R/blc_func.r

In MethodOpt: Advanced Method Optimization for Spectra-Generating Sampling and Analysis Instrumentation

# baseline correction function. Credit to Stephanie Gamble with small modifications made by Ben Luke.

#' @title Baseline correction
#'
#' @description
#' Generates the baseline of the spectra, interpolates between points, and subtracts from the intensity to generate corrected baseline.
#'
#' @param frame data frame of time versus intensity.
#' @param noise strength of the baseline subtraction.
#' @param subtract how much intensity to initially subtract.
#'
#' @return data frame of of data that has been baseline corrected

blc <- function(frame, noise=10^5, subtract=NULL){
  N <- length(frame$TIC)
  if (!(is.null(subtract))){
    if (length(subtract$'TIC')!=length(frame$'TIC')){
      stop('To perform baseline subtractions, samples must be of the same size.')
    }
    else{
      frame$'TIC' <- frame$'TIC'-subtract$'TIC'
    }
  }
  bl <- c(rep(NA,N))
  sig <- c(rep(NA,N))
  win_size <- 100
  if (win_size > N){
    win_size <- 1
  }
  else if (N<10000){
    win_size <- round(N/100)
  }
  points <- c(1:round(N/win_size))
  points <- points[1:(length(points)-1)]*win_size
  for (i in c(1:N)){
    if (i %in% points){
      if (i== points[1]){
        window <- c(1:i+win_size)
      }
      else if (i== points[length(points)]){
        window <- c(i-win_size,N)
      }
      else {
        window <- c((i-win_size):(i+win_size))
      }
      bl[i] <- min(frame$TIC[window])
    }
  }
  bl[1] <- bl[points[1]]
  bl[length(bl)] <- bl[points[length(points)]]
  min <- bl
  bl2 <- bl[is.na(bl)==FALSE]
  bl3 <- bl2+noise
  new_bl <- rep(NA,N)
  new_bl[c(1,points,N)] <- bl3
  new_bl <- zoo::na.approx(new_bl)
  frame$TIC <- frame$TIC-new_bl
  frame$TIC[frame$TIC<0]<- 0

  return(data.frame(time = frame$time, TIC = frame$TIC, baseline = new_bl))

}

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