Get elemental data from the Bruker AXS Tracer handheld pXRF

channels.csv

get_pXRF_data.R

#' Get elemental data from the Bruker AXS Tracer handheld pXRF
#' 
#' This function starts with directory of csv files (or a directory
#' of directories) that are the raw output from the 
#' pXRF and returns a list of two dataframes, one with 
#' just the counts per channel for each 
#' run, and one with counts and all the diagnostic details.
#' 
#' @param mydir the full path of the directory containing the 
#' csv files
#' 
#' @example mydata <- get_pXRF_data("C:/Users/marwick/UW-Dropbox/Dropbox/MKII_pXRF_data_SP14/MKII-SW-sec-S-pxrf/140527 Beads")
#'
get_pXRF_data <- function(mydir){
# require(data.table)

myfiles <- list.files(mydir, pattern = '.csv', full.names = TRUE, recursive = TRUE)
# data <- lapply(myfiles, fread)
data <- lapply(myfiles, read.csv)

# make a data frame where each column is one analysis and the colname is the filename

# create empty dataframe to hold the data
# df <- data.table(matrix(nrow=length(data), ncol = nrow(data[[1]])))
df <- data.frame(matrix(nrow=length(data), ncol = nrow(data[[1]])))


# loop through each CSV file and get the counts and put
# them into a column of a single data frame
# for (i in 1:length(myfiles)) {
#   df[i, ] <- as.numeric(as.character((data[[i]][[2]])))
#   print(i) # this loop is very slow with data.table!
# }

for (i in 1:length(myfiles)) {
  df[i,] <- data[[i]]$Bruker.AXS.Handheld.Inc..S1PXRF.Spectrum
  print(i) # it's nice to see the progress...
}

# put the CSV file names as the column names in the new dataframe
colnames(df) <- rownames(data[[1]])
# and as first row to use later
df$filename <- myfiles

# from line 21 - 2068 are the channels, separate them out
channels <- df[,c((which(names(df) %in% 0):ncol(df)))]
rownames(channels) <- df$filename

return(list(channels, df))
}

isolate_channels.R

isolate_channels <- function(){
# isolate and name channels by element
channel_ranges <- read.csv("https://gist.githubusercontent.com/benmarwick/c38a8d4fdef766f19eee/raw/a3ad7be4892bccdb13f26aabf8e55aa3565583b1/channels.csv")
# extract channels to ID elements
channelRangesStartEnd <- channel_ranges[,c(1,4:5)]
# round to whole numbers
channelRangesStartEnd$Chan.Start <- round(channelRangesStartEnd$Chan.Start)
channelRangesStartEnd$Chan.End <- round(channelRangesStartEnd$Chan.End)
return(channelRangesStartEnd)
}