R/set_plotter_spec.R

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

setMethod(
  "plotter", signature(model = "spec"),
  function(model, multimodel, multitheta, plotoptions) {
    oldpar <- par(no.readonly = TRUE)
    on.exit(par(oldpar))
    if (plotoptions@residplot) {
      plotResids(multimodel, multitheta, plotoptions)
    }
    if (plotoptions@residtraces) {
      plotTracesResids(multimodel, multitheta, plotoptions)
    }
    if (!plotoptions@notraces) {
      plotSpectraSuper(multimodel, multitheta, plotoptions)
    }
    if (plotoptions@writefit || plotoptions@writefitivo) {
      writeFit(multimodel, multitheta, plotoptions)
    }
    plotoptions@addest <- c("specpar")
    plotoptions@paropt <- par(
      mgp = c(2, 1, 0),
      mar = c(3, 3, 3, 2), oma = c(1, 0, 4, 0),
      mfrow = c(
        plotoptions@summaryplotrow,
        plotoptions@summaryplotcol
      )
    )

    if (dev.cur() != 1) {
      dev.new()
    }
    par(
      mgp = c(2, 1, 0),
      mar = c(3, 3, 3, 2), oma = c(1, 0, 4, 0),
      mfrow = c(
        plotoptions@summaryplotrow,
        plotoptions@summaryplotcol
      )
    )
    nt <- model@nt
    nl <- model@nl
    x <- model@x
    x2 <- model@x2
    m <- multimodel@modellist
    t <- multitheta
    resultlist <- multimodel@fit@resultlist
    conmax <- list()
    conlist <- getSpecList(multimodel, t)

    if (plotoptions@adddataimage) {
      for (i in 1:length(m)) {
        datarev <- t(apply(m[[i]]@psi.df, 2, rev))
        xr <- rev(m[[i]]@x)
        x2lab <- xr[seq(1, length(xr), length = 10)]
        x2at <- m[[i]]@x[seq(1, length(xr), length = 10)]
        image(
          x = m[[i]]@x2,
          y = m[[i]]@x,
          z = datarev,
          ylab = plotoptions@xlab,
          yaxt = "n",
          main = "Data",
          xlab = plotoptions@ylab,
          col = tim.colors()
        )
        axis(2, at = x2at, labels = x2lab)
      }
    }

    for (i in 1:length(m)) {
      contoplot <- conlist[[i]]
      matplot(m[[i]]@x, contoplot,
        type = "l",
        add = !(i == 1), lty = i, ylab = "concentration",
        xlab = plotoptions@xlab, main = "Concentrations"
      )
    }
    # SPECTRA
    specList <- vector("list", length(m))
    for (i in 1:length(m)) {
      if (m[[i]]@timedep) {
        specpar <- specparF(t[[i]]@specpar, m[[i]]@x[1],
          1, m[[i]]@specref, m[[i]]@specdispindex,
          t[[i]]@specdisppar,
          parmufunc = m[[i]]@parmufunc
        )
      } else {
        specpar <- t[[i]]@specpar
      }

      spectra <- doClpConstr(specModel(specpar, m[[i]]),
        clp_ind = 1,
        clpCon = m[[i]]@clpCon, clpequ = t[[i]]@clpequ,
        num_clpequ = length(m[[i]]@clpequspec),
        usecompnames0 = m[[i]]@usecompnames0,
        usecompnamesequ = m[[i]]@usecompnamesequ
      )
      specList[[i]] <- spectra
      matplot(m[[i]]@x2, spectra,
        type = "l",
        main = "Spectra",
        xlab = plotoptions@ylab, ylab = "amplitude", lty = i,
        add = !(i == 1)
      )
    }
    for (i in 1:length(m)) {
      matplot(m[[i]]@x2, normdat(specList[[i]]),
        type = "l",
        main = "Normalized spectra", xlab = plotoptions@ylab,
        ylab = "amplitude", lty = i, add = !(i == 1)
      )
    }
    # RESIDUALS
    # make a list of resid matrix
    residlist <- svdresidlist <- list()
    for (i in 1:length(m)) {
      residuals <- matrix(
        nrow = m[[i]]@nt,
        ncol = m[[i]]@nl
      )
      for (j in 1:length(resultlist[[i]]@resid)) {
        residuals[j, ] <- resultlist[[i]]@resid[[j]]
      }
      svdresidlist[[length(svdresidlist) + 1]] <- doSVD(residuals, 2, 2)
      residlist[[length(residlist) + 1]] <- residuals
    }
    limd <- max(max(residlist[[1]]), abs(min(residlist[[1]])))

    if (!(any(diff(x) <= 0) || any(diff(x2) <= 0))) {
      image(x, x2, residlist[[1]],
        xlab = plotoptions@xlab,
        ylab = plotoptions@ylab, main = "Residuals Dataset 1",
        zlim = c(-limd, limd), col = diverge_hcl(40,
          h = c(0, 120), c = 60,
          l = c(45, 90), power = 1.2
        )
      )
    }
    if (nt > 1 && nl > 1) {
      matplot(x, svdresidlist[[1]]$left,
        type = "l",
        main = "Left sing. vectors residuals ", log = "x", xlab =
          plotoptions@xlab, col = 1, ylab = plotoptions@ylab
      )
      if (length(m) > 1) {
        for (i in 2:length(m)) {
          matlines(m[[i]]@x,
            svdresidlist[[i]]$left,
            log = "x",
            type = "l", col = i
          )
        }
      }
      matplot(x2, t(svdresidlist[[1]]$right),
        type = "l",
        main = "Right sing. vectors residuals ", xlab = plotoptions@xlab,
        col = 1, ylab = plotoptions@ylab
      )
      if (length(m) > 1) {
        for (i in 2:length(m)) {
          matlines(m[[i]]@x2,
            t(svdresidlist[[i]]$right),
            type = "l", col = i
          )
        }
      }
      plot(1:length(svdresidlist[[1]]$values),
        log10(svdresidlist[[1]]$values),
        ylab = plotoptions@ylab,
        main = "Sing. values residuals", type = "b", xlab = ""
      )
      if (length(m) > 1) {
        for (i in 2:length(m)) {
          lines(1:length(svdresidlist[[i]]$values),
            log10(svdresidlist[[i]]$values),
            type = "b", col = i
          )
        }
      }
    }
    # DATA
    # make a list of svd data

    svddatalist <- list()
    for (i in 1:length(m)) {
      svddatalist[[length(svddatalist) + 1]] <- doSVD(
        multimodel@data[[i]]@psi.df, 2, 2
      )
    }
    if (nt > 1 && nl > 1) {
      matplot(x, svddatalist[[1]]$left,
        type = "l",
        main = "Left sing. vectors data", log = "x", xlab = plotoptions@xlab,
        col = 1, ylab = plotoptions@ylab
      )
      if (length(m) > 1) {
        for (i in 2:length(m)) {
          matlines(m[[i]]@x,
            svddatalist[[i]]$left,
            log = "x",
            type = "l", col = i
          )
        }
      }
      matplot(x2, t(svddatalist[[1]]$right),
        type = "l", ylab = "",
        main = "Right sing. vectors data", xlab = plotoptions@ylab, col = 1
      )
      if (length(m) > 1) {
        for (i in 2:length(m)) {
          matlines(m[[i]]@x2,
            t(svddatalist[[i]]$right),
            type = "l", col = i
          )
        }
      }
      plot(1:length(svddatalist[[1]]$values),
        log10(svddatalist[[1]]$values),
        ylab = "",
        main = "Sing. values data", type = "b", xlab = ""
      )
      if (length(m) > 1) {
        for (i in 2:length(m)) {
          lines(1:length(svddatalist[[i]]$values),
            log10(svddatalist[[i]]$values),
            type = "b", col = i
          )
        }
      }
    }
    # PLOT DSCALING PER CLP

    for (i in 1:length(m)) {
      pl <- FALSE
      if (length(m[[i]]@dscalspec$perclp) != 0) {
        if (m[[i]]@dscalspec$perclp) {
          if (!pl) {
            plot(m[[i]]@x2, t[[i]]@drel,
              main = "Dataset scaling per clp", xlab = plotoptions@ylab,
              ylab = "", type = "l"
            )
            pl <- TRUE
          } else {
            lines(m[[i]]@x2, t[[i]]@drel, type = "l", col = i)
          }
        }
      }
    }
    if (length(plotoptions@title) != 0) {
      tit <- plotoptions@title
      if (plotoptions@addfilename) tit <- paste(tit, m[[i]]@datafile)
    } else {
      tit <- ""
      if (plotoptions@addfilename) tit <- paste(tit, m[[i]]@datafile)
    }
    mtext(tit, side = 3, outer = TRUE, line = 1)
    par(las = 2)
    # MAKE PS
    if (dev.interactive() && length(plotoptions@makeps) != 0) {
      if (plotoptions@output == "pdf") {
        pdev <- pdf
      } else {
        pdev <- postscript
      }
      dev.print(
        device = pdev,
        file = paste(plotoptions@makeps,
          "_summary.ps", plotoptions@output,
          sep = ""
        )
      )
    }
    par(mfrow = c(plotoptions@summaryplotrow, 1), new = TRUE)
    writeEst(multimodel, multitheta, plotoptions)
    # TODO: replace functionality provided by displayEst
    displayEst(plotoptions)

    if (plotoptions@plotkinspec) {
      plotClp(multimodel, t, plotoptions)
    }
  }
)