R/AQSysPlot.R

In Hutchr/LLSR: Data Analysis of Liquid-Liquid Systems using R

#' @importFrom dplyr bind_rows
###############################################################################
#' @rdname AQSysPlot
#' @title AQSysPlot
#' @export AQSysPlot
#' @description This functions plot binodal data as a curve in a pre-defined 
#' high quality theme ready for publication.
#' @details The function have a predefined set of ggplot2 features adjusted to 
#' return a high quality picture. 
#' More suitable for plotting fitted data, once binodal data usually determined
#'  through cloudy-phase point will look irregular.
#' 
#' @param dataSET - Binodal Experimental data that will be used in the nonlinear
#'  fit. It might hold multiple systems stacked side-by-side. [type:data.frame]
#' @param Order Defines how the data is organized in the Worksheet. 
#' Use "xy" whether the first column corresponds to the lower phase fraction and
#'  "yx" whether the opposite. [type:string]
#' @param xlbl Plot's Horizontal axis label.
#' @param ylbl Plot's Vertical axis label.
#' @param seriesNames A list of sequential names which will identify each system
#'  provided by the user in the dataSET variable. [type:List]
#' @param save Save the generated plot in the disk using path and filename 
#' provided by the user. Default is False. [type:Logical]
#' @param filename A filename provided by the user to save a given plot. No 
#' default is provided. [type:String]
#' @param HR  Adjust Plot's text to be compatible with High Resolution 
#' size [type:Logical]
#' @param wdir The directory in which the plot file will be saved. [type:String]
#' @param silent save plot file without actually showing it to the user. 
#' Default is FALSE. [type:Logical]
#' @return The plot is returned as a ggplot2 object that can be manipulated 
#' accordingly.
# ' @param maxiter	- A positive integer specifying the maximum number of 
# iterations allowed.
#' @examples
#' # Populating variable dataSET with binodal data
#' dataSET <- peg4kslt[ , 1:2]
#' # Fitting dataSET using Merchuk's function
#' data <- AQSys.data(dataSET, Order = "xy")
#' AQSysPlot(data)
AQSysPlot <- function (dataSET,
                       Order = "xy",
                       xlbl = "",
                       ylbl = "",
                       seriesNames = NULL,
                       save = FALSE,
                       filename = NULL,
                       HR = FALSE,
                       wdir = NULL,
                       silent = FALSE) {
  #
  nSys <- (ncol(dataSET) / 2)
  SysNames <- FALSE
  #
  if ((ncol(dataSET) %% 2) == 0) {
    if (is.null(seriesNames) || !(length(seriesNames) == nSys)) {
      print(paste("The array seriesNames must have", nSys, 
                  "elements. Default names will be used instead."))
      seriesNames <- sapply(seq(1, nSys), function(x) paste("Series", x))
    } else {
      SysNames <- TRUE
    }
    SysList <- list()
    for (i in seq(1, nSys)) {
      SysList[[i]] <- unname(na.exclude(dataSET[, (i * 2 - 1):(i * 2)]))
      names(SysList[[i]]) <- c("X", "Y")
      SysList[[i]]["System"] <- seriesNames[i]
    }
    output <- bind_rows(SysList)
    output_plot <- bndOrthPlot(output, Order, xlbl, ylbl)
    #
    saveConfig(output_plot, save, HR, filename, wdir, silent)
    #
    if (silent == FALSE) {
      print(output_plot)
      invisible(list("data" = SysList, "plot" = output_plot))
    } else {
      invisible(list("data" = SysList, "plot" = output_plot))
    }
  }
  else{
    AQSys.err(9)
  }
}

bndOrthPlot <- function(dataSET, Order, xlbl = "", ylbl = "") {
  #
  # dataSET[, 1:2] <- toNumeric(dataSET, Order)
  #
  xmax <- ceiling(round(max(dataSET[, 1]) / 0.92, 1) / 5) * 5
  ymax <- ceiling(round(max(dataSET[, 2]) / 0.92, 1) / 5) * 5
  #
  outputPLOT <- ggplot() + scale_colour_grey() +
    geom_line(data = dataSET, size = 1, 
              aes_string(color = "System", x = "X", y = "Y")) +
    geom_point(data = dataSET, size = 2,
               aes_string(color = "System", x = "X", y = "Y")) +
    xlab(paste(xlbl,  "(%, m/m)")) +
    ylab(paste(ylbl, "(%, m/m)")) +
    theme_light() +
    theme(
      validate = FALSE,
      plot.margin = unit(c(1, 1, 1, 1), "cm"),
      text = element_text(size = 16),
      legend.position = "top",
      axis.title.y = element_text(vjust = 5),
      axis.title.x = element_text(vjust = -2),
      panel.grid.major = element_line(size = .70, colour = "black"),
      panel.grid.minor = element_line(size = .70),
      panel.border = element_rect(size = .5, colour = "white"),
      axis.text.x = element_text(size = 15),
      axis.text.y = element_text(size = 15),
      axis.line = element_line(colour = 'black', size = 1.25),
      legend.title = element_blank(),
      legend.text = element_text(
        colour = "black",
        size = 12,
        face = "plain"
      )
    ) +
    scale_y_continuous(
      expand = c(0, 0),
      limits = c(0, ymax),
      breaks = seq(0, ymax, by = 5),
      labels = seq(0, ymax, by = 5)
    ) +
    scale_x_continuous(
      expand = c(0, 0),
      limits = c(0, xmax),
      breaks = seq(0, xmax, by = xmax / 10),
      labels = seq(0, xmax, by = xmax / 10)
    )
  #
  return(outputPLOT)
}