R/cytoPlot.R

In optimalFlow: optimalFlow

#' cytoPlot
#'
#' A plot wrapper for cytometries as a mixture of multivariate normals as used in optimalFlowTemplates.
#'
#' @param cytometry.as.mixture A list, where each element contains the parameters of a component of the mixture as a list with entries: mean, cov, weight and type.
#' @param dimensions A vector containing the two variables on which to perform the projection.
#' @param xlim the x limits (x1, x2) of the plot. Note that x1 > x2 is allowed and leads to a ‘reversed axis’. The default value, NULL, indicates that the range of the finite values to be plotted should be used.
#' @param ylim the y limits of the plot.
#' @param xlab a label for the x axis, defaults to a description of x.
#' @param ylab a label for the y axis, defaults to a description of y.
#'
#' @return A two dimensional plot of ellipses containing the 95% of probability for the respectives components of the mixture distribution.
#' @examples
#' database <- buildDatabase(
#'   dataset_names = paste0('Cytometry', c(2:5, 7:9, 12:17, 19, 21)),
#'   population_ids = c('Monocytes', 'CD4+CD8-', 'Mature SIg Kappa', 'TCRgd-'))
#' templates.optimalFlow <-
#'   optimalFlowTemplates(
#'     database = database, templates.number = 5, cl.paral = 1
#'   )
#' cytoPlot(templates.optimalFlow$templates[[3]], dimensions = c(4, 3), xlim = c(0, 8000), ylim = c(0, 8000), xlab = "", ylab = "")
#'
#' @import ellipse
#' @importFrom graphics lines
#' @export
cytoPlot <- function (cytometry.as.mixture, dimensions = c(1,2), xlim = NULL,
                      ylim = NULL, xlab = NULL, ylab = NULL) {
  n.cells <- length(cytometry.as.mixture)
  plot(
    ellipse(
      cytometry.as.mixture[[1]]$cov[dimensions, dimensions],
      centre = cytometry.as.mixture[[1]]$mean[dimensions]
    ),
    xlim = xlim, ylim = ylim, col = 1, type = "l",
    xlab = xlab, ylab = ylab
  )
  for (j in 2:n.cells){
    lines(
      ellipse(
        cytometry.as.mixture[[j]]$cov[dimensions, dimensions],
        centre = cytometry.as.mixture[[j]]$mean[dimensions]
      ),
      col = j
    )
  }
}