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R

# INCA.R
# Functions to read and manipulate data from the Oxford INCA EDS
# Taha Ahmed, April 2011
# CONTENTS
source("/home/taha/chepec/chetex/common/R/common.R")
# >>>> eds2df
# >>>> edspk
##################################################
################### eds2df #######################
##################################################
eds2df <- function(edstxtfile) {
## Description:
## Reads EDS textfile from INCA EDS.
## Stores data in data frame.
## Usage:
## eds2df(edstxtfile)
## Arguments:
## edstxtfile: character string, the full filename
## (with path) to one txt file.
## Value:
## A dataframe
#
incatxt <- file(edstxtfile, "r")
edsfile <- readLines(incatxt, n = -1) #read all lines of input file
close(incatxt)
#
sampleid <- ProvideSampleId(edstxtfile)
#
rgxp.comment <- "^\\#"
#
numrow.idx <- regexpr(rgxp.comment, edsfile)
# scrap the match.length attribute
attr(numrow.idx, "match.length") <- NULL
#
i <- seq(1, length(numrow.idx) - 1, 1)
j <- seq(2, length(numrow.idx), 1)
# Start index of data range
start.idx <- which(numrow.idx[i] == 1 & numrow.idx[j] != 1) + 1
# End index of the data range
end.idx <- which(numrow.idx[i] != 1 & numrow.idx[j] == 1)
#
zz <- textConnection(edsfile[start.idx:end.idx], "r")
#
ff <- data.frame()
ff <- data.frame(stringsAsFactors = FALSE,
sampleid = sampleid,
matrix(scan(zz, what = numeric(), sep = ","), ncol = 2, byrow = T))
close(zz)
names(ff) <- c("sampleid", "energy", "counts")
#
### Collect attributes of this experiment
# XUnit
position.XUnit <- regexpr("^\\#XUNITS", edsfile)
XUnit <- as.character(strsplit(edsfile[which(position.XUnit == 1)], ":\\s")[[1]][2])
ff$XUnit <- XUnit
# YUnit
position.YUnit <- regexpr("^\\#YUNITS", edsfile)
YUnit <- as.character(strsplit(edsfile[which(position.YUnit == 1)], ":\\s")[[1]][2])
ff$YUnit <- YUnit
# Date
position.Date <- regexpr("^\\#DATE", edsfile)
Date <- strsplit(edsfile[which(position.Date == 1)], ":\\s")[[1]][2]
ff$Date <- Date
# Time
position.Time <- regexpr("^\\#TIME", edsfile)
Time <- strsplit(edsfile[which(position.Time == 1)], ":\\s")[[1]][2]
ff$Time <- Time
# XPerChannel
position.XPerChannel <- regexpr("^\\#XPERCHAN", edsfile)
XPerChannel <- as.numeric(strsplit(edsfile[which(position.XPerChannel == 1)], ":\\s")[[1]][2])
ff$XPerChannel <- XPerChannel
# Offset
position.Offset <- regexpr("^\\#OFFSET", edsfile)
Offset <- as.numeric(strsplit(edsfile[which(position.Offset == 1)], ":\\s")[[1]][2])
ff$Offset <- Offset
# ChOffset
position.ChOffset <- regexpr("^\\#CHOFFSET", edsfile)
ChOffset <- as.numeric(strsplit(edsfile[which(position.ChOffset == 1)], ":\\s")[[1]][2])
ff$ChOffset <- ChOffset
# LiveTime
position.LiveTime <- regexpr("^\\#LIVETIME", edsfile)
LiveTime <- as.numeric(strsplit(edsfile[which(position.LiveTime == 1)], ":\\s")[[1]][2])
ff$LiveTime <- LiveTime
# DeadTime is calculated from: REALTIME - LIVETIME
position.RealTime <- regexpr("^\\#REALTIME", edsfile)
RealTime <- as.numeric(strsplit(edsfile[which(position.RealTime == 1)], ":\\s")[[1]][2])
DeadTime <- RealTime - LiveTime
ff$DeadTime <- DeadTime
# BeamEnergy
position.BeamEnergy <- regexpr("^\\#BEAMKV", edsfile)
BeamEnergy <- as.numeric(strsplit(edsfile[which(position.BeamEnergy == 1)], ":\\s")[[1]][2])
ff$BeamEnergy <- BeamEnergy
#
return(ff)
}
##################################################
#################### edspk #######################
##################################################
edspk <- function(eds.exp, kerpk = 1, fitmaxiter = 50) {
eds.base <- baselinefit(eds.exp, tau=2.0, gam=1.0, scl.factor=3.0, maxwdth=0.20)
# This loop deals with the output from baselinefit()
# It makes a "melted" dataframe in long form for each
# separated peak for some baseline parameters
eds.pks <- data.frame()
eds.pks.basl <- data.frame()
eds.pks.pmg <- data.frame()
eds.pks.spl <- data.frame()
peaks <- 1:length(eds.base$npks)
for (s in peaks) {
# recorded data in long form by separated peak
eds.pks <- rbind(eds.pks, # column names assigned after loop
data.frame(peak = factor(peaks[s]),
kernel = NA,
eds.exp[eds.base$indlsep[s]:eds.base$indrsep[s], ]))
# the calculated baseline in long form by separated peak
eds.pks.basl <- rbind(eds.pks.basl,
data.frame(peak = factor(peaks[s]),
kernel = NA,
x = eds.exp[eds.base$indlsep[s]:eds.base$indrsep[s]],
y = eds.base$baseline$basisl[eds.base$indlsep[s]:eds.base$indrsep[s]]))
# the taut string estimation in long form by separated peak
eds.pks.pmg <- rbind(eds.pks.pmg,
data.frame(peak = factor(peaks[s]),
kernel = NA,
x = eds.exp[eds.base$indlsep[s]:eds.base$indrsep[s]],
y = eds.base$pmg$fn[eds.base$indlsep[s]:eds.base$indrsep[s]]))
# the weighted smoothed spline in long form by separated peak
eds.pks.spl <- rbind(eds.pks.spl,
data.frame(peak = factor(peaks[s]),
kernel = NA,
x = eds.exp[eds.base$indlsep[s]:eds.base$indrsep[s]],
y = eds.base$spl$reg[eds.base$indlsep[s]:eds.base$indrsep[s]]))
}
# Column names assigned to d.pks
names(eds.pks) <- c("peak", "kernel", "x", "y")
# This loop calls pkdecompint() on each peak separately
# It makes a "melted" dataframe in long form for:
eds.fit <- list() # holds pkdecompint output
eds.fit.fitpk <- data.frame() # contains fitting curves
eds.fit.parpk <- data.frame() # physical parameters by peak and kernel
eds.nobasl <- data.frame() # data with baseline removed
peaks <- 1:length(eds.base$npks)
for (s in peaks) {
######## PKDECOMPINT ########
if (length(kerpk) > 1) {
# set number of kernels per peak manually
eds.fit[[s]] <- pkdecompint(eds.base, intnum = s,
k = kerpk[s], maxiter = fitmaxiter)
} else {
# use number of kernels determined by baselinefit()
eds.fit[[s]] <- pkdecompint(eds.base, intnum = s,
k = eds.base$npks[s], maxiter = fitmaxiter)
}
# Setup the dataframe that makes up the peak table
for (kernel in 1:eds.fit[[s]]$num.ker) {
eds.fit.parpk <- rbind(eds.fit.parpk,
data.frame(peak = factor(eds.fit[[s]]$intnr),
kernel = factor(kernel),
x = eds.fit[[s]]$parpks[kernel, "loc"],
height = eds.fit[[s]]$parpks[kernel, "height"],
area = eds.fit[[s]]$parpks[kernel, "intens"],
fwhm = eds.fit[[s]]$parpks[kernel, "FWHM"],
m = eds.fit[[s]]$parpks[kernel, "m"],
accept = eds.fit[[s]]$accept))
eds.fit.fitpk <- rbind(eds.fit.fitpk,
data.frame(peak = factor(peaks[s]),
kernel = factor(kernel),
x = eds.fit[[s]]$x,
y = eds.fit[[s]]$fitpk[kernel, ]))
}
eds.nobasl <- rbind(eds.nobasl,
data.frame(peak = factor(peaks[s]),
x = eds.fit[[s]]$x,
y = eds.fit[[s]]$y))
}
return(list(eds.base = eds.base,
eds.peaks = eds.pks,
eds.fit.parpk = eds.fit.parpk,
eds.fit.fitpk = eds.fit.fitpk,
eds.nobasl = eds.nobasl))
}