tooling for Technical Analysis Equipment wellplate flourescence measurement xlsx sheet csv

time-resolved-fluorescence-well-measurements.R

# run with:
# R --no-save --no-restore --file=time-resolved-fluorescence-well-measurements.R

# Hombrechtikon tooling for Technical Analysis Equipment

library(ggplot2)

filename <- 'measurement.csv'
offset <- 56
stop <- FALSE
wellMarker <- "Cycles / Well"
endMarker <- "End Time:"
testPoints <- 9

# scan file for headers and column count
data <- read.csv2(
  filename,
  skip = offset,
  header = FALSE,
  stringsAsFactors = FALSE
)
columnCount <- length(names(data))
# find all marked wells
headers <- data[,1]
rm(data)
# read rows of wells and their names from all header lines
getWellRows <- function (headers) {
  wellRows <- NULL
  wellRowNames <- NULL
  headersLength <- length(headers);
  stop <- FALSE
  for (headerRow in 1:headersLength) {
    if (! stop) {
      header <- headers[[headerRow]]
      if (header == endMarker) {
        stop <- TRUE
      } else {
        if (header == wellMarker) {
          wellRows <- c(wellRows, headerRow)
        }
      }
    }
  }
  return (wellRows)
}
getWellRowNames <- function (headers) {
  wellRows <- NULL
  wellRowNames <- NULL
  headersLength <- length(headers);
  stop <- FALSE
  for (headerRow in 1:headersLength) {
    if (! stop) {
      header <- headers[[headerRow]]
      if (header == endMarker) {
        stop <- TRUE
      } else {
        if (header == wellMarker) {
          wellRowNames <- c(wellRowNames, headers[[headerRow + 1]])
        }
      }
    }
  }
  return (wellRowNames)
}
wellRows <- getWellRows(headers)
wellRowNames <- getWellRowNames(headers)
# go through all wells
colClasses <- c("character", rep("numeric", columnCount - 1))
wellsCount <- min(length(wellRows), length(wellRowNames))
for (wellRowIndex in 1:wellsCount) {
  wellRow <- wellRows[wellRowIndex]
  wellRowName <- wellRowNames[wellRowIndex]
  wellData <- read.csv2(
    filename,
    skip = offset + wellRow,
    nrows = 4 + testPoints,
    header = TRUE,
    row.names = 1,
    colClasses = colClasses,
    stringsAsFactors = FALSE
  )
  rownames(wellData)[1] <- 'time'
  wellDataT <- data.frame(t(wellData))
  # prepare for rbind distinction
  wellDataT$well <- wellRowName
}

#debug last well
plot <- ggplot() +
        geom_line(data = wellDataT, aes(x = time, y = StDev)) +
        geom_line(data = wellDataT, aes(x = time, y = Mean))

print(plot)