R/pH_rolling_mean.R

In ctriandafillou/flownalysis: Analysis of Yeast Protein Induction and pH by Flow Cytometry

#' Calculate rolling mean of flow cytometry pH timecourse data
#' 
#' Takes a subset of a dataframe that represents a single experiment and calculates a rolling mean on the data with binwidth k.
#'
#' @param dat A dataframe or dataframe subset to act on. Should have a column called pH.m on which the fit will be calculated.
#' @param k Indicates method to use for binwidth. If k is an integer, this will be the number of samples to include in the averaging bin. If k is "auto", the binwidth will be determined for each subset individually, size will be determined by k_val
#' @param k_val Only used if k = "auto"; the percentage of the total number of observations that will be averaged over for each subset
#' @export
#' @return a dataframe with columns "Time" and "fit" representing the rolling mean at each timepoint.


pH_rolling_mean <- function(dat, k="auto", k_val=0.05) {
  y <- dat$pH.m
  if (k == "auto") {
    auto_k <- round(nrow(dat)*k_val)
    if (auto_k %% 2 == 0) {
      auto_k <- auto_k + 1
    }
    print(auto_k)
    fit <- rollmean(y, auto_k, fill = NA)
    x <- dat$Time
  } else {
    fit <- rollmean(y, k, fill = NA)
    x <- dat$Time
  }
  #x <- ifelse(is.integer(k/2), dat$Time[round(k/2):(length(dat$Time)-round(k/2)-1)], dat$Time[round(k/2):(length(dat$Time)-round(k/2))])
  setNames(data.frame(x, fit), c("Time", "fit"))
}