsplit(info, "Pass energy"))[2] #extract PE value
PEnergy[ii] <- as.integer(gsub("\\D","", xxx)) # extract numeric characters from xxx = PE value
if(is.na(PEnergy[ii])){
txt <- paste("CoreLine ", XPSSample[[ii]]@Symbol, ": \nPass Energy unknown! Please provide the Pass Energy value", sep="")
PEwin <- gwindow("INPUT CORE-LINE PASS ENERGY", parent=c(50, 10), visible=FALSE) #
PEgroup1 <- ggroup(horizontal=FALSE, container=PEwin)
PElabel <- glabel(txt, container=PEgroup1)
font(PElabel) <- list(family="sans", size=12)
CL.PE <- gedit("", initial.msg="CoreLine Pass Energy ", container=PEgroup1)
gseparator(container=PEgroup1)
PEgroup2 <- ggroup(horizontal=TRUE, container=PEgroup1)
gbutton("OK", container=PEgroup2, handler=function(...){ #input spectrum name
PEnergy[ii] <<- as.integer(svalue(CL.PE))
XPSSample[[ii]]@Info[1] <<- paste(XPSSample[[ii]]@Info, " Pass energy ", PEnergy[ii], sep="")
dispose(PEwin)
})
gbutton("Cancel", container=PEgroup2, handler=function(...) dispose(PEwin))
visible(PEwin) <- TRUE
PEwin$set_modal(TRUE)
}
}
} else {
info <- CL@Info[1] #retrieve info containing PE value
xxx <- unlist(strsplit(info, "Pass energy"))[2] #extract PE value
PEnergy <- as.integer(gsub("\\D","", xxx)) # extract numeric characters from xxx = PE value
}
return(PEnergy)
}
CorrectPE <- function(CheckedCL, CK.PassE, SurPE, CLinePE){
idx <- which(CK.PassE == SurPE) #select all the corelines with PE==160. It is supposed that survey cannot be used for quantification. Only CL extracted from survey can be used
LL <- length(idx)
for (ii in 1:LL){
jj <- CheckedCL[idx[ii]]
info <- XPSSample[[jj]]@Info[1] #retrieve info containing PE value
xxx <- strsplit(info, "Pass energy") #extract PE value
PE <- strsplit(xxx[[1]][2], "Iris") #PE value
info <- paste(xxx[[1]][1],"Pass energy ", CLinePE, " Iris", PE[[1]][2], sep="")
XPSSample[[jj]]@Info[1] <<- info
assign(activeFName, XPSSample, envir=.GlobalEnv)
}
}
CalcNormCoeff <- function(CheckedCL, CK.PassE, SurIdx){
# CheckedCL = CoreLines selected for quantification
# CK.PassE = PE of CheckedCL
# SurIdx = index of the survey
# It is supposed that a coreline was extracted from the survey
# For elements extracted from survey at high PE the photoelectron collection efficiency
# is different from that of the corelines with low PE (higher energy resolution)
# Spectra acquired at different PE need a normalization coefficient
# Let us consider C1s extracted from survey(PE=160eV in KratosXPS) and C1s coreline (PE=20eV)
# Different PE leads to markedly different signal intensities.
# Let A1 = area of C1s at PE=160, A2 = area of C1s at PE=20
# It has discovered that a simple normalization for the PE: A1/160, A2/20 does not work
# In htis function a high resolution-Coreline (lower PE) is compared with the same spectrum
# from the survey and a proportion coeff. is computed
# This proportion coeff. is used to normalize Corelines acquired at different PE.
#variables
PassCL <- NULL
BaseLine <- NULL
X <- list()
Y <- list()
Area1 <- Area2 <- Area3 <- NULL
#------
CLinePE <- min(CK.PassE)
txt <- paste("Please Confirm if the Pass Energy of the High-Resolution Core Lines is ", as.character(CLinePE), sep="")
answ <- gconfirm(txt, title="CORE LINE PASS ENERGY", icon="info")
if (answ == FALSE){
winCL <- gwindow("CORE LINE PASS ENERGY", visible=FALSE)
size(winCL) <- c(250, 150)
groupCL <- ggroup(horizontal=FALSE, container=winCL)
labPE <- glabel(text="Please input the Pass Energy of the Core-Lines", container=groupCL)
PassE.CL <- gedit(initial.msg = "PE ?", handler=function(h, ...){
CLinePE <<- as.integer(svalue(PassE.CL))
}, container=groupCL)
gbutton(" OK ", handler=function(h, ...){
dispose(winCL)
}, container=groupCL)
visible(winCL) <- TRUE
winCL$set_modal(TRUE) #nothing can be done while running this macro
}
idx <- which(CK.PassE == CLinePE) #select all the corelines acquired at lower PE
CL.PE <- CheckedCL[idx] #CL.PE contains CL indexes which could be in sparse order
LL <- length(CL.PE)
MaxI <- NULL
#Now find the coreline with max intensity and compare this coreline
#with the same in the survey to compute the normalization factor
for(ii in 1:LL){ #Among the selected corelines finds the one with max intensity
MaxI[ii] <- max(XPSSample[[CL.PE[ii]]]@.Data[[2]]) #find the coreline with max intensity
}
idx <- which(MaxI == max(MaxI)) #index of the coreline with max intensity
idx <- CL.PE[idx] #index of the CL with max internsity and acquired with min PE
if(XPSSample[[SurIdx]]@units[1] != XPSSample[[idx]]@units[1]){
gmessage(msg="WARNING: Wide Spectrum and Core-Lines energy scale units are different. Check please!", title="WARNING", icon="warning")
NormCoeff <<- -1
return()
}
CLName <- XPSSample[[idx]]@Symbol
X[[1]] <- unlist(XPSSample[[idx]]@RegionToFit$x) #resume the abscissa
Y[[1]] <- unlist(XPSSample[[idx]]@RegionToFit$y)
LL <- length(X[[1]])
DY <- (Y[[1]][LL] - Y[[1]][1])/(LL-1) #energy step
for (ii in 1:LL){
BaseLine[ii] <- Y[[1]][1]+(ii-1)*DY #this is the linear baseline
}
# matplot(matrix(c(X[[1]], X[[1]]), ncol=2), matrix(c(Y[[1]], BaseLine), ncol=2), type="l", lty=1, col=c("black","red"))
Y[[1]] <- Y[[1]]-BaseLine
E_stp <- abs(X[[1]][2]-X[[1]][1])
Area1 <- sum(Y[[1]])*E_stp #Area of high resolution coreline
Xlim <- range(X[[1]]) #X range of the selected CL
Xlim <- sort(Xlim, decreasing=FALSE)
Xlim[1] <- Xlim[1]-2 #extend the CL X-range for higher PE (maybe PE=160eV)
Xlim[2] <- Xlim[2]+2 #extend the CL X-range for higher PE
if (XPSSample[[idx]]@Flags[1]==TRUE) {Xlim <- c(Xlim[2], Xlim[1])} #Binding energy scale
idx1 <- findXIndex(XPSSample[[SurIdx]]@.Data[[1]], Xlim[1])
idx2 <- findXIndex(XPSSample[[SurIdx]]@.Data[[1]], Xlim[2])
X[[2]] <- unlist(XPSSample[[SurIdx]]@.Data[[1]][idx1:idx2]) #X values of coreline extracted from survey
Y[[2]] <- unlist(XPSSample[[SurIdx]]@.Data[[2]][idx1:idx2]) #Y values of coreline extracted from survey
Ylim <- range(sapply(Y, sapply, range))
LL <- length(X[[2]])
BaseLine <- NULL
DY <- (Y[[2]][LL] - Y[[2]][1])/(LL-1) #energy step
for (ii in 1:LL){
BaseLine[ii] <- Y[[2]][1]+(ii-1)*DY #this is the linear baseline
}
# matplot(x=matrix(c(X[[2]], X[[2]]), ncol=2), y=matrix(c(Y[[2]], BaseLine), ncol=2), type="l", lty=1, col=c("black","red"))
Y[[2]] <- Y[[2]]-BaseLine
E_stp <- abs(X[[2]][2]-X[[2]][1])
Area2 <- sum(Y[[2]])*E_stp #Area of the coreline extracted from survey
NormCoeff <<- Area2/Area1
X[[3]] <- X[[2]]
Y[[3]] <- Y[[2]]/NormCoeff
Area3 <- sum(Y[[3]])*E_stp
cat("\n => Normalization coefficient: ", round(NormCoeff, 3))
#----- Graphics
if (XPSSample[[SurIdx]]@Flags[[1]]){ #Binding energy set
Xlim <- sort(Xlim, decreasing=TRUE)
} else {
Xlim <- sort(Xlim, decreasing=FALSE)
}
XLabel <- XPSSample[[SurIdx]]@units[1]
YLabel <- XPSSample[[SurIdx]]@units[2]
LL <- max(sapply(X, length))
X <- sapply(X, function(x) {length(x)<-LL #insert NAs if the length of X[] < LL
return(x)})
Y <- sapply(Y, function(x) {length(x)<-LL #insert NAs if the length of Y[] < LL
return(x)})
X <- matrix(unname(unlist(X)), ncol=3) #transform list in matrix
Y <- matrix(unname(unlist(Y)), ncol=3)
txt <- paste("Normalization coeff. computed on ", CLName, sep="")
matplot(x=X, y=Y, xlim=Xlim, type="l", lty=1, lw=1, col=c("black","green","red"), main=txt, xlab=XLabel, ylab=YLabel)
txt <- c("High res. CL", "Extracted CL ", "Normalized CL")
legend(x=Xlim[1], y=Ylim[2]/1.02, legend=txt, text.col=c("black","green","red"))
gmessage(msg="Check the graph: Black and Red spectra should have similar spectral areas", title="Compare HighRes and Normalized Spectra", icon="warning")
SurPE <- RetrivePE(XPSSample[[SurIdx]]) # Retrieve used for the survey
idx <- which(CK.PassE == SurPE)
idx <- CheckedCL[idx] #retrieve the index of the selected corelines having PE=SurPE.
for(ii in idx){
XPSSample[[ii]]@.Data[[2]] <<- XPSSample[[ii]]@.Data[[2]]/NormCoeff
XPSSample[[ii]]@RegionToFit$y <<- XPSSample[[ii]]@RegionToFit$y/NormCoeff
XPSSample[[ii]]@Baseline$y <<- XPSSample[[ii]]@Baseline$y/NormCoeff
XPSSample[[ii]]@RegionToFit$NormCoeff <<- NormCoeff
if(hasComponents(XPSSample[[ii]]) == TRUE) {
XPSSample[[ii]]@Components <<- sapply(XPSSample[[ii]]@Components, function(x) {
x@ycoor <- x@ycoor/NormCoeff
return(x) } )
XPSSample[[ii]]@Fit$y <<- XPSSample[[ii]]@Fit$y/NormCoeff
}
}
CorrectPE(CheckedCL, CK.PassE, SurPE, CLinePE)
return()
}
#XPScalc() function cannot be applied since here you can select fit components and their RSF
quant <- function(CoreLineComp){
N_CL <- length(CoreLineComp)
maxFitComp <- 0
for(ii in 1:length(CoreLineComp)){
LL <- length(CoreLineComp[[ii]])
if (LL > maxFitComp) { maxFitComp <- LL }
}
AreaCL <- rep(0,N_CL)
NormAreaCL <- rep(0,N_CL)
sumComp <- matrix(0,nrow=N_CL,ncol=maxFitComp) #define a zero matrix
AreaComp <- matrix(0,nrow=N_CL,ncol=maxFitComp)
maxNchar <- 0
TabTxt <<- ""
QTabTxt <<- ""
for(ii in 1:N_CL){
AreaCL[ii] <- 0
indx <- CoreLineIndx[ii]
if (svalue(CoreLineCK[[ii]])=="TRUE") { #if a coreline is selected
N_comp <- length(CoreLineComp[[ii]]) #this is the number of fit components
RSF <- XPSSample[[indx]]@RSF #Sensitivity factor of the coreline
E_stp <- abs(XPSSample[[indx]]@.Data[[1]][2]-XPSSample[[indx]]@.Data[[1]][1]) #energy step
if (RSF != 0) { #Sum is made only on components with RSF != 0 (Fit on Auger or VB not considered)
AreaCL[ii] <- sum(XPSSample[[indx]]@RegionToFit$y-XPSSample[[indx]]@Baseline$y)*E_stp #Integral undeer coreline spectrum
NormAreaCL[ii] <- AreaCL[ii]/RSF #Coreline contribution corrected for the relative RSF
} else {
AreaCL[ii] <- sum(XPSSample[[indx]]@RegionToFit$y-XPSSample[[indx]]@Baseline$y)*E_stp #if RSF not defined the integral under the coreline is considered
NormAreaCL[ii] <- AreaCL[ii]
}
txt <- as.character(round(AreaCL[ii], 2))
if (hasComponents(XPSSample[[indx]])) { #is fit present on the coreline?
for(jj in 1:N_comp){ #ii runs on CoreLines, jj runs on coreline fit components
comp <- CoreLineComp[[ii]][jj]
RSF <- XPSSample[[indx]]@Components[[comp]]@rsf
if (RSF!=0) { #if the RSF is lacking(es. Auger, VB spectra...) : it is not possible to make correction for the RSF...
sumComp[ii,jj] <- (sum(XPSSample[[indx]]@Components[[comp]]@ycoor)-sum(XPSSample[[indx]]@Baseline$y))*E_stp #simple area of the coreline
AreaComp[ii,jj] <- sumComp[ii,jj]/RSF #(area of the single component - area backgroound) corrected for the RSF
} else {
sumComp[ii,jj] <- (sum(XPSSample[[indx]]@Components[[comp]]@ycoor)-sum(XPSSample[[indx]]@Baseline$y))*E_stp #if RSF is not defined the simple spectral integral is computed
AreaComp[ii,jj] <- sumComp[ii,jj] #Component spectral integral
}
txt <- as.character(round(sumComp[ii,jj], 2))
Nch <- nchar(txt)
if (Nch > maxNchar) { maxNchar <- Nch } #calculate the max number of characters of numbers describing component areas
}
if (RSF != 0) { #summation only on components with RSF !=0 (no fit on Auger o VB
NormAreaCL[ii] <- sum(AreaComp[ii,])
AreaCL[ii] <- sum(sumComp[ii, ])
}
}
}
}
AreaTot <- sum(NormAreaCL)
sumTot <- sum(AreaCL)
txt <- as.character(round(sumTot, 2)) #print original integral area witout RSF corrections
maxNchar <- max(c(10,nchar(txt)+2))
lgth <- c(10, maxNchar, 8, 8, 8, 9) #width of table columns "Components", "Area", ", FWHM", "BE(eV)", "RSF", "TOT%"
totLgth <- sum(lgth)+1
cat("\n")
txt <- paste(" File Name:", XPSSample@Filename) #Filename
cell <- printCell("label",txt,CellB=" ",totLgth,"left") #call cellprint in modality LABEL alignment LEFT
QTabTxt <<- c(QTabTxt,cell,"\n") #add QTabTxt the information to compose the quant table
TabTxt <<- c(TabTxt,txt,"\n")
txt <- "-" #separator
cell <- printCell("separator", "-","",totLgth,"left") #call cellprint in modality SEPARATOR alignment LEFT
TabTxt <<- c(TabTxt, cell)
QTabTxt <<- c(QTabTxt,"\n")
TabTxt <<- c(TabTxt,"\n")
txt <- c("Components", "Area(cps)", "FWHM", "RSF", "BE(eV)", "TOT.(%)")
cell <- printCell("tableRow", txt, CellB=" ", lgth, "center")
QTabTxt <<- c(QTabTxt,cell,"\n")
TabTxt <<- c(TabTxt,cell,"\n")
cell <- printCell("separator", "-","",totLgth,"left")
TabTxt <<- c(TabTxt, cell)
QTabTxt <<- c(QTabTxt,"\n")
TabTxt <<- c(TabTxt,"\n")
for(ii in 1:N_CL){
indx <- CoreLineIndx[ii]
if (svalue(CoreLineCK[[ii]])=="TRUE") {
#PEAK data
Component <- names(CoreLineComp[ii])
Area <- sprintf("%1.2f", AreaCL[ii]) #round number to 2 decimals and trasform in string
RSF <- sprintf("%1.3f",XPSSample[[indx]]@RSF)
Mpos <- NULL
Mpos <- findMaxPos(XPSSample[[indx]]@RegionToFit) #Mpos[1]==position of spectrum max, Mpos[2]==spectrum max value
BE <- sprintf("%1.3f",Mpos[1])
if (RSF=="0.000") { #RSF not defined (es. Auger, VB spectra...) : cannot make correction for RSF
Conc <- sprintf("%1.2f",0)
} else {
Conc <- sprintf("%1.2f",100*NormAreaCL[ii]/AreaTot)
}
txt <- c(Component, Area, " ", RSF, BE, Conc ) #total concentration relative to the coreline: FWHM e BE not print
cell <- printCell("tableRow", txt, CellB=" ", lgth, "center")
QTabTxt <<- c(QTabTxt,cell,"\n") #this QTabTxt will appear in the Quant widget
cell <- printCell("tableRow", txt, CellB="|", lgth, "center")
TabTxt <<- c(TabTxt,cell,"\n") #this TabTxt will appear in the R consolle
#FIT COMPONENT's data
if (hasComponents(XPSSample[[indx]])) {
N_comp <- length(CoreLineComp[[ii]]) #number of fit components
for(jj in 1:N_comp){ #ii runs on the corelines, jj runs on the fit components
comp <- CoreLineComp[[ii]][jj]
Area <- sprintf("%1.2f",sumComp[ii,jj]) #area of component jj coreline ii
FWHM <- sprintf("%1.2f",XPSSample[[indx]]@Components[[comp]]@param[3,1]) #FWHM component ii
RSF <- sprintf("%1.3f",XPSSample[[indx]]@Components[[comp]]@rsf) #RSF component ii
BE <- sprintf("%1.2f",XPSSample[[indx]]@Components[[comp]]@param[2,1]) #BE component ii
if (RSF=="0.000") {
Conc <- sprintf("%1.2f",0)
} else {
Conc <- sprintf("%1.2f",100*AreaComp[ii,jj]/AreaTot) #Concentration component ii
}
txt <- c(comp, Area, FWHM, RSF, BE, Conc) #make string to print
cell <- printCell("tableRow", txt, CellB=" ", lgth, "center") #print string in modality TABLEROW
QTabTxt <<- c(QTabTxt,cell,"\n")
cell <- printCell("tableRow", txt, CellB="|", lgth, "center") #print string in modality TABLEROW
TabTxt <<- c(TabTxt,cell,"\n")
}
}
QTabTxt <<- c(QTabTxt,"\n")
TabTxt <<- c(TabTxt,"\n")
}
}
Font <- get("XPSSettings", envir=.GlobalEnv)[[1]][1]
FStyle <- get("XPSSettings", envir=.GlobalEnv)[[1]][2]
FSize <- get("XPSSettings", envir=.GlobalEnv)[[1]][3]
# svalue(QTable) <<- capture.output(cat("\n", QTabTxt))
insert(QTable, paste(QTabTxt, collapse=""))
font(QTable) <- list(weight="light", family=Font, style=FStyle, size=FSize)
cat("\n", TabTxt)
}
ResetComp <- function(ii){
indx <- CoreLineIndx[ii]
if (svalue(CoreLineCK[[ii]])=="FALSE") { #if the coreline is not selected the fit component are disabled
if (hasComponents(XPSSample[[indx]])) { #Does the coreline possess fitting components?
svalue(ComponentCK[[ii]]) <- ""
}
names(CoreLineComp)[ii] <<- ""
}
if (svalue(CoreLineCK[[ii]])=="TRUE") { #if the coreline is selected all the fitting components are selected
if (hasComponents(XPSSample[[indx]])) {
svalue(ComponentCK[[ii]]) <- names(XPSSample[[indx]]@Components)
}
names(CoreLineComp)[ii] <<- CoreLineNames[ii] #reset coreline name: it could be dropped if all fitting components are cancelled
}
}
SetRSF <- function(ii){
kk <- 1
for(ii in 1:NCoreLines){
Eq.RSF <- TRUE #Eq.RSF==TRUE means all RSF are equal
indx <- CoreLineIndx[ii]
LL=length(unlist(OrigCoreLinComp[ii])) #the list vectors may have different lengths (different N. Fit components)
if (LL > 0){ #The RSF may be changed then control the RSF of all the fit components
refRSF <- svalue(RSFCK[[kk]]) #set the referenceRSF as the first of the CorelineComponent
if (Eq.RSF == TRUE){ #if all Component RSF are equal set same value also in the Coreline RSF-Slot
XPSSample[[indx]]@RSF <<- as.numeric(refRSF)
}
for(jj in 1:LL){
newRSF <- svalue(RSFCK[[kk]])
if (newRSF != refRSF) { Eq.RSF <- FALSE } #at end of for Eq.RSF==TRUE means all RSF are equal
slot(XPSSample[[indx]]@Components[[jj]], "rsf") <<- as.numeric(newRSF) #load the new RSFR in the relative slot of the XPSSample
kk <- kk+1
}
}
if (LL == 0) {
newRSF <- svalue(RSFCK[[kk]])
XPSSample[[indx]]@RSF <<- as.numeric(newRSF) #load the new RSFR in the relative slot of the XPSSample
kk <- kk+1
}
}
}
CKHandlers <- function(){
for(ii in 1:NCoreLines){
#----HANDLER on Widget-CoreLineCK to call ResetComp()
if ((svalue(CoreLineCK[[ii]]) != CLChecked[ii]) && length(CLChecked[ii])>0) {
CLChecked[ii] <<- svalue(CoreLineCK[[ii]])
ResetComp(ii) #set/reset fit components
}
#----HANDLER on Widget-ComponentCK
tmp1 <- svalue(ComponentCK[[ii]])
tmp2 <- unlist(CoreLineComp[[ii]])
if(svalue(CoreLineCK[[ii]])==FALSE && is.null(tmp2)==TRUE) { #Coreline has only baseline is un-selected
tmp1 <- ""
tmp2 <- ""
svalue(CoreLineCK[[ii]]) <- FALSE
} else if(length(tmp1)==0 && length(tmp2)>0) { #Coreline with fit is un-selected
tmp1 <- ""
svalue(CoreLineCK[[ii]]) <- FALSE
CLChecked[ii] <<- FALSE
} else {
svalue(CoreLineCK[[ii]]) <- TRUE
CLChecked[ii] <<- TRUE
}
if(is.null(tmp2)=="TRUE") {
tmp2 <- ""
} # the correspondent coreline does NOT possess fitting components but only the BaseLine
if (all(tmp1==tmp2)==FALSE) { #if the two vector contain different elements
CoreLineComp[ii] <<- list(tmp1) #modify component [ii] of the list following the checkbox component selections
if (nchar(tmp1)==0) {
names(CoreLineComp)[ii] <<- ""
CLChecked[ii] <<- ""
}
if (nchar(tmp1) > 0) {
CoreLineComp <<- setNames(CoreLineComp, CoreLineNames)
}
}
}
}
#----MakeNb makes the notebook: a coreline for each notebook page
MakeNb <- function(){
kk <- 1
# CoreLineCK <- list() #define a list of Gwidget
# ComponentCK <- list()
# RSFCK <- list()
for(ii in 1:NCoreLines){
Qgroup[[ii]] <<- ggroup(label=CoreLineNames[ii], horizontal=TRUE, container=Qnb)
Qlayout[[ii]] <<- glayout(homogeneous=FALSE, spacing=3, container=Qgroup[[ii]])
NoComp <- "FALSE"
indx <- CoreLineIndx[ii]
tmp <- names(XPSSample[[indx]]@Components)
if (is.null(tmp)) { NoComp <- "TRUE" }
LL <- length(tmp) # the vector of the list may have different length (different N FitComp)
CoreLineComp <<- c(CoreLineComp, list(tmp)) #create a list containing the fit components of corelines
txt <- paste("CORE LINE", ii , sep="")
Qlayout[[ii]][1,1] <<- CLframe[[ii]] <<- gframe(text=txt, horizontal=FALSE, spacing=5, container=Qlayout[[ii]])
CoreLineCK[[ii]] <<- gcheckbox(CoreLineNames[ii], checked=CLChecked[ii], handler=function(h, ...){
ii <- svalue(Qnb) #set the ii value to the active notebook page
CKHandlers()
}, container=CLframe[[ii]]) #here CoreLineName is an array
Qlayout[[ii]][1,2] <<- CMPframe[[ii]] <- gframe(text="COMPONENTS", horizontal=FALSE, spacing=5, container=Qlayout[[ii]])
ComponentCK[[ii]] <<- gcheckboxgroup(unlist(CoreLineComp[ii]), checked=TRUE, handler=function(h,...){
ii <- svalue(Qnb) #set the ii value to the active notebook page
CKHandlers()
}, container=CMPframe[[ii]]) #here CoreLineName is an array
Qlayout[[ii]][1,3] <<- RSFframe[[ii]] <- gframe(text="RSF", horizontal=FALSE, spacing=5, container=Qlayout[[ii]])
if ( NoComp=="TRUE"){
ComponentCK[[ii]] <<- "" #NO fitting components only baseline
OldRSF <<- XPSSample[[indx]]@RSF
RSFCK[[kk]] <<- gedit(text=OldRSF, handler=NULL, container=RSFframe[[ii]])
kk <- kk+1
} else {
for(jj in 1:LL){
OldRSF <<- XPSSample[[indx]]@Components[[jj]]@rsf
RSFCK[[kk]] <<- gedit(text=OldRSF, handler=NULL, container=RSFframe[[ii]])
kk <- kk+1
}
}
}
CoreLineComp <<- setNames(CoreLineComp, CoreLineNames) #the list contains the names of the corelines and relative FitComponents
OrigCoreLinComp <<- CoreLineComp
ii <- NCoreLines+1
Qgroup[[ii]] <<- ggroup(label=" QUANTIFY ", horizontal=FALSE, container=Qnb)
Qlayout[[ii]] <<- glayout(homogeneous=FALSE, spacing=3, container=Qgroup[[ii]])
Qlayout[[ii]][1,1] <<- gbutton(" QUANTIFY ", handler=function(h,...){ #glayout is generated in MakeNB()
SetRSF()
#extract indexes of CoreLines selected for quantification
CheckedCL <- names(CoreLineComp)
CheckedCL <- CheckedCL[which(CheckedCL !="")]
CheckedCL <- sapply(CheckedCL, function(x) { x <- unlist(strsplit(x, "\\."))
x <- unname(x)
return(x)
})
CheckedCL <- as.integer(CheckedCL[1,])
#Control on the Pass Energies
CK.PassE <- PassE[CheckedCL] #extracts PE valued corresponding to the elements selected for quantification
idx <- unname(which(CK.PassE != CK.PassE[1])) #are the selected elements acquired at different PE?
is.NC <- TRUE #logic, TRUE if NormCoeff is already computed
idx <- CheckedCL[idx] #now idx correctly indicates the corelines
for(ii in idx){
if(length(XPSSample[[ii]]@RegionToFit) < 3){
is.NC <- FALSE} #NormCoeff not saved in ...RegionToFit@NormCoeff
}
if (length(idx) > 0 && is.NC == FALSE) { #selected elements are acquired at different PE and NormCoeff not computed
answ <- gconfirm(" Found spectra acquired at different Pass Energies. \n Do you want to quantify spectra EXTRACTED FROM SURVEY ?",
title="NORMALIZATION COEFFICIENT", icon="warning")
if (answ == TRUE){
#Control how many Survey spectra in XPSSample
SurIdx <<- grep("Survey", SpectList) #indexes of the names components == "Survey"
if (length(SurIdx) == 0) {
SurIdx <<- grep("survey", SpectList)
}
N_Survey <- length(SurIdx)
if (N_Survey > 1) {
txt <- paste(" Found ", N_Survey, " in the XPSSample ", activeFName, ": \n select the Survey used to extract the Core Lines", sep="")
gmessage(txt, title="SELECT SURVEY", icon="warning")
winCL <- gwindow("SELECT SURVEY", visible=FALSE)
size(winCL) <- c(250, 150)
groupCL <- ggroup(horizontal=FALSE, container=winCL)
CL_Names <- SpectList[SurIdx]
selectSur <- gradio(CL_Names, selected=1, horizontal=TRUE, container=groupCL)
gbutton(" OK ", handler=function(h, ...){
SurIdx <<- svalue(selectSur)
SurIdx <<- unlist(strsplit(SurIdx, "\\.")) #drop "NUMBER." at beginning of coreLine name
SurIdx <<- as.integer(SurIdx[1])
dispose(winCL)
}, container=groupCL)
visible(winCL) <- TRUE
winCL$set_modal(TRUE) #nothing can be done while running this macro
}
cat("\n => Compute the normalization coefficient")
CalcNormCoeff(CheckedCL, CK.PassE, SurIdx)
if(NormCoeff == -1){ #Found wide spectrum and corelines acquired using different energy units.
return()
}
} else {
gmessage("Spectra acquired at different PE cannot be used for quantification", title="QUANTIFICATION NOT ALLOWED", icon="warning")
return()
}
}
quant(CoreLineComp)
}, container = Qlayout[[ii]])
Qlayout[[ii]][1,2] <<- gbutton(" WRITE TO FILE ", handler=function(h,...){
Filename <- unlist(strsplit(QTabTxt[2], ":"))[2]
Filename <- unlist(strsplit(Filename, "\\."))[1]
Filename <- paste(Filename, "txt", sep="")
PathFile <- gfile(text = "", type = "save", initial.filename = "Filename", initial.dir = getwd())
NL <- length(QTabTxt)
if (is.null(PathFile)) {
gmessage(msg="File Name not defined. Please give the file name", title="NO FILENAME", icon="error")
return()
}
OutFile <- file(PathFile, open="wt")
for (ii in 1:NL){
writeLines(QTabTxt[ii], sep="", OutFile)
}
close(OutFile)
}, container = Qlayout[[ii]])
QTable <<- gtext(text="", wrap=FALSE, container = Qgroup[[ii]])
size(QTable) <<- c(550, 370)
svalue(QTable) <- ""
for (ii in (NCoreLines+1):1){
svalue(Qnb) <<- ii #refresh all pages until from the last to the first
}
return(CoreLineComp)
}
#----Reset vars resets variables to initial values
ResetVars <- function(){
XPSSample <<- get(activeFName, envir = .GlobalEnv) #load the active XPSSample dataFrame
XPSSampleList <<- XPSFNameList() #list of all XPSSamples
XPSSampleIdx <<- grep(activeFName,XPSSampleList)
SpectList <<- XPSSpectList(activeFName) #list of all CoreLines of the active XPSSample
PassE <<- RetrivePE() # Retrieve list of CoreLine Pass Energies
NormCoeff <<- 1
CoreLineNames <<- ""
CoreLineIndx <<- NULL
FitComp <<- ""
NComp <<- NULL
CoreLineComp <<- list()
OrigCoreLinComp <<- list()
CompChecked <<- NULL
CoreLineCK <<- list() #define a list of the selected CL for quantification
ComponentCK <<- list() #define the CL fit components selected CL for quantification
RSFCKv <- list()
Qgroup <<- list()
Qlayout <<- list()
CLframe <<- list()
CMPframe <<- list()
RSFframev <<- list()
QTable <<- list()
NCoreLines <<- length(SpectList)
NoFitFoundv <<- 0
NmaxFitCompv <<- 0
QTabTxt <<- "" #text containing Quantification results for the Qtable gtext()
TabTxt <<- "" #text containing Quantification results for the RStudio consolle
RegionToFit <- 0
jj <- 1
for(ii in 1:NCoreLines){
if (length(XPSSample[[ii]]@RegionToFit) > 0){ #a Baseline is defined
RegionToFit <- 1
CoreLineNames[jj] <<- SpectList[ii] #Save the coreline name where a baseline is defined
CoreLineIndx[jj] <<- ii #vector containing indexes of the corelines where a baseline is defined
jj <- jj+1
NFC <- length(XPSSample[[ii]]@Components)
if (NFC > NmaxFitComp) {NmaxFitComp <<- NFC}
}
}
if (RegionToFit == 0){
gmessage(msg="WARNING: NO FIT REGIONS DEFINED ON THIS XPS SAMPLE", title = "WARNING", icon = "warning")
return()
}
NCoreLines <<- length(CoreLineIndx) #now only the corelines with baseline are considered for the quantification
CLChecked <<- rep("TRUE",NCoreLines)
}
#---- variables ----
if (is.na(activeFName)){
gmessage("No data present: please load and XPS Sample", title="XPS SAMPLES MISSING", icon="error")
return()
}
XPSSample <- NULL
XPSSample <- get(activeFName, envir = .GlobalEnv) #load the active XPSSample
XPSSampleList <- XPSFNameList() #list of all XPSSamples
XPSSampleIdx <- grep(activeFName,XPSSampleList)
SpectList <- XPSSpectList(activeFName) #list of all the corelines of the active XPSSample
PassE <- RetrivePE() # Retrieve list of CoreLine Pass Energies
names(PassE) <- SpectList
NormCoeff <<- 1
CoreLineNames <- ""
CoreLineIndx <- NULL
FitComp <- ""
NComp <- NULL
CoreLineComp <- list()
OrigCoreLinComp <- list()
CompChecked <- NULL
CoreLineCK <- list() #define a list of the Gwidgets
ComponentCK <- list()
RSFCK <- list()
Qgroup <- list()
Qlayout <- list()
CLframe <- list()
CMPframe <- list()
RSFframe <- list()
QTable <- list()
NCoreLines <- length(SpectList)
NoFitFound <- 0
NmaxFitComp <- 0
QTabTxt <- "" #text containing Quantification results for the Qtable gtext()
TabTxt <- "" #text containing Quantification results for the RStudio consolle
RegionToFit <- 0
jj <- 1
for(ii in 1:NCoreLines){
if (length(XPSSample[[ii]]@RegionToFit) > 0){ #a baseline is defined
RegionToFit <- 1
CoreLineNames[jj] <- SpectList[ii] #Save the coreline name where a baseline is defined
CoreLineIndx[jj] <- ii #vector containing indexes of the corelines where a baseline is defined
jj <- jj+1
NFC <- length(XPSSample[[ii]]@Components)
if (NFC > NmaxFitComp) {NmaxFitComp <- NFC}
}
}
if (RegionToFit == 0){
gmessage(msg="WARNING: NO FIT REGIONS DEFINED ON THIS XPS SAMPLE", title = "WARNING", icon = "warning")
return()
}
NCoreLines <- length(CoreLineIndx) #now only the corelines with baseline are considered for the quantification
CLChecked <- rep("TRUE",NCoreLines)
#===== GUI =====
Qwin <- gwindow(" QUANTIFICATION FUNCTION ", visible=FALSE)
size(Qwin) <- c(280, 530)
QmainGroup <- ggroup(horizontal=FALSE, container=Qwin)
Qgrp0 <- ggroup(horizontal= TRUE, spacing=2, container=QmainGroup)
glabel(text="XPSSample", container=Qgrp0)
SelXPSData <- gcombobox(XPSSampleList, width=15, selected=XPSSampleIdx, handler=function(h, ...){
activeFName <<- svalue(SelXPSData)
ResetVars()
assign("activeSpectIndx", 1, envir=.GlobalEnv)
assign("activeSpectName", SpectList[1], envir=.GlobalEnv)
delete(Qframe1,Qnb)
Qnb <<- gnotebook(expand=TRUE, container = Qframe1)
add(Qframe1,Qnb)
CoreLineComp <<- MakeNb()
plot(XPSSample)
}, container=Qgrp0)
QReset <- gbutton(" RESET ", handler=function(h,...){
ResetVars()
delete(Qframe1,Qnb)
Qnb <<- gnotebook(expand=TRUE, container = Qframe1)
add(Qframe1,Qnb)
CoreLineComp <<- MakeNb()
plot(XPSSample)
}, container = Qgrp0)
QSave <- gbutton(" SAVE ", handler=function(h,...){
SetRSF()
assign(activeFName, XPSSample, .GlobalEnv) #save the fit parameters in the activeSample
XPSSaveRetrieveBkp("save")
}, container = Qgrp0)
QSaveExit <- gbutton(" SAVE & EXIT ", handler=function(h,...){
SetRSF()
assign(activeFName, XPSSample, .GlobalEnv) #save the fit parameters in the activeSample
dispose(Qwin)
XPSSaveRetrieveBkp("save")
}, container = Qgrp0)
Qframe1 <- gframe(text="Core Lines", spacing=5,horizontal=FALSE, container=QmainGroup)
Qnb <- gnotebook(expand=TRUE, container = Qframe1)
CoreLineComp <- MakeNb()
CoreLineComp <- setNames(CoreLineComp, CoreLineNames) #the list contains the names of the coreline and the relative FitComponents
OrigCoreLinComp <- CoreLineComp
visible(Qwin) <- TRUE
for(ii in (NCoreLines+1):1){ #reset nb pages from the last to the first
svalue(Qnb) <- ii
}
Qwin$set_modal(TRUE)
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.