R/PLOT-nmr.data.object.R

In jmstrat/NMR.Utils: Importing and processing Bruker NMR data

#' Plot ex situ NMR data
#'
#' This function is used to plot ex situ NMR data.
#' @param x An nmr.data.object
#' @param ... Additional parameters passed to \code{\link[jms.classes]{plot.jms.data.object}}
#' @export
plot.nmr.data.object <- function(x, ..., axes=1, xlim=NULL, div=2) {
  if (any_complex(x)) x <- makeReal(x)
  if (any(is.null(xlim))) xlim <- range(x[, jms.classes::xcol(x)][is.finite(x[, jms.classes::xcol(x)])])
  xlim <- rev(range(xlim))
  NextMethod(x, axes=axes, xlim=xlim, div=div, ...)
}

#' @export
lines.nmr.data.object <- function(x, ...) {
  if (any_complex(x)) x <- makeReal(x)
  # Normalise
  m <- attr(x, "mass")
  if (is.null(m)) m <- 1
  ns <- attr(x, "mass")
  if (is.null(ns)) ns <- 1
  x <- x / m / ns
  NextMethod(x, ...)
}

#' Plot ex situ NMR data
#'
#' This function is used to plot ex situ NMR data.
#' @param x An nmr.data.object
#' @param ... Additional parameters passed to \code{\link[jms.classes]{iplot.jms.data.object}}
#' @export
iplot.nmr.data.object <- function(..., axes=1, offset=NULL, xlim=NULL, ylim=NULL, y2lim=NULL,
                                  xlab=NULL, ylab=NULL, y2lab=NULL, col=NULL, lwd=NULL,
                                  pch=NULL, labels=NULL, group=NULL) {
  data <- list(...)
  warnedM <- warnedNS <- F

  if (length(data) > 1) {
    for (i in 1:length(data)) {
      m <- attr(data[[i]], "mass")
      if (is.null(m)) {
        m <- 1
        if (!warnedM) {
          warning("Data are not normalised by mass")
          warnedM <- T
        }
      }
      m <- as.numeric(m)
      ns <- attr(data[[i]], "ns")
      if (is.null(ns)) {
        ns <- 1
        if (!warnedNS) {
          warning("Data are not normalised by ns")
          warnedNS <- T
        }
      }
      ns <- as.numeric(ns)
      if (any_complex(data[[i]])) data[[i]] <- makeReal(data[[i]])
      data[[i]] <- data[[i]] / m / ns
    }
  } else {
    if (any_complex(data[[1]])) data[[1]] <- makeReal(data[[1]])
  }

  data <- jms.classes::combine(unname(data), interpolate=TRUE)

  if (any(is.null(xlim))) {
    xlim <- range(data[, jms.classes::xcol(data)][is.finite(data[, jms.classes::xcol(data)])])
  }
  xlim <- rev(range(xlim))
  if (!length(labels)) {
    dots <- substitute(list(...))[-1]
    labels <- c(sapply(dots, deparse))
    if (object.size(labels) > 1000) labels <- NULL
  }

  args <- list(data,
    axes=axes, offset=offset, xlim=xlim,
    ylim=ylim, y2lim=y2lim, xlab=xlab, ylab=ylab,
    y2lab=y2lab, col=col, lwd=lwd, pch=pch,
    labels=labels, group=group
  )


  do.call(jms.classes:::iplot.jms.data.object, args[!sapply(args, is.null)])
  # NextMethod(data, axes=axes, xlim=xlim)
}