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#'Plot a score along the forecast time with its confidence interval
#'
#'Plot the correlation (\code{Corr()}), the root mean square error
#'(\code{RMS()}) between the forecast values and their observational
#'counterpart, the slope of their trend (\code{Trend()}), the
#'InterQuartile range, maximum-mininum, standard deviation or median absolute
#'Deviation of the ensemble members (\code{Spread()}), or the ratio between
#'the ensemble spread and the RMSE of the ensemble mean (\code{RatioSDRMS()})
#'along the forecast time for all the input experiments on the same figure
#'with their confidence intervals.
#'
#'@param var Matrix containing any Prediction Score with dimensions:\cr
#' (nexp/nmod, 3/4 ,nltime)\cr
#' or (nexp/nmod, nobs, 3/4 ,nltime).
#'@param toptitle Main title, optional.
#'@param ytitle Title of Y-axis, optional.
#'@param monini Starting month between 1 and 12. Default = 1.
#'@param freq 1 = yearly, 12 = monthly, 4 = seasonal, ... Default = 12.
#'@param nticks Number of ticks and labels on the x-axis, optional.
#'@param limits c(lower limit, upper limit): limits of the Y-axis, optional.
#'@param listexp List of experiment names, optional.
#'@param listobs List of observation names, optional.
#'@param biglab TRUE/FALSE for presentation/paper plot. Default = FALSE.
#'@param hlines c(a,b, ..) Add horizontal black lines at Y-positions a,b, ...\cr
#' Default = NULL.
#'@param leg TRUE/FALSE if legend should be added or not to the plot.
#' Default = TRUE.
#'@param siglev TRUE/FALSE if significance level should replace confidence
#' interval.\cr
#' Default = FALSE.
#'@param sizetit Multiplicative factor to change title size, optional.
#'@param show_conf TRUE/FALSE to show/not confidence intervals for input
#' variables.
#'@param fileout Name of output file. Extensions allowed: eps/ps, jpeg, png,
#' pdf, bmp and tiff. The default value is NULL.
#'@param width File width, in the units specified in the parameter size_units
#' (inches by default). Takes 8 by default.
#'@param height File height, in the units specified in the parameter
#' size_units (inches by default). Takes 5 by default.
#'@param size_units Units of the size of the device (file or window) to plot
#' in. Inches ('in') by default. See ?Devices and the creator function of the
#' corresponding device.
#'@param res Resolution of the device (file or window) to plot in. See
#' ?Devices and the creator function of the corresponding device.
#'@param ... Arguments to be passed to the method. Only accepts the following
#' graphical parameters:\cr
#' adj ann ask bg bty cex.sub cin col.axis col.lab col.main col.sub cra crt
#' csi cxy err family fg fig font font.axis font.lab font.main font.sub
#' lheight ljoin lmitre mar mex mfcol mfrow mfg mkh oma omd omi page pch plt
#' smo srt tck tcl usr xaxp xaxs xaxt xlog xpd yaxp yaxs yaxt ylbias ylog \cr
#' For more information about the parameters see `par`.
#'
#'@details
#'Examples of input:\cr
#'Model and observed output from \code{Load()} then \code{Clim()} then
#'\code{Ano()} then \code{Smoothing()}:\cr
#'(nmod, nmemb, nsdate, nltime) and (nobs, nmemb, nsdate, nltime)\cr
#'then averaged over the members\cr
#'\code{Mean1Dim(var_exp/var_obs, posdim = 2)}:\cr
#'(nmod, nsdate, nltime) and (nobs, nsdate, nltime)\cr
#'then passed through\cr
#' \code{Corr(exp, obs, posloop = 1, poscor = 2)} or\cr
#' \code{RMS(exp, obs, posloop = 1, posRMS = 2)}:\cr
#' (nmod, nobs, 3, nltime)\cr
#'would plot the correlations or RMS between each exp & each obs as a function
#'of the forecast time.
#'
#'@examples
#'# Load sample data as in Load() example:
#'example(Load)
#'clim <- Clim(sampleData$mod, sampleData$obs)
#'ano_exp <- Ano(sampleData$mod, clim$clim_exp)
#'ano_obs <- Ano(sampleData$obs, clim$clim_obs)
#'runmean_months <- 12
#'smooth_ano_exp <- Smoothing(data = ano_exp, runmeanlen = runmean_months)
#'smooth_ano_obs <- Smoothing(data = ano_obs, runmeanlen = runmean_months)
#'dim_to_mean <- 'member' # mean along members
#'required_complete_row <- 'ftime' # discard startdates for which there are NA leadtimes
#'leadtimes_per_startdate <- 60
#'corr <- Corr(MeanDims(smooth_ano_exp, dim_to_mean),
#' MeanDims(smooth_ano_obs, dim_to_mean),
#' comp_dim = required_complete_row,
#' limits = c(ceiling((runmean_months + 1) / 2),
#' leadtimes_per_startdate - floor(runmean_months / 2)))
#'# Combine corr results for plotting
#'corr_combine <- abind::abind(corr$conf.lower, corr$corr, corr$conf.upper, corr$p.val, along = 0)
#'corr_combine <- Reorder(corr_combine, c(2, 3, 1, 4))
#'\donttest{
#'PlotVsLTime(corr_combine, toptitle = "correlations", ytitle = "correlation",
#' monini = 11, limits = c(-1, 2), listexp = c('CMIP5 IC3'),
#' listobs = c('ERSST'), biglab = FALSE, hlines = c(-1, 0, 1))
#' }
#'
#'@importFrom grDevices dev.cur dev.new dev.off
#'@importFrom stats ts
#'@export
PlotVsLTime <- function(var, toptitle = '', ytitle = '', monini = 1, freq = 12,
nticks = NULL, limits = NULL,
listexp = c('exp1', 'exp2', 'exp3'),
listobs = c('obs1', 'obs2', 'obs3'), biglab = FALSE, hlines = NULL,
leg = TRUE, siglev = FALSE, sizetit = 1, show_conf = TRUE,
fileout = NULL,
width = 8, height = 5, size_units = 'in', res = 100, ...) {
# Process the user graphical parameters that may be passed in the call
## Graphical parameters to exclude
excludedArgs <- c("cex", "cex.axis", "cex.lab", "cex.main", "col", "fin", "lab", "las", "lend", "lty", "lwd", "mai", "mgp", "new", "pin", "ps", "pty")
userArgs <- .FilterUserGraphicArgs(excludedArgs, ...)
# If there is any filenames to store the graphics, process them
# to select the right device
if (!is.null(fileout)) {
deviceInfo <- .SelectDevice(fileout = fileout, width = width, height = height, units = size_units, res = res)
saveToFile <- deviceInfo$fun
fileout <- deviceInfo$files
}
#
# Get some arguments
# ~~~~~~~~~~~~~~~~~~~~
#
if (length(dim(var)) == 3) {
var <- InsertDim(var, posdim = 2, lendim = 1)
} else if (length(dim(var)) != 4) {
stop("Parameter 'var' should have 3 or 4 dimensions: c(n. exp[, n. obs], 3/4, n. lead-times)")
}
nleadtime <- dim(var)[4]
nexp <- dim(var)[1]
nobs <- dim(var)[2]
if (is.null(limits) == TRUE) {
if (all(is.na(var > 0))) {
ll <- ul <- 0
} else {
ll <- min(var, na.rm = TRUE)
ul <- max(var, na.rm = TRUE)
}
if (biglab) {
ul <- ul + 0.4 * (ul - ll)
} else {
ul <- ul + 0.3 * (ul - ll)
}
} else {
ll <- limits[1]
ul <- limits[2]
}
lastyear <- (monini + (nleadtime - 1) * 12 / freq - 1) %/% 12
lastmonth <- (monini + (nleadtime - 1) * 12 / freq - 1) %% 12 + 1
empty_ts <- ts(start = c(0000, (monini - 1) %/% (12 / freq) + 1),
end = c(lastyear, (lastmonth - 1) %/% (12 / freq) + 1),
frequency = freq)
empty <- array(dim = length(empty_ts))
#
# Define some plot parameters
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
if (is.null(nticks)) {
if (biglab) {
nticks <- 5
} else {
nticks <- 10
}
}
labind <- seq(1, nleadtime, max(nleadtime %/% nticks, 1))
months <- c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep",
"Oct", "Nov", "Dec")
labyear <- ((labind - 1) * 12 / freq + monini - 1) %/% 12
labmonth <- months[((labind - 1) * 12 / freq + monini -1 ) %% 12 + 1]
for (jx in 1:length(labmonth)) {
y2o3dig <- paste("0", as.character(labyear[jx]), sep = "")
labmonth[jx] <- paste(labmonth[jx], "\nYr ", substr(y2o3dig, nchar(y2o3dig)
- 1, nchar(y2o3dig)), sep = "")
}
color <- c("red1", "dodgerblue1", "green1", "orange1", "lightblue1",
"deeppink1", "mediumpurple1", "lightgoldenrod1", "olivedrab1",
"mediumorchid1")
type <- c(1, 3, 2, 4)
thickness <- array(dim = c(4, 4))
thickness[, 1] <- c(1, 2, 1, 1.5)
thickness[, 2] <- c(8, 12, 8, 10)
thickness[, 3] <- thickness[, 1]
thickness[, 4] <- c(4, 6, 4, 5)
if (siglev == TRUE) {
lines <- c("n", "l", "n", "l")
} else {
lines <- c("l", "l", "l", "n")
}
#
# Define plot layout
# ~~~~~~~~~~~~~~~~~~~~
#
# Open connection to graphical device
if (!is.null(fileout)) {
saveToFile(fileout)
} else if (names(dev.cur()) == 'null device') {
dev.new(units = size_units, res = res, width = width, height = height)
}
# Load the user parameters
par(userArgs)
if (biglab) {
par(mai = c(1.25, 1.4, 0.5, 1), mgp = c(4, 2.5, 0))
par(cex = 1.3, cex.lab = 2, cex.axis = 1.8)
cexmain <- 2.2
legsize <- 1.5
} else {
par(mai = c(1, 1.1, 0.5, 0), mgp = c(3, 1.8, 0))
par(cex = 1.3, cex.lab = 1.5, cex.axis = 1.1)
cexmain <- 1.5
legsize <- 1
}
plot(empty, ylim = c(ll, ul), xlab = "Time (months)", ylab = ytitle,
main = toptitle, cex.main = cexmain*sizetit, axes = FALSE)
axis(1, at = labind, labels = labmonth)
axis(2)
box()
if (is.null(hlines) != TRUE) {
for (jy in 1:length(hlines)) {
par(new = TRUE)
abline(h = hlines[jy])
}
}
#
# Loop on experimental & observational data
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
legendnames <- array(dim = nobs * nexp)
legendthick <- array(dim = nobs * nexp)
legendsty <- array(dim = nobs * nexp)
legendcol <- array(dim = nobs * nexp)
ind <- 1
if (show_conf == TRUE) {
start_line <- dim(var)[3]
end_line <- 1
} else {
start_line <- 2
end_line <- 2
}
for (jt in seq(start_line, end_line, -1)) {
ind <- 1
for (jexp in 1:nexp) {
for (jobs in 1:nobs) {
par(new = TRUE)
plot(var[jexp, jobs, jt, ], type = lines[jt], ylim = c(ll, ul),
col = color[jexp], lty = type[jobs], lwd = thickness[jobs, jt],
ylab = "", xlab = "", axes = FALSE)
legendnames[ind] <- paste(listexp[jexp], 'vs', listobs[jobs])
legendthick[ind] <- thickness[jobs, 1] * 3
legendsty[ind] <- type[jobs]
legendcol[ind] <- color[jexp]
ind <- ind + 1
}
}
}
if (leg) {
if (nobs == 1) {
legendnames <- listexp[1:nexp]
}
legend(1, ul, legendnames, lty = legendsty, lwd = legendthick,
col = legendcol, cex = legsize)
}
# If the graphic was saved to file, close the connection with the device
if(!is.null(fileout)) dev.off()
}