Added XRD peak wrapper functions (as done previously for XRF and Raman).

Also put the short R-data loading function I wrote into the
common directory.
master
Taha Ahmed 13 years ago
parent 0579b5ea52
commit 3d4244f1fd

@ -19,7 +19,6 @@ pdf2df <- function(pdffile) {
# attr: This function sets the following attributes:
# ApplicationName,
# ApplicationVersion,
# pdfNumber,
# chemicalformula,
# empiricalformula,
# wavelength
@ -55,13 +54,14 @@ pdf2df <- function(pdffile) {
"$}", 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 = ""),
pdfNumber = xmlValue(pdf[["pdf_data"]][["pdf_number"]])
pdfNumber = xmlValue(pdf[["pdf_data"]][["pdf_number"]]),
formula = gsub("[ ]", "", xmlValue(pdf[["pdf_data"]][["empirical_formula"]]))
))
}
#
attr(angles, "ApplicationName") <- xmlAttrs(pdf)[[1]]
attr(angles, "ApplicationVersion") <- xmlAttrs(pdf)[[2]]
attr(angles, "pdfNumber") <- xmlValue(pdf[["pdf_data"]][["pdf_number"]])
#attr(angles, "pdfNumber") <- xmlValue(pdf[["pdf_data"]][["pdf_number"]])
attr(angles, "chemicalformula") <- gsub("[ ]", "", xmlValue(pdf[["pdf_data"]][["chemical_formula"]]))
attr(angles, "empiricalformula") <- gsub("[ ]", "", xmlValue(pdf[["pdf_data"]][["empirical_formula"]]))
attr(angles, "wavelength") <- as.numeric(xmlValue(pdf[["graphs"]][["wave_length"]]))

@ -0,0 +1,92 @@
xrdpk <-
function(xrd.exp, kerpk = 1, fitmaxiter = 50, gam = 1.0, scl.factor = 1.2, maxwdth=5.0) {
xrd.base <- baselinefit(xrd.exp, tau=2.5, gam=gam, scl.factor=scl.factor, maxwdth=maxwdth)
# This loop deals with the output from baselinefit()
# It makes a "melted" dataframe in long form for each
# separated peak for some baseline parameters
xrd.pks <- data.frame()
xrd.pks.basl <- data.frame()
xrd.pks.pmg <- data.frame()
xrd.pks.spl <- data.frame()
peaks <- 1:length(xrd.base$npks)
for (s in peaks) {
# recorded data in long form by separated peak
xrd.pks <- rbind(xrd.pks, # column names assigned after loop
data.frame(peak = factor(peaks[s]),
kernel = NA,
xrd.exp[xrd.base$indlsep[s]:xrd.base$indrsep[s], ]))
# the calculated baseline in long form by separated peak
xrd.pks.basl <- rbind(xrd.pks.basl,
data.frame(peak = factor(peaks[s]),
kernel = NA,
x = xrd.exp[xrd.base$indlsep[s]:xrd.base$indrsep[s], ],
y = xrd.base$baseline$basisl[xrd.base$indlsep[s]:xrd.base$indrsep[s]]))
# the taut string estimation in long form by separated peak
xrd.pks.pmg <- rbind(xrd.pks.pmg,
data.frame(peak = factor(peaks[s]),
kernel = NA,
x = xrd.exp[xrd.base$indlsep[s]:xrd.base$indrsep[s], ],
y = xrd.base$pmg$fn[xrd.base$indlsep[s]:xrd.base$indrsep[s]]))
# the weighted smoothed spline in long form by separated peak
xrd.pks.spl <- rbind(xrd.pks.spl,
data.frame(peak = factor(peaks[s]),
kernel = NA,
x = xrd.exp[xrd.base$indlsep[s]:xrd.base$indrsep[s], ],
y = xrd.base$spl$reg[xrd.base$indlsep[s]:xrd.base$indrsep[s]]))
}
# Column names assigned to d.pks
names(xrd.pks) <- c("peak", "kernel", "x", "y")
# This loop calls pkdecompint() on each peak separately
# It makes a "melted" dataframe in long form for:
xrd.fit <- list() # holds pkdecompint output
xrd.fit.fitpk <- data.frame() # contains fitting curves
xrd.fit.parpk <- data.frame() # physical parameters by peak and kernel
xrd.nobasl <- data.frame() # data with baseline removed
peaks <- 1:length(xrd.base$npks)
for (s in peaks) {
######## PKDECOMPINT ########
if (length(kerpk) > 1) {
# set number of kernels per peak manually
xrd.fit[[s]] <- pkdecompint(xrd.base, intnum = s,
k = kerpk[s], maxiter = fitmaxiter)
} else {
# use number of kernels determined by baselinefit()
xrd.fit[[s]] <- pkdecompint(xrd.base, intnum = s,
k = xrd.base$npks[s], maxiter = fitmaxiter)
}
# Setup the dataframe that makes up the peak table
for (kernel in 1:xrd.fit[[s]]$num.ker) {
xrd.fit.parpk <- rbind(xrd.fit.parpk,
data.frame(peak = factor(xrd.fit[[s]]$intnr),
kernel = factor(kernel),
x = xrd.fit[[s]]$parpks[kernel, "loc"],
height = xrd.fit[[s]]$parpks[kernel, "height"],
area = xrd.fit[[s]]$parpks[kernel, "intens"],
fwhm = xrd.fit[[s]]$parpks[kernel, "FWHM"],
m = xrd.fit[[s]]$parpks[kernel, "m"],
accept = xrd.fit[[s]]$accept))
xrd.fit.fitpk <- rbind(xrd.fit.fitpk,
data.frame(peak = factor(peaks[s]),
kernel = factor(kernel),
x = xrd.fit[[s]]$x,
y = xrd.fit[[s]]$fitpk[kernel, ]))
}
xrd.nobasl <- rbind(xrd.nobasl,
data.frame(peak = factor(peaks[s]),
x = xrd.fit[[s]]$x,
y = xrd.fit[[s]]$y))
}
return(list(xrd.base = xrd.base,
xrd.peaks = xrd.pks,
xrd.fit.parpk = xrd.fit.parpk,
xrd.fit.fitpk = xrd.fit.fitpk,
xrd.nobasl = xrd.nobasl))
}

@ -0,0 +1,63 @@
xrdpkWrapper <-
function(data.exp, run, override = FALSE,
kerpk = 1, fitmaxiter = 50, gam = 1.0, scl.factor = 1.2, maxwdth=5.0) {
print("... Started xrdpkWrapper")
# check if xrdpk has already completed successfully for the current job
current.dirname <- getwd()
print(current.dirname)
current.filename <- "xrd-peak-data.rda"
xrddatafile <- paste(current.dirname, current.filename, sep = "/")
if (file.exists(xrddatafile) && !override) {
print("... Started if-clause 1")
# File already exists
# return the data using load() or data()
load(file = xrddatafile)
if (run > length(xrdres)) {
print("... Started if-clause 1:1")
# then it does not really exist
xrdres[[run]] <- xrdpk(data.exp,
kerpk = kerpk,
fitmaxiter = fitmaxiter,
gam = gam,
scl.factor = scl.factor,
maxwdth = maxwdth)
save(xrdres, file = xrddatafile)
print("... Ended if-clause 1:1")
}
print("... Ended if-clause 1")
return(xrdres)
} else {
print("... Started else-clause 1")
if (!exists("xrdres")) {
xrdres <- list()
print("... xrdres list created")
}
# Need to call xrdpk() and save its results to file as above
xrdres[[run]] <- xrdpk(data.exp,
kerpk = kerpk,
fitmaxiter = fitmaxiter,
gam = gam,
scl.factor = scl.factor,
maxwdth = maxwdth)
save(xrdres, file = xrddatafile)
print("... Ended else-clause 1")
return(xrdres)
}
}

@ -0,0 +1,6 @@
# Function loads R-data file into a variable instead of into the workspace
# Works well when the R-data file contains only ONE variable
# NOT TESTED for when the R-data file contains many variables
LoadRData2Variable <- function(FullPathToRData) {
return(eval(parse(text = load(FullPathToRData))))
}
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