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R-common/xrdtf.R

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# Collection of R functions for analysis of thin-film X-ray diffraction patterns
# Maintainer: Taha Ahmed
# CONTENTS
# >>>> matchpdf
# >>>> scherrer
# >>>> pdf2df
# >>>> uxd2mtx
# >>>> uxd2df
# >>>> muxd2df
# >>>> muxd2mtx
# >>>> muxd2ls
# - REPAIR SHOP
# - EliminateKa2
# - print.xtable.booktabs
# - split.muxd
# - strip.ka2
# - pearson.beta
## All XRD reading functions need to be re-written to identify the data instead of identifying metadata
## Take inspiration from the functions in CHI.R
##################################################
################## matchpdf ######################
##################################################
matchpdf <- function(expcol, pdfrow) {
# Function for matching each element of two numeric vectors
# to the closest-lying element (numerically) in the other
# vector. For example for matching 2th values of PDF to
# 2th values of recorded diffractogram.
## Args: two vectors to be matched (any special considerations on vector lengths?)
## Values: A list of 5 numeric vectors. See description inside function.
# A word of caution. This function creates a matrix with dimensions pdfrow * expcol.
# Usually both of these vectors are rather short. But watch out if large vectors
# are submitted --- the looping below could make this function very slow.
#
diff.thth <- matrix(NA, length(pdfrow), length(expcol))
diff.indx <- matrix(NA, length(pdfrow), length(expcol))
for (pdf.row in 1:length(pdfrow)) {
# For every row, calculate differences between that pdf value and all exp values
diff.thth[pdf.row, ] <- expcol - pdfrow[pdf.row]
}
#
# Now we go on to find the minimum along each row of diff.thth
# and set all other values to some arbitrary value
diff.rmin <- diff.thth
for (pdf.row in 1:dim(diff.thth)[1]) {
for (exp.col in 1:dim(diff.thth)[2]) {
if (abs(diff.thth[pdf.row, exp.col]) != min(abs(diff.thth[pdf.row, ]))) {
diff.rmin[pdf.row, exp.col] <- Inf
}
}
}
#
# We likewise find the minimum along each column and set any other,
# non-Inf values to Inf
diff.cmin <- diff.rmin
for (exp.col in 1:dim(diff.rmin)[2]) {
for (pdf.row in 1:dim(diff.rmin)[1]) {
if (abs(diff.rmin[pdf.row, exp.col]) != min(abs(diff.rmin[, exp.col]))) {
diff.cmin[pdf.row, exp.col] <- Inf
}
}
}
#
# The matrix now contains at most one non-Inf value per row and column.
# To make the use of colSums and rowSums possible (next step) all Inf are set zero,
# and all matches are set to 1.
for (pdf.row in 1:dim(diff.cmin)[1]) {
for (exp.col in 1:dim(diff.cmin)[2]) {
if ((diff.cmin[pdf.row, exp.col]) != Inf) {
diff.indx[pdf.row, exp.col] <- 1
} else {
diff.indx[pdf.row, exp.col] <- 0
}
}
}
#
# Attach error message to return list if sum(rowSums(diff.indx)) == sum(colSums(diff.indx))
matchpdf.err.msg <-"matchpdf() failed to complete. It seems rowSums != colSums."
mtch <- matchpdf.err.msg
#
# Check that sum(rowSums(diff.indx)) == sum(colSums(diff.indx))
if (sum(rowSums(diff.indx)) == sum(colSums(diff.indx))) {
# Reset mtch
mtch <- list()
mtch <- list(csums = colSums(diff.indx), rsums = rowSums(diff.indx), expthth = expcol[colSums(diff.indx) != 0], pdfthth = pdfrow[rowSums(diff.indx) != 0], deltathth = expcol[colSums(diff.indx) != 0] - pdfrow[rowSums(diff.indx) != 0])
# List of 5
# $ csums : num - consisting of ones and zeroes. Shows you which positions of expcol matched.
# $ rsums : num - consisting of ones and zeroes. Shows you which positions of pdfrow matched.
# $ expthth : num - consisting of the matching elements of expcol.
# $ pdfthth : num - consisting of the matching elements of pdfrow.
# $ deltathth : num - element-wise difference of expcol and pdfrow.
}
#
return(mtch)
}
##################################################
################## scherrer ######################
##################################################
scherrer <- function(integralbreadth, thth, wavelength = 1.54056, shapeconstant = ((4/3)*(pi/6))^(1/3)) {
# Function for calculating crystallite grain size from reflection data
# ARGS: integralbreadth - vector with integral breadth of reflections (in degrees)
# thth - vector with 2theta values of reflections (in degrees)
# wavelength - X-ray wavelength used (default 1.54056 Å, Cu Ka)
# shapeconstant - Scherrer constant (default spherical, ~0.9)
# VALUE: vector with size parameters
## REQUIRES: as.radians(), source("/home/taha/chepec/chetex/common/R/common.R")
D <- (shapeconstant * wavelength) / (as.radians(integralbreadth) * cos(as.radians(thth)))
# cos() - angles must be in radians, not degrees!
return(D) #units of angstrom
}
##################################################
################### pdf2df #######################
##################################################
pdf2df <- function(pdffile) {
# Function for extracting information from ICDD PDF XML-files
# For example the PDF files produced by the PDF database at Ångström's X-ray lab
# NOTE: sometimes intensity values are specified as less than some value.
# In those cases, this function simply strips the less-than character.
# ARGS: pdffile (complete path and filename to PDF file)
# VALUE: dataframe with 9 columns:
# thth angles (numeric),
# d (numeric),
# h index (numeric),
# k index (numeric),
# l index (numeric),
# hkl indices (factor of strings),
# hkl.TeX indices formatted for LaTeX (factor of strings),
# intensity (numeric),
# int.TeX intensity formatted for LaTeX (factor of strings)
# attr: This function sets the following attributes:
# ApplicationName,
# ApplicationVersion,
# pdfNumber,
# chemicalformula,
# wavelength
#
require(XML)
doc <- xmlTreeParse(pdffile)
pdf <- xmlRoot(doc)
rmchar <- "[^0-9]"
#
angles <- data.frame(NULL)
for (i in 1:length(pdf[["graphs"]][["stick_series"]])) {
angles <- rbind(angles, data.frame(#
thth = as.numeric(xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["theta"]])),
d = as.numeric(xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["da"]])),
h = as.numeric(xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["h"]])),
k = as.numeric(xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["k"]])),
l = as.numeric(xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["l"]])),
hkl = paste(xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["h"]]),
xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["k"]]),
xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["l"]]), sep = ""),
hkl.TeX = paste("\\mbox{$", ifelse(as.numeric(xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["h"]])) < 0,
paste("\\bar{", abs(as.numeric(xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["h"]]))),
"}", sep = ""),
xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["h"]])),
"\\,", ifelse(as.numeric(xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["k"]])) < 0,
paste("\\bar{", abs(as.numeric(xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["k"]]))),
"}", sep = ""),
xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["k"]])),
"\\,", ifelse(as.numeric(xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["l"]])) < 0,
paste("\\bar{", abs(as.numeric(xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["l"]]))),
"}", sep = ""),
xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["l"]])),
"$}", sep = "", collapse = ""),
intensity = as.numeric(gsub(rmchar, "", xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["intensity"]]))),
int.TeX = paste("{", xmlValue(pdf[["graphs"]][["stick_series"]][[i]][["intensity"]]), "}", sep = "")
))
}
#
attr(angles, "ApplicationName") <- xmlAttrs(pdf)[[1]]
attr(angles, "ApplicationVersion") <- xmlAttrs(pdf)[[2]]
attr(angles, "pdfNumber") <- xmlValue(pdf[["pdf_data"]][["pdf_number"]])
attr(angles, "chemicalformula") <- gsub("[ ]", "", xmlValue(pdf[["pdf_data"]][["chemical_formula"]]))
attr(angles, "wavelength") <- as.numeric(xmlValue(pdf[["graphs"]][["wave_length"]]))
# Caution: Do not subset. Subsetting causes all attributes to be lost.
return(angles)
}
##################################################
################### uxd2mtx ######################
##################################################
uxd2mtx <- function(uxdfile) {
# Function for reading UXD files
# Assumptions: data in two columns
# Args: uxdfile (filename with extension)
# Return value: matrix with two columns
cchar <- "[;_]" #regexpr matching the comment characters used in Bruker's UXD
cdata <- "[0-9]" #regexpr matching one character of any digit
# A new file (datafile) containing only data will be created,
# extension ".data" appended to uxdfile
#datafile <- paste(uxdfile,".data",sep="")
ufile <- file(uxdfile, "r")
f <- readLines(ufile, n=-1) #read _all_ lines from UXD file
close(ufile)
# This way we identify data rows by looking for numeric characters.
#wh <- regexpr("[0-9]", f)
# This way we identify header rows
# We assume that all other rows are data
wh <- regexpr(cchar, f)
mh <- wh[1:length(wh)] # this gives you the corresponding index vector
# the value of each element corresponds to the position of the regexp match.
# value = 1 means the first character of the row is cchar (row is header)
# value =-1 means no cchar occur on the row (row is data)
i <- seq(1, length(mh) - 1, 1)
j <- seq(2, length(mh), 1)
starts <- which(mh[i] == 1 & mh[j] != 1) + 1
ends <- length(mh)
f <- f[starts:ends]
zz <- textConnection(f, "r")
ff <- matrix(scan(zz, what = numeric()), ncol=2, byrow=T)
close(zz)
#zz <- file(datafile, "w") #open connection to datafile
#write.table(ff, file=datafile, row.names=F, sep=",")
#close(zz)
# Return matrix
ff
}
##################################################
#################### uxd2df ######################
##################################################
uxd2df <- function(uxdfile) {
# Function for reading UXD files # Assumptions: data in two columns
# Args: uxdfile (filename with extension)
# Returns: dataframe with three columns
cchar <- "[;_]" #regexpr matching the comment characters used in Bruker's UXD
cdata <- "[0-9]" #regexpr matching one character of any digit
# A new file (datafile) containing only data will be created,
# extension ".data" appended to uxdfile
#datafile <- paste(uxdfile,".data",sep="")
ufile <- file(uxdfile, "r")
f <- readLines(ufile, n=-1) #read _all_ lines from UXD file
close(ufile)
# This way we identify data rows by looking for numeric characters.
#wh <- regexpr("[0-9]", f)
# This way we identify header rows
# We assume that all other rows are data
wh <- regexpr(cchar, f)
mh <- wh[1:length(wh)] # this gives you the corresponding index vector
# the value of each element corresponds to the position of the regexp match.
# value = 1 means the first character of the row is cchar (row is header)
# value =-1 means no cchar occur on the row (row is data)
i <- seq(1, length(mh) - 1, 1)
j <- seq(2, length(mh), 1)
starts <- which(mh[i] == 1 & mh[j] != 1) + 1
ends <- length(mh)
f <- f[starts:ends]
rgxp.sampleid <- "[^/]*(?=\\.\\w*)" ## THIS REQUIRES perl=TRUE
# Regular expression that extracts the filename out of a full path.
# Matches and extracts everything from the last forward slash (assuming Unix slashes)
# up until a dot folllowed by an arbitrary number of alphanumeric characters.
sampleidmtch <- regexpr(rgxp.sampleid, uxdfile, perl=TRUE)
# Check that there was a match
if (sampleidmtch < 0) {
# -1 means no match
sampleid <- uxdfile
# If match was unsuccessful we use the argument as passed to this function as sampleid
}
sampleid <- substr(uxdfile, sampleidmtch, (sampleidmtch + attr(sampleidmtch, "match.length") - 1))
zz <- textConnection(f, "r")
ff <- data.frame(sampleid, matrix(scan(zz,
what = numeric()), ncol=2, byrow=T))
names(ff) <- c("sampleid", "angle", "intensity")
close(zz)
#zz <- file(datafile, "w") #open connection to datafile
#write.table(ff, file=datafile, row.names=F, sep=",")
#close(zz)
# Return dataframe
ff
}
##################################################
################### muxd2df ######################
##################################################
muxd2df <- function(uxdfile, range.descriptor) {
# Function that reads an UXD file which contains several ranges
# (created in a programmed run, for example)
# Arguments
# :: uxdfile (filename with extension)
# :: range.descriptor (an array with as many elements as
# there are ranges in the uxdfile)
# Returns: dataframe with 3 columns
cchar <- "[;_]" #regexpr matching the comment characters used in Bruker's UXD
cdata <- "[0-9]" #regexpr matching one character of any digit
# Create filenames for the output # no longer used, return dataframe instead
#datafile <- paste(uxdfile,"-",range.descriptor,".data",sep="")
# Read the input multirange file
ufile <- file(uxdfile, "r")
f <- readLines(ufile, n=-1) #read _all_ lines from UXD file
close(ufile)
# This way we identify data rows by looking for numeric characters.
#wh <- regexpr("[0-9]", f)
# This way we identify header rows
# Later we will assume that all other rows are data
wh <- regexpr(cchar, f)
mh <- wh[1:length(wh)] # this gives you the corresponding index vector
# the value of each element corresponds to the position of the regexp match.
# value = 1 means the first character of the row is cchar (row is header)
# value =-1 means no cchar occur on the row (row is data)
#length(mh[mh == -1]) #total number of datarows in uxdfile
#mh[mh > 1 | mh < 0] <- 0 #set all header-rows to zero (just to make things easier)
i <- seq(1, length(mh) - 1, 1)
j <- seq(2, length(mh), 1)
starts <- which(mh[i] == 1 & mh[j] != 1) + 1 #start indices
ends <- which(mh[i] != 1 & mh[j] == 1) #end indices, except the last
ends <- c(ends, length(mh)) #fixed the last index of ends
ff <- data.frame(NULL)
for (s in 1:length(range.descriptor)) {
zz <- textConnection(f[starts[s]:ends[s]], "r")
ff <- rbind(ff, data.frame(range.descriptor[s],
matrix(scan(zz, what = numeric()), ncol=2, byrow=T)))
close(zz)
}
names(ff) <- c("sampleid", "angle", "intensity")
# Return dataframe
ff
}
##################################################
################### muxd2mtx #####################
##################################################
muxd2mtx <- function(uxdfile, range) {
# Function that reads an UXD file which contains several ranges
# (created in a programmed run, for example)
# Arguments
# :: uxdfile (filename with extension)
# :: range (an integer, the number of ranges in the uxdfile)
# Returns: matrix with 2 columns
cchar <- "[;_]" #regexpr matching the comment characters used in Bruker's UXD
cdata <- "[0-9]" #regexpr matching one character of any digit
# Create filenames for the output # no longer used, return dataframe instead
#datafile <- paste(uxdfile,"-",range.descriptor,".data",sep="")
# Read the input multirange file
ufile <- file(uxdfile, "r")
f <- readLines(ufile, n=-1) #read _all_ lines from UXD file
close(ufile)
# We identify header rows. We will assume that all other rows are data
wh <- regexpr(cchar, f)
# length(wh) equals length(f)
# wh has either 1 or -1 for each element
# value = 1 means the first character of that row is cchar (row is header)
# value =-1 means absence of cchar on that row (row is data)
# Since wh contains some attributes (given by regexpr function), we strip out everything
# but the index vector and assign it to the new vector mh
mh <- wh[1:length(wh)] # this gives you the corresponding index vector
#length(mh[mh == -1]) #total number of datarows in uxdfile
#mh[mh > 1 | mh < 0] <- 0 #set all header-rows to zero (just to make things easier)
# Set counters i and j used in assignment below
i <- seq(1, length(mh) - 1, 1)
j <- seq(2, length(mh), 1)
starts <- which(mh[i] == 1 & mh[j] != 1) + 1 #start indices
ends <- which(mh[i] != 1 & mh[j] == 1) #end indices, except the last
ends <- c(ends, length(mh)) #fixes the last index of ends
# note that length of starts (or ends) gives the number of ranges
ff <- matrix(NA, length(f), 2)
for (s in 1:range) {
zz <- textConnection(f[starts[s]:ends[s]], "r")
ff <- rbind(ff, matrix(scan(zz, what = numeric()), ncol=2, byrow=T))
close(zz)
}
# Clean up matrix: remove extra rows
ff[apply(ff,1,function(x)any(!is.na(x))), ]
# Return matrix
ff
}
##################################################
################### muxd2ls ######################
##################################################
muxd2ls <- function(uxdfile) {
# Function that reads an UXD file which contains several ranges
# (created in a programmed run, for example)
# Arguments
# :: uxdfile (filename with extension)
# Returns: List of matrices, as many as there were ranges
# Requires: ??
# See extensive comments in muxd2mtx()
cchar <- "[;_]" #comment characters used in Bruker's UXD
cdata <- "[0-9]"
ufile <- file(uxdfile, "r")
f <- readLines(ufile, n=-1) #read _all_ lines from UXD file
close(ufile)
wh <- regexpr(cchar, f)
mh <- wh[1:length(wh)]
i <- seq(1, length(mh) - 1, 1)
j <- seq(2, length(mh), 1)
starts <- which(mh[i] == 1 & mh[j] != 1) + 1
ends <- which(mh[i] != 1 & mh[j] == 1)
ends <- c(ends, length(mh))
ff <- list()
for (s in 1:length(starts)) {
zz <- textConnection(f[starts[s]:ends[s]], "r")
ms <- matrix(scan(zz, what = numeric()), ncol = 2, byrow = T)
close(zz)
ff[[s]] <- ms
}
# Return list of matrices
return(ff)
}
# -------- ##################### -------- #
# -------- #### REPAIR SHOP #### -------- #
# -------- ##################### -------- #
##################################################
################ EliminateKa2 ####################
##################################################
EliminateKa2 <- function(thth, intensity, lever = 2) {
# Args: 2theta vector, numeric
# intensity vector, numeric
# parameter pairs, numeric between 1 and 6, default 2
# "High-quality a2-free patterns can be obtained in most cases
# using five (5) or seven (7) pairs of parameters."
# "When the step-width is less than 0.01 degrees and the
# 2theta angle is high, a large number of parameter pairs
# should be used to get accurate results." {Dong1999a}
### 1 2 3 4 5 6 - lever
### 3 5 7 9 15 25 - corresponding parameter pairs
#
##### THIS FUNCTION USES THESE OTHER FUNCTIONS #####
# REQUIRES: common.R :: as.radians() - converts degrees to radians
# REQUIRES: stats::approx - linear interpolation
####################################################
# For test-purposes, use the following data
# /home/taha/chepec/laboratory/XRD/0103-instrumentbroadening/100917Th2ThLong-counts.UXD
##### STILL UNDER CONSTRUCTION ####
##### STILL UNDER CONSTRUCTION ####
startdatapoint <- 4
# Ka1a Ka1b Ka2a Ka2b
CuKa.data <- c(1.534753, 1.540596, 1.541058, 1.544410, 1.544721,
3.69, 0.44, 0.60, 0.52, 0.62,
1.60, 57.07, 7.64, 25.38, 8.31)
CuKa <- data.frame(matrix(CuKa.data, ncol=3, byrow=F))
names(CuKa) <- c("lambda", "w", "E")
row.names(CuKa) <- c("Satellites", "Ka1a", "Ka1b", "Ka2a", "Ka2b")
# The following lever arm weights are from Dong1999a
weights <- list()
# Three-bar weights
weights[[1]] <- c(0.005134296, 0.491686047, 0.003179657)
# Five-bar weights
weights[[2]] <- c(0.002614410, 0.011928014, 0.480406967,
0.002121807, 0.002928802)
# Seven-bar weights
weights[[3]] <- c(0.001580069, 0.003463773, 0.015533472, 0.422601977,
0.053632977, 0.001572467, 0.001615265)
# Nine-bar weights
weights[[4]] <- c(0.001138001, 0.00195272, 0.004324464,
0.019246541, 0.394175823, 0.079159001,
-0.003591547, 0.002505604, 0.001089392)
# 15-bar weights
weights[[5]] <- c(0.000614225, 0.000810836, 0.001134775, 0.001723265, 0.002968405,
0.006433676, 0.02575384, 0.345872599, 0.100578092, 0.014493969,
-0.004176171, 0.000678688, 0.001610333, 0.000918077, 0.000585391)
# 25-bar weights
weights[[6]] <- c(0.000349669, 0.000408044, 0.000484578, 0.000587457, 0.000730087,
0.000935685, 0.001247401, 0.001753233, 0.002657209, 0.004531817,
0.009591103, 0.034998436, 0.2876498, 0.074964321, 0.065000871,
0.016762729, -0.00306221, -0.002717412, -0.000902322, 0.000915701,
0.001036484, 0.000808199, 0.000539899, 0.000398896, 0.000330325)
# The following lever arm lengths are from Dong1999a
lengths <- list()
# Three-bar lengths
lengths[[1]] <- c(0.998506815, 0.997503913, 0.996699460)
# Five-bar lengths
lengths[[2]] <- c(0.998471576, 0.997935524, 0.997503530,
0.997163494, 0.996606519)
# Seven-bar lengths
lengths[[3]] <- c(0.998563433, 0.998204025, 0.997825027, 0.997522195,
0.997297615, 0.996844235, 0.996516288)
# Nine-bar lengths
lengths[[4]] <- c(0.998609749, 0.998334027, 0.998054914,
0.99776062, 0.997527844, 0.997327154,
0.997028978, 0.996734639, 0.99646335)
# 15-bar lengths
lengths[[5]] <- c(0.998671599, 0.99850911, 0.998346447, 0.998183442, 0.998019704,
0.997854063, 0.997680649, 0.997533314, 0.997377391, 0.997266106,
0.997060614, 0.996888005, 0.996741151, 0.996583672, 0.996418168)
# 25-bar lengths
lengths[[6]] <- c(0.998706192, 0.998608958, 0.998511721, 0.998414475, 0.998317209,
0.998219906, 0.998122538, 0.998025057, 0.997927367, 0.997829244,
0.997730044, 0.997626987, 0.997535705, 0.997458223, 0.997346989,
0.997277763, 0.997161452, 0.997057942, 0.996982688, 0.99686108,
0.996769728, 0.996675255, 0.996578407, 0.996480641, 0.99638324)
### --- Arguments check
# Check that "lever" argument is within bounds
if (lever > length(weights) || lever < 1) {
# if not, fall back to the default value
lever <- 2 # corresponds to 5 parameter pairs
}
### --- Arguments check
# Check that vectors are of the same length
if (!(length(thth) == length(intensity))) {
# If not the same length, abort with error message
stop("Arguments thth and intensity have different lengths!")
}
### --- Arguments check
if (any(thth <= 0)) {
stop("thth vector contains values less-than or equal to zero")
}
### --- Arguments check
if (any(intensity < 0)) {
stop("intensity vector contains values less than zero")
}
# THIS IS NECESSARY, but overlooked for the moment
#int.p.start <- (1 / (1 + (CuKa["Ka2a", "E"] + CuKa["Ka2b", "E"]) /
#(CuKa["Ka1a", "E"] + CuKa["Ka1b", "E"]))) * intensity[1:startdatapoint-1]
# Redefine everything
#thth <- thth[startdatapoint:length(thth)]
#intensity <- intensity[startdatapoint:length(intensity)]
# Convert from 2theta to theta scale for use in first step of calculations
theta <- thth / 2
sintheta <- sin(as.radians(theta))
# Corresponds to equation 10 in Dong1999a
# This is based on the assumption that we are supposed to get delta-thth values
delta.thth.a <- matrix(0, length(theta), length(weights[[lever]]))
for (j in 1:length(lengths[[lever]])) {
delta.thth.a[,j] <- 2 * asin(as.radians((lengths[[lever]][j] * sintheta)))
}
# Add the calculated deltas to the recorded thth values
# Corresponds to equation 10 in Dong1999a
thth.a <- matrix(NA, dim(delta.thth.a)[1], dim(delta.thth.a)[2] + 1)
# Flip the delta.thth.a matrix vertically (just for convenience)
delta.thth.a <- delta.thth.a[,dim(delta.thth.a)[2]:1]
for (j in 2:dim(thth.a)[2]) {
thth.a[,1] <- thth
thth.a[,j] <- thth + delta.thth.a[,j - 1]
}
# Intensities with interpolated intensities at the calculated 2theta values
int.interp <- matrix(NA, dim(thth.a)[1], dim(thth.a)[2])
for (j in 2:dim(int.interp)[2]) {
int.interp[,1] <- intensity
int.interp[,j] <- approx(thth, intensity, xout = thth.a[,j])$y
}
# So far, we have just replaced the old thth-scale with a new one,
# and calculated the intensitites by linearly interpolating from the old intensities.
# Intensities times lever weights, P(j) (this is what you will substract from int.interp)
int.p <- matrix(NA, length(theta), length(weights[[lever]]))
for (j in 1:length(lengths[[lever]])) {
int.p[,j] <- weights[[lever]][j] * int.interp[,j + 1]
}
# Calculate intensities with Ka2 contribution stripped
#int.stripped <- c(int.interp[,-1]) - rowSums(int.p)
int.stripped <- thth - rowSums(int.p)
#corr.tmp.df <- data.frame(thth = c(thth.a[,-1]), int.corr = int.stripped)
corr.tmp.df <- data.frame(thth = thth, int.corr = int.stripped)
corr.df <- corr.tmp.df[order(corr.tmp.df$thth), ]
#row.names(corr.df) <- seq(1, length(corr.df$thth))
# Make a dataframe of thth.a and int.a and order it by thth
#df.a <- data.frame(thth = c(thth.a), intensity = c(int.a))
#df.as <- df.a[order(df.a$thth), ]
#row.names(df.as) <- seq(1,length(df.as$thth)) # fixes row names order
# df.as is exactly as the original data, just with the correct number of
# interpolated thth and intensity values included.
return(corr.df)
# Perhaps thth.a and int.p.terms are the new x and y
# Intensities in summation term (this is the Ka2 correction)
#int.p <- rowSums(int.p.terms)
# Collapse the matrix thth.a into a single column
#thth.ai <- matrix(NA, dim(thth.a)[1] * dim(thth.a)[2], 2)
#thth.ai[,1] <- sort(c(thth.a))
#thth.ai[,2] <- approx(thth, intensity, xout = thth.ai[,1])$y
# Built-in functions in R to interpolate or extrapolate
# stats::approx Linear interpolation
# Hmisc::approxExtrap Linear extrapolation
# go with linear functions for now, see how that works out
# This is NOT necessary
# This vector helps convert from lever to actual number of parameter pairs
#parpairs <- numeric()
#for (j in 1:length(weights)) {
# parpairs[j] <- length(weights[[j]])
#}
##### STILL UNDER CONSTRUCTION ####
}
##################################################
################ pearson.beta ####################
##################################################
pearson.beta <- function(m, w) {
# Function for calculating integral breadth, \beta, of
# an X-ray reflection using the half-width of FWHM (w)
# and m parameter from a Pearson fit.
## Args: m - shape parameter from Pearson fit (numeric)
## w - half the FWHM for the reflection (numeric)
## **** NOTE: gamma(x) out of range for x > 171
## Values: The integral breadth of the reflection (numeric)
# Ref: Birkholz2006, page 96 (Eq. 3.5)
beta <- ((pi * 2^(2 * (1 - m)) * gamma(2 * m - 1)) /
((2^(1 / m) - 1) * (gamma(m))^2)) * w
}
##################################################
################## strip.ka2 #####################
##################################################
strip.ka <- function(angle, intensity) {
# Function that strips (removes) the Cu Ka2 contribution
# from an experimental diffractogram (2Th, I(2Th))
# using the Rachinger algorithm.
## Args: 2theta vector
## intensity vector
## Values: intensity vector
# Ref: Birkholz2006, page 99 (Eq. 3.12), and page 31
Cu.Kai <- 0.154059 # nanometre
Cu.Kaii <- 0.154441 # nanometre
alpha.int.ratio <- 0.5
int.stripped <- intensity - alpha.int.ratio*intensity
return(int.stripped)
}
print.xtable.booktabs <- function(x){
# Make xtable print booktabs tables
# ARGS: x (matrix)
require(xtable)
print(xtable(x), floating=F, hline.after=NULL,
add.to.row=list(pos=list(-1,0, nrow(x)),
command=c("\\toprule ", "\\midrule ", "\\bottomrule ")))
}
split.muxd <- function(uxdfile, range.descriptor) {
# Fix this some other day!!
# Function that reads an UXD file which contains several ranges
# (created in a programmed run, for example) and splits it into
# its ranges and writes to that number of files
# Arguments
# :: uxdfile (filename with extension)
# :: range.descriptor (an array with as many elements as
# there are ranges in the uxdfile)
# Returns: nothing. Writes files to HDD.
cchar <- "[;_]" #regexpr matching the comment characters used in Bruker's UXD
cdata <- "[0-9]" #regexpr matching one character of any digit
# Create filenames for the output # no longer used, return dataframe instead
datafile <- paste(uxdfile,"-",range.descriptor,".data",sep="")
# Read the input multirange file
f <- readLines(uxdfile, n=-1)
# This way we identify data rows by looking for numeric characters.
#wh <- regexpr("[0-9]", f)
# This way we identify header rows
# Later we will assume that all other rows are data
wh <- regexpr(cchar, f)
mh <- wh[1:length(wh)] # this gives you the corresponding index vector
# the value of each element corresponds to the position of the regexp match.
# value = 1 means the first character of the row is cchar (row is header)
# value =-1 means no cchar occur on the row (row is data)
#length(mh[mh == -1]) #total number of datarows in uxdfile
#mh[mh > 1 | mh < 0] <- 0 #set all header-rows to zero (just to make things easier)
i <- seq(1, length(mh) - 1, 1)
j <- seq(2, length(mh), 1)
starts <- which(mh[i] == 1 & mh[j] != 1) + 1 #start indices
ends <- which(mh[i] != 1 & mh[j] == 1) #end indices, except the last
ends <- c(ends, length(mh)) #fixed the last index of ends
#ff <- data.frame(NULL)
for (s in 1:length(range.descriptor)) {
matrix(scan(file=textConnection(f[starts[s]:ends[s]]),
what = numeric()), ncol=2, byrow=T)
}
names(ff) <- c("sampleid", "angle", "intensity")
# Return dataframe
ff
}
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