R/divergeZimage.R

In glotaran/TIMP: Fitting Separable Nonlinear Models in Spectroscopy and Microscopy

"divergeZimage" <- function(ob, out = FALSE,
                            file = "divergeZimage.pdf",
                            lin = 1, title = "", center = 0,
                            x2 = vector(), x = vector(),
                            plainmat = FALSE, ylab = "wavelength (nm)",
                            xlab = "time (ns)") {
  oldpar <- par(no.readonly = TRUE)
  on.exit(par(oldpar))
  if (out) {
    pdf(file)
  }
  if (!plainmat) {
    x2 <- ob@x2
    x <- ob@x
    psi.df <- ob@psi.df
  } else {
    psi.df <- ob
  }

  xnew <- linloglines(x, mu = 0, alpha = lin)
  newlab <- linlogtics(x, mu = 0, alpha = lin)
  m <- par("mar")
  par(mar = c(m[1:3], 6))
  st <- ceiling((max(psi.df) - min(psi.df)) / 100)
  br <- seq(floor(min(psi.df)), ceiling(max(psi.df)), by = st)
  zpt <- which(br == center)
  negbr <- 1:(zpt - 1)
  posbr <- zpt:length(br)
  cl <- c(
    sequential_hcl(length(negbr) - 1, h = 260),
    rev(sequential_hcl(length(posbr), h = 0))
  )
  image(xnew, x2,
    breaks = br, col = cl,
    psi.df, ylab = ylab, xaxt = "n",
    main = title, xlab = xlab
  )
  axis(1, at = newlab[, 1], labels = newlab[, 2])
  labs <- pretty(br)
  labsp <- vector()
  for (i in 1:length(br)) {
    labsp <- append(labsp, if (br[i] %in% pretty(br)) br[i] else NA)
  }
  image.plot(xnew, x2, psi.df,
    ylab = ylab,
    legend.only = TRUE, breaks = br, col = cl,
    lab.breaks = labsp
  )
  if (out) {
    dev.off()
  }
}