R/Desc.R

Defines functions .has_color Desc.palette printWrd plot.Desc.factnum plot.Desc.numnum plot.Desc.numfact plot.Desc.factfact plot.Desc.xtabs plot.Desc.matrix plot.Desc.table plot.Desc.xtabs plot.Desc.ts plot.Desc.Date plot.Desc.logical plot.Desc.ordered plot.Desc.integer plot.Desc.factor plot.Desc.character plot.Desc.numeric plot.Desc.default plot.Desc print.Desc.factnum print.Desc.numnum print.Desc.numfact print.Desc.factfact print.Desc.ts print.Desc.Date print.Desc.xtabs print.Desc.table print.Desc.matrix print.Desc.integer print.Desc.ordered print.Desc.character print.Desc.factor print.Desc.logical print.Desc.numeric print.Desc.header print.Desc .LineSep .print.charmatrix calcDesc.bivar calcDesc.matrix calcDesc.table calcDesc.ts calcDesc.Date calcDesc.character calcDesc.factor calcDesc.logical calcDesc.numeric calcDesc.default calcDesc Desc.formula Desc.list Desc.data.frame desc Desc.default Desc.table Desc.Date Desc.logical Desc.ts Desc.character Desc.ordered Desc.labelled Desc.factor Desc.integer Desc.numeric Desc ChisqWarning

Documented in Desc Desc.character Desc.data.frame Desc.Date Desc.default Desc.factor Desc.formula Desc.integer Desc.labelled Desc.list Desc.logical Desc.numeric Desc.ordered Desc.palette Desc.table Desc.ts plot.Desc print.Desc

ChisqWarning <- function(){
  cat(cli::col_red("\nWarning message:\n  Exp. counts < 5: Chi-squared approx. may be incorrect!!\n\n"))
}




#' Describe Data
#' 
#' Produce summaries of various types of variables. Calculate descriptive
#' statistics for x and use Word as reporting tool for the numeric results and
#' for descriptive plots.  The appropriate statistics are chosen depending on
#' the class of x.  The general intention is to simplify the description
#' process for lazy typers and return a quick, but rich summary.
#' 
#' A **2-dimensional table** will be described with it's relative frequencies, a
#' short summary containing the total cases, the dimensions of the table,
#' chi-square tests and some association measures as phi-coefficient,
#' contingency coefficient and Cramer's V. \cr
#' Tables with higher dimensions  will simply be printed as flat table,
#' with marginal sums for the first and for the last dimension.
#' 
#' `Desc` is a **generic function**. It dispatches to one of the methods above
#' depending on the class of its first argument. Typing `?Desc` + TAB at the
#' prompt should present a choice of links: the help pages for each of these
#' `Desc` methods (at least if you're using RStudio, which anyway is
#' recommended). You don't need to use the full name of the method although you
#' may if you wish; i.e., `Desc(x)` is idiomatic R but you can bypass method
#' dispatch by going direct if you wish: `Desc.numeric(x)`.
#' 
#' This function produces a rich description of a **factor**, containing length,
#' number of NAs, number of levels and detailed frequencies of all levels. The
#' order of the frequency table can be chosen between descending/ascending
#' frequency, labels or levels. For ordered factors the order default is
#' `"level"`. Character vectors are treated as unordered factors Desc.char
#' converts x to a factor an processes x as factor.\cr
#' Desc.ordered does nothing more than changing the standard order for the 
#' frequencies to it's intrinsic order, which means order `"level"` 
#' instead of `"desc"` in the factor case.
#' 
#' Description interface for **dates**. We do here what seems reasonable for
#' describing dates. We start with a short summary about length, number of NAs
#' and extreme values, before we describe the frequencies of the weekdays and
#' months, rounded up by a chi-square test.
#' 
#' A **2-dimensional table** will be described with it's relative frequencies, a
#' short summary containing the total cases, the dimensions of the table,
#' chi-square tests and some association measures as phi-coefficient,
#' contingency coefficient and Cramer's V. \cr
#' Tables with higher dimensions will simply be printed as flat table, 
#' with marginal sums for the first and for the last dimension.
#' 
#' Note that `NA`s cannot be handled by this interface, as tables in general come
#' in "as.is", say basically as a matrix without any further information about
#' potentially previously cleared NAs.
#' 
#' Description of a **dichotomous variable**. This can either be a logical vector,
#' a factor with two levels or a numeric variable with only two unique values.
#' The confidence levels for the relative frequencies are calculated by
#' [BinomCI()], method `"Wilson"` on a confidence level defined
#' by `conf.level`. Dichotomous variables can easily be condensed in one
#' graphical representation. Desc for a set of flags (=dichotomous variables)
#' calculates the frequencies, a binomial confidence interval and produces a
#' kind of dotplot with error bars. Motivation for this function is, that
#' dichotomous variable in general do not contain intense information.
#' Therefore it makes sense to condense the description of sets of dichotomous
#' variables.
#' 
#' The **formula interface** accepts the formula operators `+`, `:`,
#' `*`, `I()`, `1` and evaluates any function. The left hand
#' side and right hand side of the formula are evaluated the same way. The
#' variable pairs are processed in dependency of their classes.
#' 
#' `Word` This function is not thought of being directly run by the end user. 
#' It will normally be called automatically, when a pointer to a Word instance 
#' is passed to the function [Desc()].\cr
#' However `DescWrd` takes
#' some more specific arguments concerning the Word output (like `font` or
#' `fontsize`), which can make it necessary to call the function directly.
#' 
#' @aliases 
#' Desc 
#' Desc.default 
#' Desc.data.frame 
#' Desc.list 
#' Desc.formula
#' Desc.numeric 
#' Desc.integer 
#' Desc.factor 
#' Desc.ordered 
#' Desc.character
#' Desc.logical 
#' Desc.Date 
#' Desc.table 
#' print.Desc 
#' plot.Desc
#' 
#' @param x the object to be described. This can be a data.frame, a list, a
#' table or a vector of the classes: numeric, integer, factor, ordered factor,
#' logical.
#' 
#' @param main (character|`NULL`|`NA`), the main title(s).
#' - If `NULL`, the title will be composed as:
#'     - variable name (class(es)),
#'     - resp. number - variable name (class(es)) if the `enum` option 
#'       is set to `TRUE.`
#' -  Use `NA` if no caption should be printed at all.
#' 
#' @param wrd the pointer to a running MS Word instance, as created by
#' [GetNewWrd()] (for a new one) or by [GetCurrWrd()] for an existing
#' one.  All output will then be redirected there. Default is `NULL`,
#' which will report all results to the console.
#' 
#' @param digits integer. With how many digits should the relative frequencies
#' be formatted? Default can be set by 
#' [DescToolsOptions(digits=x)][DescToolsOptions()].
#' 
#' @param maxrows numeric; defines the maximum number of rows in a frequency
#' table to be reported. For factors with many levels it is often not
#' interesting to see all of them. Default is set to 12 most frequent ones
#' (resp. the first ones if `ord` is set to `"levels"` or
#' `"names"`).
#' 
#' For a numeric argument x `maxrows` is the minimum
#' number of unique values needed for a numeric variable to be treated as
#' continuous. If left to its default `NULL`, x will be regarded as
#' continuous if it has more than 12 single values. In this case the list of
#' extreme values will be displayed and the frequency table else.
#' 
#' If `maxrows` is < 1 it will be interpreted as percentage. In this case
#' just as many rows, as the `maxrows` most frequent levels will be
#' shown. Say, if `maxrows` is set to `0.8`, then the number of rows is
#' fixed so, that the highest cumulative relative frequency is the first one
#' going beyond 0.8.
#' 
#' Setting `maxrows` to `Inf` will unconditionally report all values
#' and also produce a plot with type "h" instead of a histogram.
#' 
#' @param ord character out of `"name"` (alphabetical order),
#' `"level"`, `"asc"` (by frequencies ascending), `"desc"` (by
#' frequencies descending) defining the order for a frequency table as used for
#' factors, numerics with few unique values and logicals. Factors (and
#' character vectors) are by default ordered by their descending frequencies,
#' ordered factors by their natural order.
#' 
#' @param rfrq a string with 3 characters, each of them being `1` or
#' `0`, defining which percentages should be reported. The first position
#' is interpreted as total percentages, the second as row percentages and the
#' third as column percentages. "`011`" hence produces a table output with
#' row and column percentages. If set to `NULL` `rfrq` is defined in
#' dependency of `verbose` (`verbose = 1` sets `rfrq` to
#' `"000"` and else to `"111"`, latter meaning all percentages will
#' be reported.) \cr
#' Applies only to tables and is ignored else. 
#' 
#' @param margins a vector, consisting out of 1 and/or 2. Defines the margin
#' sums to be included. Row margins are reported if margins is set to 1. Set it
#' to 2 for column margins and c(1,2) for both. \cr
#' Default is `NULL` (none).\cr 
#' Applies only to tables and is ignored else.
#' 
#' @param verbose integer out of `c(2, 1, 3)` defining the verbosity of
#' the reported results. 2 (default) means medium, 1 less and 3 extensive
#' results. \cr
#' Applies only to tables and is ignored else.
#' 
#' @param conf.level confidence level of the interval. If set to `NA` no
#' confidence interval will be calculated. Default is 0.95.
#' 
#' @param dprobs,mprobs a vector with the probabilities for the Chi-Square test
#' for days, resp. months, when describing a `Date` variable.  If this is
#' left to `NULL` (default) then a uniform distribution will be used for
#' days and a monthdays distribution in a non leap year (p = c(31/365, 28/365,
#' 31/365, ...)) for the months. \cr
#' Applies only to `Dates` and is ignored else.
#' 
#' @param enum logical, determining if in data.frames and lists a sequential
#' number should be included in the main title. Default is TRUE. The reason for
#' this option is, that if a Word report with enumerated headings is created,
#' the numbers may be redundant or inconsistent.
#' 
#' @param plotit logical. Should a plot be created? The plot type will be
#' chosen according to the classes of variables (roughly following a
#' numeric-numeric, numeric-categorical, categorical-categorical logic).
#' Default can be defined by option `plotit`, if it does not exist then
#' it's set to `FALSE`.
#' 
#' @param sep character. The separator for the title. By default a line of
#' `"-"` for the current width of the screen `(options("width"))`
#' will be used.
#' 
#' @param nolabel logical, defining if labels (defined as attribute with the
#' name `label`, as done by `Label`) should be plotted.
#' 
#' @param formula a formula of the form `lhs ~ rhs` where `lhs` gives
#' the data values and rhs the corresponding groups.
#' 
#' @param data an optional matrix or data frame containing the variables in the
#' formula `formula`.  By default the variables are taken from
#' `environment(formula)`.
#' 
#' @param subset an optional vector specifying a subset of observations to be
#' used.
#' 
#' @param nomain logical, determines if the main title of the output is printed
#' or not, default is `TRUE`.
#' 
#' @param \dots further arguments to be passed to or from other methods.
#'       For the internal default method these can include: 
#'    \describe{
#'  
#'    \item{`p`}{a vector of probabilities of the same length of `x`. 
#'    An error is given if any entry of `p` is negative. 
#'    This argument will be passed on to [chisq.test()][stats::chisq.test()].
#'    Default is `rep(1/length(x), length(x))`.}
#'    
#'    \item{`add_ni`}{logical. Indicates if the group length should be
#'    displayed in the boxplot.}
#'    
#'    \item{`smooth`}{character, either "loess" or "smooth.spline" defining
#'    the type of smoother to be used in num ~ num plots. Default is "loess" for 
#'    n < 500 and "smooth.spline" otherwise.}
#'    }
#' 
#' @return A list containing the following components: 
#' 
#' \item{length}{the length of the vector (n + NAs).}
#' \item{n}{the valid entries (NAs are excluded)}
#' \item{NAs}{number of NAs} 
#' \item{unique}{number of unique values. }
#' \item{0s}{number of zeros}
#' \item{mean}{arithmetic mean}
#' \item{MeanSE}{standard error of the mean, as calculated by [MeanSE()].} 
#' \item{quant}{a table of quantiles, as calculated by
#'       [quantile(x, probs = c(.05,.10,.25,.5,.75,.9,.95), na.rm = TRUE)][stats::quantile()].
#'       }
#' \item{sd}{standard deviation}
#' \item{vcoef}{coefficient of variation: `mean(x)` / `sd(x)`.}
#' \item{mad}{median absolute deviation ([stats::mad()]).}
#' \item{IQR}{interquartile range }
#' \item{skew}{skewness, as calculated by [Skew()].}
#' \item{kurt}{kurtosis, as calculated by [Kurt()].}
#' \item{highlow}{the lowest and the highest values, reported with their
#'      frequencies in brackets, if > 1.}
#' \item{frq}{a data.frame of absolute and  relative frequencies given by
#'       [Freq()] if `maxlevels` > unique values in the vector.}
#' 
#' @author Andri Signorell <andri@@signorell.net>
#' 
#' @seealso 
#' [base::summary()], [base::plot()]
#' 
#' @concept Desc
#' @family Statistical summary functions
#' @keywords print univar multivariate
#' 
#' 
#' @export
#' 
#' @examples
#' 
#' opt <- DescToolsOptions()
#'
#' # implemented classes:
#' Desc(d.pizza$wrongpizza)               # logical
#' Desc(d.pizza$driver)                   # factor
#' Desc(d.pizza$quality)                  # ordered factor
#' Desc(as.character(d.pizza$driver))     # character
#' Desc(d.pizza$week)                     # integer
#' Desc(d.pizza$delivery_min)             # numeric
#' Desc(d.pizza$date)                     # Date
#'
#' Desc(d.pizza)
#'
#' Desc(d.pizza$wrongpizza, main="The wrong pizza delivered", digits=5)
#'
#' Desc(table(d.pizza$area))                                    # 1-dim table
#' Desc(table(d.pizza$area, d.pizza$operator))                  # 2-dim table
#' Desc(table(d.pizza$area, d.pizza$operator, d.pizza$driver))  # n-dim table
#'
#' # expressions
#' Desc(log(d.pizza$temperature))
#' Desc(d.pizza$temperature > 45)
#'
#' # supported labels
#' Label(d.pizza$temperature) <- "This is the temperature in degrees Celsius
#' measured at the time when the pizza is delivered to the client."
#' Desc(d.pizza$temperature)
#' # try as well:      Desc(d.pizza$temperature, wrd=GetNewWrd())
#'
#' z <- Desc(d.pizza$temperature)
#' print(z, digits=1, plotit=FALSE)
#' # plot (additional arguments are passed on to the underlying plot function)
#' plot(z, main="The pizza's temperature in Celsius", args.hist=list(breaks=50))
#'
#'
#' # formula interface for single variables
#' Desc(~ uptake + Type, data = CO2, plotit = FALSE)
#'
#' # bivariate
#' Desc(price ~ operator, data=d.pizza)                  # numeric ~ factor
#' Desc(driver ~ operator, data=d.pizza)                 # factor ~ factor
#' Desc(driver ~ area + operator, data=d.pizza)          # factor ~ several factors
#' Desc(driver + area ~ operator, data=d.pizza)          # several factors ~ factor
#' Desc(driver ~ week, data=d.pizza)                     # factor ~ integer
#'
#' Desc(driver ~ operator, data=d.pizza, rfrq="111")   # alle rel. frequencies
#' Desc(driver ~ operator, data=d.pizza, rfrq="000",
#'      verbose=3)                                  # no rel. frequencies
#'
#' Desc(price ~ delivery_min, data=d.pizza)              # numeric ~ numeric
#' Desc(price + delivery_min ~ operator + driver + wrongpizza,
#'      data=d.pizza, digits=c(2,2,2,2,0,3,0,0) )
#'
#' Desc(week ~ driver, data=d.pizza, digits=c(2,2,2,2,0,3,0,0))   # define digits
#'
#' Desc(delivery_min + weekday ~ driver, data=d.pizza)
#'
#'
#' # without defining data-parameter
#' Desc(d.pizza$delivery_min ~ d.pizza$driver)
#'
#'
#' # with functions and interactions
#' Desc(sqrt(price) ~ operator : factor(wrongpizza), data=d.pizza)
#' Desc(log(price+1) ~ cut(delivery_min, breaks=seq(10,90,10)),
#'      data=d.pizza, digits=c(2,2,2,2,0,3,0,0))
#'
#' # response versus all the rest
#' Desc(driver ~ ., data=d.pizza[, c("temperature","wine_delivered","area","driver")])
#'
#' # all the rest versus response
#' Desc(. ~ driver, data=d.pizza[, c("temperature","wine_delivered","area","driver")])
#'
#' # pairwise Descriptions
#' p <- CombPairs(c("area","count","operator","driver","temperature","wrongpizza","quality"), )
#' for(i in 1:nrow(p))
#'   print(Desc(formula(gettextf("%s ~ %s", p$X1[i], p$X2[i])), data=d.pizza))
#'
#'
#' # get more flexibility, create the table first
#' tab <- as.table(apply(HairEyeColor, c(1,2), sum))
#' tab <- tab[,c("Brown","Hazel","Green","Blue")]
#'
#' # display only absolute values, row and columnwise percentages
#' Desc(tab, row.vars=c(3, 1), rfrq="011", plotit=FALSE)
#'
#' # do the plot by hand, while setting the colours for the mosaics
#' cols1 <- SetAlpha(c("sienna4", "burlywood", "chartreuse3", "slategray1"), 0.6)
#' cols2 <- SetAlpha(c("moccasin", "salmon1", "wheat3", "gray32"), 0.8)
#' plot(Desc(tab), col1=cols1, col2=cols2)
#'
#' # choose alternative flavours for graphing numeric ~ factor using pipe
#' # (colors are recyled)
#' Desc(temperature ~ driver, data = d.pizza) |> plot(type="dens", col=Pal("Tibco"))
#'
#'
#' # use global format options for presentation
#' Fmt(abs=as.fmt(digits=0, big.mark=""))
#' Fmt(per=as.fmt(digits=2, fmt="%"))
#' Desc(area ~ driver, d.pizza, plotit=FALSE)
#'
#' Fmt(abs=as.fmt(digits=0, big.mark="'"))
#' Fmt(per=as.fmt(digits=3, ldigits=0))
#' Desc(area ~ driver, d.pizza, plotit=FALSE)
#'
#' # plot arguments can be fixed in detail
#' z <- Desc(BoxCox(d.pizza$temperature, lambda = 1.5))
#' plot(z, mar=c(0, 2.1, 4.1, 2.1), args.rug=TRUE, args.hist=list(breaks=50),
#'      args.dens=list(from=0))
#'
#' # The default description for count variables can be inappropriate,
#' # the density curve does not represent the variable well.
#' set.seed(1972)
#' x <- rpois(n = 500, lambda = 5)
#' Desc(x)
#' # but setting maxrows to Inf gives a better plot
#' Desc(x, maxrows = Inf)
#'
#'
#' # Output into word document (Windows-specific example) -----------------------
#' # by simply setting wrd=GetNewWrd()
#' \dontrun{
#'
#'   # create a new word instance and insert title and contents
#'   wrd <- GetNewWrd(header=TRUE)
#'
#'   # let's have a subset
#'   d.sub <- d.pizza[,c("driver", "date", "operator", "price", "wrongpizza")]
#'
#'   # do just the univariate analysis
#'   Desc(d.sub, wrd=wrd)
#' }
#'
#' DescToolsOptions(opt)
#'
#' 
Desc <- function(x, ..., main = NULL, plotit = NULL, wrd = NULL) {
  if (is.null(wrd)) {
    UseMethod("Desc")
  } else {
    if (!IsValidHwnd(wrd)) {
      warning("wrd is not a valid handle to a running Word instance.")
    } else {
      if (is.null(main) && !is.recursive((x))) {
        main <- deparse(substitute(x))
      }

      z <- Desc(x, main = main, plotit = FALSE, ..., wrd = NULL)

      # only if header exists (it does not for single variables!!)
      if (!is.null(z[["_objheader"]])) {
        z[["_objheader"]]["main"] <- gettextf(
          "Describe %s (%s):", paste(deparse(substitute(x)), collapse = " "),
          paste(class(x), collapse = " ,")
        )
      }

      printWrd(x = z, main = main, plotit = plotit, ..., wrd = wrd)
    }
  }
}



#' @rdname Desc
#' @export
Desc.numeric <- function(x, main = NULL,
                         maxrows = NULL,
                         plotit = NULL, sep = NULL, digits = NULL, ...) {
  return(desc(
    x = x,
    xname = deparse(substitute(x)), main = main, digits = digits,
    maxrows = maxrows, plotit = plotit, sep = sep, ...
  ))
}



#' @rdname Desc
#' @export
Desc.integer <- function(x, main = NULL,
                         maxrows = NULL,
                         plotit = NULL, sep = NULL, digits = NULL, ...) {
  return(desc(
    x = x,
    xname = deparse(substitute(x)), main = main, digits = digits,
    maxrows = maxrows, plotit = plotit, sep = sep, ...
  ))
}



#' @rdname Desc
#' @export
Desc.factor <- function(x, main = NULL,
                        maxrows = NULL, ord = NULL,
                        plotit = NULL, sep = NULL, digits = NULL, ...) {
  return(desc(
    x = x,
    xname = deparse(substitute(x)), main = main, digits = digits,
    maxrows = maxrows, ord = ord, plotit = plotit, sep = sep, ...
  ))
}



#' @rdname Desc
#' @export
Desc.labelled <- function(x, main = NULL,
                          maxrows = NULL, ord = NULL,
                          plotit = NULL, sep = NULL, digits = NULL, ...) {
  xname <- deparse(substitute(x))
  lbl <- Label(x)
  x <- factor(x, labels = names(attr(x, "labels")))
  Label(x) <- lbl
  return(desc(
    x = x, xname = xname, main = main, digits = digits,
    maxrows = maxrows, ord = ord, plotit = plotit, sep = sep, ...
  ))
}



#' @rdname Desc
#' @export
Desc.ordered <- function(x, main = NULL,
                         maxrows = NULL, ord = NULL,
                         plotit = NULL, sep = NULL, digits = NULL, ...) {
  return(desc(
    x = x,
    xname = deparse(substitute(x)), main = main, digits = digits,
    maxrows = maxrows, ord = ord, plotit = plotit, sep = sep, ...
  ))
}



#' @rdname Desc
#' @export
Desc.character <- function(x, main = NULL,
                           maxrows = NULL, ord = NULL,
                           plotit = NULL, sep = NULL, digits = NULL, ...) {
  return(desc(
    x = x,
    xname = deparse(substitute(x)), main = main, digits = digits,
    maxrows = maxrows, ord = ord, plotit = plotit, sep = sep, ...
  ))
}



#' @rdname Desc
#' @export
Desc.ts <- function(x, main = NULL,
                    plotit = NULL, sep = NULL, digits = NULL, ...) {
  return(desc(
    x = x,
    xname = deparse(substitute(x)), main = main, digits = digits,
    plotit = plotit, sep = sep, ...
  ))
}



#' @rdname Desc
#' @export
Desc.logical <- function(x, main = NULL,
                         ord = NULL, conf.level = 0.95,
                         plotit = NULL, sep = NULL, digits = NULL, ...) {
  if (is.null(ord)) ord <- "level"
  return(desc(
    x = x,
    xname = deparse(substitute(x)), main = main, digits = digits,
    ord = ord, conf.level = conf.level, plotit = plotit, sep = sep, ...
  ))
}



#' @rdname Desc
#' @export
Desc.Date <- function(x, main = NULL,
                      dprobs = NULL, mprobs = NULL,
                      plotit = NULL, sep = NULL, digits = NULL, ...) {
  return(desc(
    x = x,
    xname = deparse(substitute(x)), main = main, digits = digits,
    dprobs = dprobs, mprobs = mprobs, plotit = plotit, sep = sep, ...
  ))
}



#' @rdname Desc
#' @export
Desc.table <- function(x, main = NULL,
                       conf.level = 0.95, verbose = 2,
                       rfrq = "111", margins = c(1, 2),
                       plotit = NULL, sep = NULL, digits = NULL, ...) {
  return(desc(
    x = x,
    xname = deparse(substitute(x)), main = main, digits = digits,
    conf.level = conf.level, verbose = verbose, rfrq = rfrq, margins = margins,
    plotit = plotit, sep = sep, ...
  ))
}



#' @rdname Desc
#' @export
Desc.default <- function(x, main = NULL, maxrows = NULL, ord = NULL,
                         conf.level = 0.95, verbose = 2, rfrq = "111", margins = c(1, 2),
                         dprobs = NULL, mprobs = NULL,
                         plotit = NULL, sep = NULL, digits = NULL, ...) {
  desc(x,
    xname = deparse(substitute(x)), main = NULL, digits = NULL,
    maxrows = NULL, ord = NULL,
    conf.level = 0.95, verbose = 2, rfrq = "111", margins = c(1, 2),
    dprobs = NULL, mprobs = NULL,
    plotit = NULL, sep = NULL, ...
  )
}




desc <- function(x, main = NULL, xname = deparse(substitute(x)), digits = NULL,
                 maxrows = NULL, ord = NULL,
                 conf.level = 0.95, verbose = 2, rfrq = "111", margins = c(1, 2),
                 dprobs = NULL, mprobs = NULL,
                 plotit = NULL, sep = NULL, ...) {
  # univariate Desc

  # z <- list(xname = deparse(substitute(x)),
  #           label = attr(x, "label"))

  # we have to collapse xname here, else there are some breaks like in
  # Desc(Recode(d.pizza$driver, carp=c("Carpenter","Carter"),
  #     arm=c("Butcher","Farmer"), elselevel = "Anyone"))

  z <- list(
    xname = paste(StrTrim(xname), collapse = ""),
    label = attr(x, "label")
  )

  if (any(class(x) %in% c("table", "matrix"))) {
    ntot <- length(x)
    n <- sum(x, na.rm = TRUE) # without NAs
    NAs <- NA # number of NAs in a table, how to?? after all they're pairs..
  } else if (identical(class(x), "NULL")) {
    ntot <- 0
    x <- NULL
    n <- 0
    NAs <- 0
  } else if (inherits(x, "ts")) {
    ntot <- length(x) # total count
    # x <- x[!is.na(x)]   do not omit NAs for timeseries
    n <- length(x) # now without NAs
    NAs <- ntot - n # number of NAs
  } else {
    ntot <- length(x) # total count
    x <- x[!is.na(x)]
    n <- length(x) # now without NAs
    NAs <- ntot - n # number of NAs
  }
  # ignore class AsIs from I(...) and keep only the rest of class(es)
  if (!is.null(x)) {
    class(x) <- class(x)[class(x) != "AsIs"]
  }

  z <- c(z,
    main = main,
    class = class(x)[1], # highest class here
    classlabel = paste(class(x), collapse = ", "),
    length = ntot,
    n = n,
    NAs = NAs,
    plotit = plotit,
    digits = digits,
    sep = sep
  )

  # define order for displaying frequencies of factors,
  # default level order for ordered factors
  # Descending frequencies for unordered factors
  if (is.null(ord)) {
    if (inherits(x, "ordered") ||
      inherits(x, "numeric") ||
      inherits(x, "integer")) {
      ord <- "level"
    } else if (inherits(x, "factor")) {
      ord <- if (nlevels(x) == 2) "level" else "desc"
    }
  }
  ord <- match.arg(arg = ord, choices = c("desc", "asc", "name", "level"))

  # define default main title
  if (is.null(main)) {
    z$main <- gettextf("%s (%s)", z$xname, paste(class(x), collapse = ", "))
  }

  # if not an empty vector (or only NAs)
  if (n > 0) {
    # send na stripped x to calcDesc, with n being vector length
    z <- c(z, calcDesc(
      x = x, n = n, digits = digits, conf.level = conf.level,
      ord = ord, maxrows = maxrows,
      verbose = verbose, rfrq = rfrq, margins = margins, ...
    ))

    if (z$class %nin% c("numeric", "Date") &&
      !is.null(z$unique) &&
      !is.na(z$unique) &&
      z$unique <= 2 &&
      !(z$class %in% c("factor", "ordered") && z$levels > 2)) {
      # escalate to logical description if only two values

      if (is.null(main)) {
        z$main <- gettextf(
          "%s (%s - dichotomous)", z$xname, paste(class(x), collapse = ", ")
        )
      }

      if (z$class %in% c("integer")) {
        z$afrq <- cbind(z$small$freq)
        rownames(z$afrq) <- z$small$val
      }
      if (z$class %in% c("factor", "ordered", "character")) {
        z$afrq <- cbind(z$freq$freq)
        rownames(z$afrq) <- z$freq$level
      }

      z$rfrq <- BinomCI(z$afrq, n, conf.level = conf.level)
      z$conf.level <- conf.level
      z$class <- "logical"
    }
  } else {
    z$unique <- NA
    z$noplot <- TRUE
    z$plotit <- FALSE
  }

  # why did I do that? not ok for frequencies??
  # anyway I may not overwrite digits here
  # if(is.null(digits) && !is.null(z$freq)) z$digits <- 1

  # make a list
  z <- list(z)

  class(z) <- "Desc"
  return(z)
}



#' @rdname Desc
#' @export
Desc.data.frame <- function(x, main = NULL, plotit = NULL, enum = TRUE,
                            sep = NULL, ...) {
  res <- Desc.list(
    x = x, main = main, plotit = plotit, enum = enum, sep = sep, ...
  )

  res[["_objheader"]][["main"]] <- gettextf(
    "Describe %s (%s):",
    gsub(" +", " ", paste(deparse(substitute(x)), collapse = " ")),
    paste(class(x), collapse = ", ")
  )

  res[["_objheader"]][["abstract"]] <- Abstract(x)

  attr(res[["_objheader"]][["abstract"]], "main") <-
    res[["_objheader"]][["main"]]

  res[["_objheader"]][["str"]] <- .CaptOut(
    res[["_objheader"]][["abstract"]],
    width = getOption("width")
  )[-c(1:3)]

  return(res)
}



#' @rdname Desc
#' @export
Desc.list <- function(x, main = NULL, plotit = NULL, enum = TRUE,
                      sep = NULL, ...) {
  xname <- deparse(substitute(x))

  # header for the data.frame of the list

  if (is.null(names(x))) {
    names(x) <- seq_along(x)
  }

  # default main titles if main is left to NULL
  def.main <- is.null(main)
  if (def.main) {
    main <- paste(
      if (enum) {
        paste(seq_along(names(x)), "- ")
      }, names(x),
      sep = ""
    )
  } else {
    main <- rep(main, length.out = ncol(x))
  }

  lst <- list()
  for (i in seq_along(x)) {
    xn <- names(x)[i]
    lst[[xn]] <- Desc(x[[xn]], plotit = plotit, sep = sep, ...)[[1]]
    lst[[xn]]["xname"] <- xn
    if (def.main) {
      lst[[xn]]["main"] <-
        gsub("x[[xn]]", main[i], lst[[xn]]["main"], fixed = TRUE)
    } else {
      lst[[xn]]["main"] <- main[i]
    }
  }


  header <- list(
    str = .CaptOut(
      Str(x, list.len = Inf)
    ),
    xname = xname,
    label = Label(x),
    class = "header",
    sep = sep,
    # main  = gettextf("Describe %s (%s):", deparse(substitute(x)), class(x))
    # we might be too late for substituting here... ?
    main = gettextf("Describe %s (%s):", xname, class(x))
  )
  # class(header) <- "Desc"

  lst <- append(lst, list(header), after = 0)
  names(lst)[1] <- "_objheader"
  class(lst) <- "Desc"

  return(lst)
}



#' @rdname Desc
#' @export
Desc.formula <- function(formula, data = parent.frame(),
                         subset, main = NULL, plotit = NULL, digits = NULL, ...) {
  mf <- match.call(expand.dots = FALSE)

  subset.expr <- mf$subset
  mf$subset <- NULL
  if (!missing(subset)) {
    s <- eval(subset.expr, data, parent.frame())
    data <- data[s, ]
  }

  mm <- DescTools::ParseFormula(formula = formula, data = data)

  lst <- list()
  if (length(mm$formula) == 2L) {
    for (x in mm$rhs$vars) { # for all x variables
      lst[x] <- Desc(mm$rhs$mf.eval[, x], plotit = plotit, digits = digits, ...)
      if (deparse(substitute(data)) != "parent.frame()") {
        lst[[x]]$main <-
          gettextf("%s$%s (%s)", deparse(substitute(data)), x, lst[[x]]$class)
      } else {
        lst[[x]]$main <- gettextf("%s (%s)", x, lst[[x]]$class)
      }
    }
  } else if (length(mm$rhs$vars) == 0 & length(mm$lhs$vars) != 0) {
    for (x in mm$lhs$vars) { # for all x variables
      lst[x] <- Desc(mm$lhs$mf.eval[, x], plotit = plotit, digits = digits, ...)
      if (deparse(substitute(data)) != "parent.frame()") {
        lst[[x]]$main <-
          gettextf("%s$%s (%s)", deparse(substitute(data)), x, lst[[x]]$class)
      } else {
        lst[[x]]$main <- gettextf("%s (%s)", x, lst[[x]]$class)
      }
    }
  } else {
    # don't want AsIs (will come in case of I(...)) to proceed, so just
    # coerce to vector an back again
    # but don't use the following, as interaction names will be
    # set to y.x instead of y:x
    # mm$lhs$mf.eval <- data.frame(lapply(mm$lhs$mf.eval, as.vector))
    # mm$rhs$mf.eval <- data.frame(lapply(mm$rhs$mf.eval, as.vector))
    for (i in which(lapply(mm$lhs$mf.eval, class) == "AsIs")) {
      mm$lhs$mf.eval[, i] <- as.vector(mm$lhs$mf.eval[, i])
    }
    for (i in which(lapply(mm$rhs$mf.eval, class) == "AsIs")) {
      mm$rhs$mf.eval[, i] <- as.vector(mm$rhs$mf.eval[, i])
    }

    for (resp in mm$lhs$vars) { # for all response variables
      for (pred in mm$rhs$vars) { # evalutate for all conditions

        y <- mm$lhs$mf.eval[, resp]
        x <- mm$rhs$mf.eval[, pred]

        if (IsDichotomous(y, na.rm = TRUE)) y <- factor(y)
        if (IsDichotomous(x, na.rm = TRUE)) x <- factor(x)

        names(y) <- resp
        names(x) <- pred

        lst[[paste(resp, pred, sep = " ~ ")]] <-
          calcDesc.bivar(x = y, g = x, xname = resp, gname = pred, ...)

        lst[[paste(resp, pred, sep = " ~ ")]]["plotit"] <- plotit
        # would not accept vectors when ["digits"] used. Why??:
        lst[[paste(resp, pred, sep = " ~ ")]][["digits"]] <- digits

        lst[[paste(resp, pred, sep = " ~ ")]]["main"] <- if (is.null(main)) {
          gettextf(
            "%s ~ %s%s",
            lst[[paste(resp, pred, sep = " ~ ")]]["xname"],
            lst[[paste(resp, pred, sep = " ~ ")]]["gname"],
            # don't display parent.frame() for simple formulas in main titles
            if ((ctxt <- deparse(substitute(data))) == "parent.frame()") {
              ""
            } else {
              paste0(" (", ctxt, ")")
            }
          )
        }
      }
    }

    if (!is.null(main)) {
      main <- rep(main, length.out = length(lst))
      for (i in seq_along(lst)) {
        lst[[i]]["main"] <- main[i]
      }
    }
  }

  attr(lst, "call") <- deparse(sys.call())

  class(lst) <- "Desc"
  return(lst)
}




calcDesc <- function(x, ...) {
  UseMethod("calcDesc")
}


calcDesc.default <- function(x, ...) {
  if (!is.null(class(x))) {
    # cat(gettextf("\nSorry, don't know how to Desc class(es) %s (%s)!\n\n",
    #              paste(class(x), collapse = ", "), deparse(substitute(x))))
    r <- "unhandled class"
  } else {
    # cat(gettextf("\nObject %s does not exist!\n\n", deparse(substitute(x))))
    r <- "no object"
  }

  invisible(r)
}



calcDesc.numeric <- function(x, n, maxrows = NULL, conf.level = 0.95,
                             include_x = TRUE, ...) {
  
  probs <- c(0, 0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95, 1)

  # the quantiles, totally analogue to the core of stats::quantile:
  index <- 1 + (n - 1) * probs

  lo <- floor(index)
  hi <- ceiling(index)

  x <- sort(x, partial = unique(c(lo, hi)))
  # WHOLE x MUST be sorted in order to get the smallest and largest values,
  # as well as the number of unique values!!!

  # old: x <- sort(x)
  # x <- sort.int(x, method="quick")  # somewhat faster than "shell"

  qs <- x[lo]
  i <- which(index > lo)
  h <- (index - lo)[i]
  qs[i] <- (1 - h) * qs[i] + h * x[hi[i]]
  
  names(qs) <- c("min", ".05", ".10", ".25", "median", ".75", ".90", ".95", "max")

  # ... here we go, all we need so far is in qs

  # proceed with the parameteric stuff, we cannot calc mean faster than R,
  # so do it here
  # meanx <- mean.default(x)      # somewhat faster than mean

  # we send the SORTED vector WITHOUT NAs to the C++ function to calc
  # the power sum(s)
  psum <- .Call("_DescTools_n_pow_sum", PACKAGE = "DescTools", x)

  # this is method 3 in the usual functions Skew and Kurt
  skewx <- ((1 / n * psum$sum3) / (psum$sum2 / n)^1.5) * ((n - 1) / n)^(3 / 2)
  kurtx <- ((((1 / n * psum$sum4) / (psum$sum2 / n)^2) - 3) + 3) * (1 - 1 / n)^2 - 3

  # get std dev here
  sdx <- sqrt(psum$sum2 / (n - 1))

  # meanCI
  if (n > 1) {
    a <- qt(p = (1-conf.level) / 2, df = n-1) * sdx / sqrt(n)
  } else {
    a <- NA
  }
  meanCI <- psum$mean + c(-1,1) * a
  
  # get the mode
  modex <- Mode(x)

  # check for remarkably frequent values in a numeric variable
  # say the most frequent value has significantly more than 5% from the total sample
  modefreq_crit <-
    binom.test(ZeroIfNA(attr(modex, "freq")), n = n, p = 0.05, alternative = "greater")
  
  if (modefreq_crit$p.value < 0.05 & psum$unique > 12) {
    modefreq_crit <- gettextf(
      "heap(?): remarkable frequency (%s) for the mode(s) (= %s)",
      Format(modefreq_crit$estimate, fmt = "%", digits = 1),
      paste(modex, collapse = ", ")
    )
  } else {
    modefreq_crit <- NA
  }

  # we display frequencies, when unique values <=12 else we set maxrows = 0
  # which will display extreme values as high-low list
  if (is.null(maxrows)) {
    maxrows <- ifelse(psum$unique <= 12, 12, 0)
  }

  if (maxrows > 0) {
    freq <- Freq(factor(x))
    colnames(freq)[1] <- "value"
    # use maxrows as percentage, when < 1
    if (maxrows < 1) {
      maxrows <- sum(freq[, 5] < maxrows) + 1
    }
  } else {
    freq <- NULL
  }

  # put together the results
  res <- list(
    unique = psum$unique,
    "0s" = psum$zero,
    mean = psum$mean,
    meanSE = sdx / sqrt(n),
    conf.level = conf.level,
    meanCI = meanCI,
    quant = qs,
    range = unname(diff(qs[c(1, 9)])),
    meanAD = psum$sum1 / n,
    sd = sdx,
    vcoef = sdx / psum$mean,
    mad = mad(x, center = qs[5]),
    IQR = unname(diff(qs[c(4, 6)])),
    skew = skewx,
    kurt = kurtx,
    small = data.frame(val = psum$small_val, freq = psum$small_freq),
    large = data.frame(val = psum$large_val, freq = psum$large_freq),
    mode = modex,
    modefreq_crit = modefreq_crit,
    freq = freq,
    maxrows = maxrows,
    x = if (include_x) x else NULL
  )

  return(res)
}


calcDesc.logical <- function(x, n, ord = "level", conf.level = 0.95, ...) {
  ff <- table(x)

  # how should the table be sorted, by name, level or frq? (NULL means "desc")
  switch(match.arg(ord, c("level", "desc", "asc", "name")),
    level = {  },
    name = {
      ff <- ff[names(ff)]
    },
    asc = {
      ff <- sort(ff)
    },
    desc = {
      ff <- -sort(-ff)
    }
  )

  bf <- BinomCI(ff, n, conf.level = conf.level)
  rownames(bf) <- names(ff)

  res <- list(
    unique = length(ff),
    afrq = ff, rfrq = bf, conf.level = conf.level
  )

  return(res)
}


calcDesc.factor <- function(x, n, maxrows = NULL, ord, ...) {
  freq <- Freq(x, ord = ord)

  if (is.null(maxrows)) {
    maxrows <- 12
  }

  if (maxrows < 1) {
    maxrows <- sum(freq[, 5] < maxrows) + 1
  }

  res <- list(
    levels = nlevels(x),
    unique = sum(freq$freq > 0), dupes = any(freq$freq > 1), maxrows = maxrows,
    ord = ord, freq = freq
  )

  return(res)
}


calcDesc.character <- function(x, n, maxrows = NULL, ord, ...) {
  # simply factorize x and send to calcDesc.factor
  calcDesc.factor(
    x = factor(x, ordered = TRUE), n = n, ord = ord, maxrows = maxrows, ...
  )
}


calcDesc.Date <- function(x, n, dprobs = NULL, mprobs = NULL,
                          include_x = TRUE, ...) {
  # time aggregation already in the definition of the variable:
  # example:     cut( x, breaks="quarter" )
  #              breaks: day, month, quarter, year

  ybreaks <- function(x, i) {
    i <- StrVal(i, as.numeric = TRUE)
    as.Date(seq(
      from =
        ISOdate(
          as.integer(min(format(x, "%Y"), na.rm = TRUE)) %/% i * i, 1, 1
        ),
      to = ISOdate(
        (as.integer(max(format(x, "%Y"), na.rm = TRUE))) %/% i * i + i, 1, 1
      ),
      "5 years"
    ))
  }

  if (is.null(dprobs)) dprobs <- rep(1 / 7, 7)
  if (is.null(mprobs)) {
    mprobs <-
      c(31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31) / 365
  }

  # weekdays in your current locale, Sunday : Saturday
  dtab <- Desc(table(Weekday(x, fmt = "ddd")),
    p = dprobs, stdres = TRUE,
    plotit = FALSE
  )[[1]]
  mtab <- Desc(table(Month(x, fmt = "mmm")),
    p = mprobs, stdres = TRUE,
    plotit = FALSE
  )[[1]]

  # set na.rm=TRUE as we inform user about NAs:
  tspan <- diff(range(x, na.rm = TRUE)) / 15
  hbreaks <- switch(findInterval(tspan, c(0, 5, 30, 100, 350, 1250, 3500, 35000)),
    "1" = "days",
    "2" = "weeks",
    "3" = "months",
    "4" = "quarters",
    "5" = "years",
    "6" = "5-years",
    "7" = "10-years"
  )

  res <- list(
    unique = length(unique(x)),
    highlow = HighLow(x, nlow = 4, na.last = NA),
    dperctab = dtab$perctab,
    d.approx.ok = dtab$approx.ok,
    d.chisq.test = dtab$chisq.test,
    mperctab = mtab$perctab,
    m.approx.ok = mtab$approx.ok,
    m.chisq.test = mtab$chisq.test,
    hbreaks = hbreaks,
    freq = Freq(
      x = x,
      breaks = (brk <- if (hbreaks %in% c("5-years", "10-years")) {
        ybreaks(x, hbreaks)
      } else {
        hbreaks
      })
    ),
    x = if (include_x) x else NULL
  )

  if (hbreaks %in% c("5-years", "10-years")) {
    res$freq$level <-
      paste("[", Year(brk[-length(brk)]), ", ", Year(brk[-1]), ")", sep = "")
  }

  return(res)
}


calcDesc.ts <- function(x, ...) {
  res <- list(
    unique = length(unique(x)),
    "0s" = sum(x == 0),
    frequency = frequency(x),
    start = start(x),
    end = end(x),
    x = x
  )
}


calcDesc.table <- function(x, n, conf.level = 0.95, verbose, rfrq, margins,
                           p, digits, ...) {
  # loglik.chisq <- function(r.chisq) {
  #   # Log-likelihood chi-squared (G2) test of independence (homogeneity)
  #
  #   lhrat <-
  #       2 * sum(r.chisq$observed *
  #       log(r.chisq$observed/r.chisq$expected), na.rm=TRUE)
  #
  #   structure(list(
  #     statistic = structure(lhrat, .Names = "X-squared"),
  #     parameter = structure(r.chisq$parameter, .Names = "df"),
  #     p.value   = structure(pchisq(lhrat, df=r.chisq$parameter,
  #                   lower.tail = FALSE), .Names = "X-squared"),
  #     method    = "Likelihood Ratio:",
  #     data.name = r.chisq$data.name
  #     ),
  #     .Names = c("statistic", "parameter", "p.value", "method", "data.name"),
  #      class = "htest")
  # }

  n.chisq.test <- function(tab) {
    z <- summary(tab)

    structure(
      list(
        statistic = structure(z$statistic, .Names = "X-squared"),
        parameter = structure(z$parameter, .Names = "df"),
        p.value   = structure(z$p.value, .Names = "X-squared"),
        method    = "Chi-squared test for independence of all factors:",
        approx.ok = z$approx.ok
      ),
      .Names = c("statistic", "parameter", "p.value", "method", "approx.ok"),
      class = "htest"
    )
  }


  ttype <- if (identical(dim(x), c(2L, 2L))) {
    "t2x2"
  } else if (length(dim(x)) > 2) {
    "tndim"
  } else if (length(dim(x)) < 2) {
    "t1dim"
  } else {
    "trxc"
  }

  suppressWarnings(r.chisq <- if (ttype == "1dim") {
    chisq.test(x, correct = FALSE, p = p)
  } else if (ttype == "tndim") {
    n.chisq.test(x)
  } else {
    chisq.test(x, correct = FALSE)
  })

  res <- list(
    n = sum(x),
    dim = dim(x),
    unique = NULL,
    ttype = ttype,
    verbose = verbose,
    conf.level = conf.level,
    chisq.test = r.chisq, # if(ttype=="tndim") n.chisq.test(x) else r.chisq,
    chisq.test.cont = if (ttype %in% c("t2x2", "trxc")) {
      suppressWarnings(chisq.test(x, correct = TRUE))
    } else {
      NULL
    },
    loglik.chisq.test = if (ttype != "tndim") {
      suppressWarnings(GTest(x))
    } else {
      NULL
    },
    mh.test = if (ttype %in% c("t2x2", "trxc")) MHChisqTest(x) else NULL,
    fisher.test = if (ttype == "t2x2") fisher.test(x) else NULL,
    mcnemar.test = if (ttype == "t2x2") mcnemar.test(x),
    or = if (ttype == "t2x2") OddsRatio(x, conf.level = conf.level),
    relrisk1 = if (ttype == "t2x2") {
      RelRisk(x, conf.level = conf.level, method = "wald", delta = 0)
    },
    relrisk2 = if (ttype == "t2x2") {
      RelRisk(Rev(x, margin = 2), conf.level = conf.level, method = "wald", delta = 0)
    },
    propdiff = if (ttype == "t2x2") {
      BinomDiffCI(x[1,1], sum(x[1,]), x[2,1], sum(x[2,]), conf.level = conf.level, method = "mn")[1,]
    },
    relrisk1r = if (ttype == "t2x2") {
      RelRisk(t(x), conf.level = conf.level, method = "wald", delta = 0)
    },
    relrisk2r = if (ttype == "t2x2") {
      RelRisk(t(Rev(x, margin = 1)), conf.level = conf.level, method = "wald", delta = 0)
    },
    assocs = if (ttype %in% c("t2x2", "trxc")) {
      Assocs(x, conf.level = conf.level, verbose = verbose)
    } else {
      NULL
    },
    tab = x,
    pfreq = prop.table(x),
    pfreqr = if (ttype != "t1dim") prop.table(x, 1) else NULL,
    pfreqc = if (ttype != "t1dim") prop.table(x, 2),
    perctab = if (ttype == "t1dim") {
      Freq(x)
    } else if (ttype == "tndim") {
      NULL
    } else {
      PercTable(x, rfrq = rfrq, margins = margins, digits = digits, ...)
    },
    approx.ok = if (ttype == "tndim") {
      r.chisq$approx.ok
    } else {
      !(any(r.chisq$expected < 5) && is.finite(r.chisq$parameter))
    }
  )

  return(res)
}


calcDesc.matrix <- function(x, n, conf.level = 0.95, verbose,
                            rfrq, margins, p, digits, ...) {
  calcDesc.table(
    x = x, n = n, conf.level = conf.level, verbose = verbose,
    rfrq = rfrq, margins = margins,
    p = p, digits = digits, ...
  )
}


calcDesc.bivar <- function(x, g, xname = NULL, gname = NULL,
                           margin = FALSE, breaks = 4, conf.level = 0.95,
                           smooth = TRUE, test = kruskal.test, verbose = 2, 
                           ...) {
  ok <- complete.cases(x, g)
  nv <- sum(ok)
  nx <- length(x)
  NAxs <- sum(is.na(x))
  ng <- length(g)
  NAgs <- sum(is.na(g))
  n <- max(nx, ng)

  gname <- if (is.null(gname)) deparse(substitute(g)) else gname
  xname <- if (is.null(xname)) deparse(substitute(x)) else xname

  res <- list(
    xname = xname, gname = gname, n = n, verbose = verbose,
    nvalid = nv, nx = nx, ng = ng, NAxs = NAxs, NAgs = NAgs,
    classx = class(x), classg = class(g), x = unname(x), g = unname(g)
  )

  if (is.numeric(x) && is.numeric(g)) {
    res$class <- "numnum"
    res$cor.p <- cor(x[ok], g[ok], use = "all.obs")
    res$cor.s <- cor(x[ok], g[ok], method = "spearman", use = "all.obs")
    res$cor.k <- if (n < 5000) {
      cor(x[ok], g[ok], method = "kendall", use = "all.obs")
    } else {
      NULL
    }
  } else if (is.numeric(x) && !is.numeric(g)) {
    res$class <- "numfact"
    res$mean <- tapply(x[ok], g[ok], FUN = mean)
    res$median <- tapply(x[ok], g[ok], FUN = median)
    res$sd <- tapply(x[ok], g[ok], FUN = sd)
    res$IQR <- tapply(x[ok], g[ok], FUN = IQR)
    res$ns <- tapply(x, g, FUN = function(z) sum(!is.na(z)))
    res$np <- res$ns / res$nv
    res$NAs <- tapply(x, g, FUN = function(z) sum(is.na(z)))
    res$Zeros <- tapply(x[ok], g[ok], FUN = function(z) sum(z == 0))
    res$nlevel <- length(res$mean)

    res$min <- tapply(x[ok], g[ok], FUN = min)
    res$max <- tapply(x[ok], g[ok], FUN = max)
    res$range <- tapply(x[ok], g[ok], FUN = Range)
    res$Q1 <- tapply(x[ok], g[ok], FUN = function(z) quantile(z, probs = 0.25))
    res$Q3 <- tapply(x[ok], g[ok], FUN = function(z) quantile(z, probs = 0.75))
    res$mad <- tapply(x[ok], g[ok], FUN = mad)
    res$meanAD <- tapply(x[ok], g[ok], FUN = MeanAD)
    res$skew <- tapply(x[ok], g[ok], FUN = Skew)
    res$kurt <- tapply(x[ok], g[ok], FUN = Kurt)

    if (margin) {
      res$mean <- c(res$mean, "Total" = mean(x[ok]))
      res$median <- c(res$median, median(x[ok]))
      res$sd <- c(res$sd, sd(x[ok]))
      res$IQR <- c(res$IQR, IQR(x[ok]))
      res$ns <- c(res$ns, sum(res$ns))
      res$np <- c(res$np, 1)
      res$NAs <- c(res$NAs, sum(res$NAs))
      res$Zeros <- c(res$Zeros, sum(res$Zeros))

      res$min <- c(res$min, min(x[ok]))
      res$max <- c(res$max, max(x[ok]))
      res$Q1 <- c(res$Q1, quantile(x[ok], probs = 0.25))
      res$Q1 <- c(res$Q1, quantile(x[ok], probs = 0.75))
      res$mad <- c(res$mad, mad(x[ok]))
      res$skew <- c(res$skew, Skew(x[ok]))
      res$kurt <- c(res$kurt, Kurt(x[ok]))
    }

    res$test <-
      tryCatch(test(x ~ g, na.action = "na.omit"), error = function(e) e)
  } else if (!is.numeric(x) && is.numeric(g)) {
    res$class <- "factnum"
    res$mean <- tapply(g[ok], x[ok], FUN = mean)
    res$median <- tapply(g[ok], x[ok], FUN = median)
    res$sd <- tapply(g[ok], x[ok], FUN = sd)
    res$IQR <- tapply(g[ok], x[ok], FUN = IQR)
    res$ns <- tapply(g, x, FUN = function(z) sum(!is.na(z)))
    res$np <- res$ns / res$nv
    res$NAs <- tapply(g, x, FUN = function(z) sum(is.na(z)))
    res$Zeros <- tapply(g[ok], x[ok], FUN = function(z) sum(z == 0))
    res$nlevel <- length(res$mean)
    res$smooth <- smooth

    res$min <- tapply(g[ok], x[ok], FUN = min)
    res$max <- tapply(g[ok], x[ok], FUN = max)
    res$Q1 <- tapply(g[ok], x[ok], FUN = function(z) quantile(z, probs = 0.25))
    res$Q3 <- tapply(g[ok], x[ok], FUN = function(z) quantile(z, probs = 0.75))
    res$mad <- tapply(g[ok], x[ok], FUN = mad)
    res$skew <- tapply(g[ok], x[ok], FUN = Skew)
    res$kurt <- tapply(g[ok], x[ok], FUN = Kurt)

    if (margin) {
      res$mean <- c(res$mean, "Total" = mean(g[ok]))
      res$median <- c(res$median, median(g[ok]))
      res$sd <- c(res$sd, sd(g[ok]))
      res$IQR <- c(res$IQR, IQR(g[ok]))
      res$ns <- c(res$ns, sum(res$ns))
      res$np <- c(res$np, 1)
      res$NAs <- c(res$NAs, sum(res$NAs))
      res$Zeros <- c(res$Zeros, sum(res$Zeros))

      res$min <- c(res$min, min(x[ok]))
      res$max <- c(res$max, max(x[ok]))
      res$Q1 <- c(res$Q1, quantile(x[ok], probs = 0.25))
      res$Q1 <- c(res$Q1, quantile(x[ok], probs = 0.75))
      res$mad <- c(res$mad, mad(x[ok]))
      res$skew <- c(res$skew, Skew(x[ok]))
      res$kurt <- c(res$kurt, Kurt(x[ok]))
    }


    res$test <-
      tryCatch(test(g ~ x, na.action = "na.omit"), error = function(e) e)

    res$atab <- table(unname(x[ok]), CutQ(g[ok],
      breaks = quantile(g[ok], probs = seq(0, 1, 1 / breaks)), na.rm = TRUE
    ))
    res$ptab <- prop.table(res$atab, 2)

    res$binci <- if (!is.na(conf.level)) {
      BinomCI(res$atab[2, ], apply(res$atab, 2, sum), conf.level = conf.level)
    } else {
      NULL
    }
  } else if (!is.numeric(x) && !is.numeric(g)) {
    res$class <- "factfact"
    #    res$tab <- table(x[ok], g[ok], useNA=InDots(..., arg="useNA",
    #    default = "no"))
    # do not use x[ok] here, as we could not use NAs in the output
    
    # changed 2024-02-03: response should be columns and predictors rows
    # old: res$tab <- table(x, g, useNA = InDots(..., arg = "useNA", default = "no"))
    
    res$tab <- table(g, x, useNA = InDots(..., arg = "useNA", default = "no"))
    res$rfrq <- InDots(..., arg = "rfrq", default = "111")
    res$conf.level <- conf.level
    res$verbose <- verbose
    res$freq <- InDots(..., arg = "freq", default = TRUE)
    res$margins <- InDots(..., arg = "margins", default = c(1, 2))
    names(dimnames(res$tab)) <- c(gname, xname)
  } else {
    return(NA)
  }

  return(res)
}



.print.charmatrix <- function(x, quote = FALSE, print.gap = 2,
                              right = TRUE, ...) {
  # prints a character matrix without rownames, by default right aligned and
  # with gap = 2
  # this is used by the print.Desc routines

  rownames(x) <- rep("", nrow(x))
  print(x, quote = quote, print.gap = print.gap, right = right, ...)
}


.LineSep <- function(sep=NULL, x=NULL){

  sep <- Coalesce(sep, x$sep, DescToolsOptions("linesep", default = "\u2500"))
  
  # Remove the ANSI color codes using gsub
  # ansi_pattern <- "\033\\[\\d+(;\\d+)?m"
  
  if(nchar(gsub("\033\\[\\d+(;\\d+)?m", "", sep, perl = TRUE)) == 1)
    sep <- strrep(sep, getOption("width") - 2)
  
  return(sep)  
    
}



#' @rdname Desc
#' @export
print.Desc <- function(x, digits = NULL, plotit = NULL, nolabel = FALSE,
                       sep = NULL, nomain = FALSE, ...) {
  .print <- function(x, digits = NULL, plotit = NULL, nomain = FALSE, ...) {
    # digits <- Coalesce(digits, x$digits, NULL)
    # Coalesce unlists the dot elements
    digits <- Filter(Negate(is.null), list(digits, x$digits, NULL))
    if (length(digits) == 0) {
      digits <- NULL
    } else {
      digits <- digits[[1]]
    }

    if (!is.null(digits)) {
      opt <- DescToolsOptions(digits = digits)
      on.exit(DescToolsOptions(opt))
    }

    plotit <- Coalesce(plotit, x$plotit, DescToolsOptions("plotit"), FALSE)

    # if(!is.null(attr(x, "call"))) {
    #   cat("\nCall:\n")
    #   cat(attr(x, "call"))
    #   cat("\n\n")
    # }

    if (!nomain) {
      cat(.LineSep(sep = sep, x = x), "\n")

      if (!identical(x$main, NA)) {
        if (.has_color()) {
          cat(cli::style_bold(x$main))
        } else {
          cat(x$main)
        }
      }
    }

    if (!is.null(x$label) && !nolabel) {
      cat(" :", strwrap(x$label, indent = 2, exdent = 2), sep = "\n")
    }
    if (!identical(x$main, NA) && !nomain) {
      cat("\n")
    }

    if (!nomain) cat("\n")

    if (any(x$class %in% c(
      "numeric", "integer", "factor", "ordered", "character",
      "logical", "table", "matrix", "xtabs", "Date", "ts", "xts",
      "factfact", "numnum", "numfact", "factnum"
    ))) {
      # escalate to logical if the vector is empty
      if (x$n == 0) {
        print.Desc.logical(x, digits, ...)
      } else {
        # do class dispatching by hand
        eval(parse(text = gettextf("print.Desc.%s(x, digits, ...)", x$class)))
      }

      if (plotit) {
        eval(parse(text = gettextf("plot.Desc.%s(x, ...)", x$class)))

        if (getOption("debug", FALSE)) {
          cat(gettextf("!print.Desc!:  plot.Desc.%s(x, ...)", x$class), "\n")
        }
      }
    } else if (identical(x$class, NULL) || identical(x$class, "NULL")) {
      cat("class is NULL, so there's nothing else to describe\n\n")
    } else if (x$class == "header") {
      print.Desc.header(x, ...)
    } else {
      print(unclass(x), ...)
    }
  }

  lapply(x, .print, digits = digits, plotit = plotit, nomain = nomain, ...)

  invisible()
}


print.Desc.header <- function(x, digits = NULL, ...) {
  cat(x[["str"]], sep = "\n")
  cat("\n")
}


print.Desc.numeric <- function(x, digits = NULL, ...) {
  nlow <- 5
  nhigh <- 5

  if (is.null(digits) && !is.null(x$digits)) digits <- x$digits
  defdigits <- is.null(digits)

  x["nperc"] <- Format(x[["n"]] / x[["length"]], fmt = "%", digits = 1)
  x["naperc"] <- Format(x[["NAs"]] / x[["length"]], fmt = "%", digits = 1)
  x["zeroperc"] <- Format(x[["0s"]] / x[["length"]], fmt = "%", digits = 1)

  if (x[["n"]] > 1) {
    a <- qt(p = (1 - x[["conf.level"]]) / 2, df = x[["n"]] - 1) * x[["meanSE"]]
  } else {
    a <- NA
  }

  x["meanCI"] <- x[["mean"]] + a
  x["meanUCI"] <- x[["mean"]] - a

  x[c("length", "n", "NAs", "unique", "0s")] <-
    lapply(x[c("length", "n", "NAs", "unique", "0s")],
      Format,
      fmt = Fmt("abs")
    )
  if (defdigits) {
    # how many digits do we want to use?
    # we would use the same number as quantile does...
    out <- capture.output(x$quant)
    digits <- max(2, MaxDigits(strsplit(StrTrim(out[[2]]), split = " ")[[1]][1]))
    # for counts the quants would tipically return 0 digits, mean and
    # ds deserve some though
    # if(digits==0) digits <- 1
  }

  x[["quant"]][] <- Format(x[["quant"]], fmt = Fmt("num", digits = digits))

  x[c("mean", "meanCI", "meanUCI", "range", "sd", "vcoef", "mad", "IQR", "skew", "kurt")] <-
    lapply(x[c("mean", "meanCI", "meanUCI", "range", "sd", "vcoef", "mad", "IQR", "skew", "kurt")],
      Format,
      fmt = Fmt("num", digits = digits)
    )

  lst <- list(
    l1 = unlist(x[c("length", "n", "NAs", "unique", "0s", "mean", "meanCI")]),
    l2 = c("", x[["nperc"]], x[["naperc"]], "", x[["zeroperc"]], "", x[["meanUCI"]]),
    l3 = x[["quant"]][-c(1, 9)],
    l4 = unlist(x[c("range", "sd", "vcoef", "mad", "IQR", "skew", "kurt")])
  )

  width <- max(c(
    unlist(lapply(lst, nchar)),
    unlist(lapply(lapply(lst, names), nchar))
  ), na.rm = TRUE)
  if (x$unique == x$n) {
    lst$l1["unique"] <- "= n"
  }


  # replaced by 0.99.19
  # cat(paste(lapply(lst, .txtline, width = width, ind = "  ",
  #                  space = "  "), collapse = "\n"), "\n")
  # clarify: print.gap can be set with space, which is set here to 2 spaces
  # should we make an argument out of that?

  m <- rbind(
    lst$l1, lst$l2, "",
    names(lst$l3), lst$l3, "",
    names(lst$l4), lst$l4, ""
  )
  out <- capture.output(.print.charmatrix(m))
  out[1] <- paste0(out[1], DescToolsOptions("footnote")[1])
  cat(out, sep = "\n")

  # we need to do that even if highlow == FALSE, as Desc.integer
  # could need the result!!
  if (x$class == "numeric") {
    vals <- Format(
      c(x$small$val, x$large$val),
      fmt = Fmt("num", digits = digits)
    )
  } else {
    vals <- Format(c(x$small$val, x$large$val), fmt = Fmt("abs"))
  }
  # we don't want too many digits but as well no trailing 0s by default
  if (defdigits) {
    vals <- gsub("\\.0+$", "\\.0", gsub("^(\\d+\\.\\d*?[1-9])0+$", "\\1",
      vals,
      perl = TRUE
    ))
  }

  if (is.null(x$freq)) {
    frq <- c(x$small$freq, x$large$freq)
    frqtxt <- paste(" (", Format(frq, fmt = Fmt("abs")), ")", sep = "")
    frqtxt[frq < 2] <- ""
    txt <- StrTrim(paste(vals, frqtxt, sep = ""))
    x$lowtxt <-
      paste(head(txt, min(length(x$small$val), nlow)), collapse = ", ")
    x$hightxt <-
      paste(rev(tail(txt, min(length(x$large$val), nhigh))), collapse = ", ")

    cat(paste("lowest : ", x$lowtxt, "\n", "highest: ", x$hightxt, "\n\n",
      sep = ""
    ))
  } else {
    cat("\n")
    print(x$freq[1:min(nrow(x$freq), x$maxrows), ])
    if (x$maxrows < nrow(x$freq)) {
      cat("... etc.\n [list output truncated]\n\n")
    } else {
      cat("\n")
    }
  }

  if (!is.na(x$modefreq_crit)) {
    cat(x$modefreq_crit)
    cat("\n\n")
  }

  if (.has_color()) {
    cat(cli::col_silver(gettextf(
      "%s %s%s-CI (classic)\n\n",
      DescToolsOptions("footnote")[1], x$conf.level * 100, "%"
    )))
  } else {
    cat(gettextf(
      "%s %s%s-CI (classic)\n\n",
      DescToolsOptions("footnote")[1], x$conf.level * 100, "%"
    ))
  }
}


print.Desc.logical <- function(x, digits = NULL, ...) {
  digits <- Coalesce(digits, x$digits, NULL)

  if (!is.null(digits)) {
    opt <- options(digits = digits)
    on.exit(options(opt))
  }

  m <- rbind(
    c("length", "n", "NAs", "unique"),
    c(Format(unlist(x[c("length", "n", "NAs", "unique")]), fmt = Fmt("abs"))),
    c(
      "",
      x["nperc"] <- Format(x[["n"]] / x[["length"]], fmt = "%", digits = 1),
      x["naperc"] <- Format(x[["NAs"]] / x[["length"]], fmt = "%", digits = 1),
      ""
    )
  )
  m[] <- StrAlign(m, sep = "\\r")
  cat(paste(" ", apply(m, 1, paste, collapse = " ")), sep = "\n")
  cat("\n")

  if (!is.null(x$afrq)) {
    out <- cbind(
      freq = Format(x$afrq, fmt = Fmt("abs")),
      Format(x$rfrq, fmt = Fmt("per", digits = digits))
    )

    rownames(out) <- rownames(x$afrq)
    colnames(out) <- c(
      "freq", "perc",
      gettextf(
        c("lci%s", "uci%s"),
        Format(x$conf.level, digits = 2, ldigits = 0)
      )
    )

    txt <- capture.output(print(StrTrim(out),
      quote = FALSE, right = TRUE,
      print.gap = 2
    ))
    cat(paste(txt[1], DescToolsOptions("footnote")[1],
      sep = ""
    ), txt[-1], sep = "\n")

    if (.has_color()) {
      cat(cli::col_silver(gettextf("\n%s %s%s-CI (Wilson)\n\n",
        DescToolsOptions("footnote")[1], x$conf.level * 100, "%"
      )))
    } else {
      cat(gettextf(
        "\n%s %s%s-CI (Wilson)\n\n",
        DescToolsOptions("footnote")[1], x$conf.level * 100, "%"
      ))
    }
  }

  if (identical(x$noplot, TRUE)) {
    cat(gettextf("Nothing to plot in %s\n\n", x$xname))
  }
}



print.Desc.factor <- function(x, digits = NULL, ...) {
  m <- rbind(
    c("length", "n", "NAs", "unique", "levels", "dupes"),
    c(
      Format(unlist(x[c("length", "n", "NAs", "unique", "levels")]),
        fmt = Fmt("abs")
      ),
      c("n", "y")[x$dupes + 1]
    ),
    c(
      "", x["nperc"] <- Format(x[["n"]] / x[["length"]], fmt = "%", digits = 1),
      x["naperc"] <- Format(x[["NAs"]] / x[["length"]], fmt = "%", digits = 1),
      "", "", ""
    )
  )

  m[] <- StrAlign(m[], sep = "\\r")
  cat(paste(" ", apply(m, 1, paste, collapse = " ")), sep = "\n")

  # digits <- Coalesce(digits, x$digits, getOption("digits"))
  digits <- Coalesce(digits, x$digits, NULL)

  x$freq <- x$freq[1:min(nrow(x$freq), x$maxrows), ]
  txt.freq <- .CaptOut(print(x$freq, digits = digits))
  cat("\n")
  cat(txt.freq, sep = "\n")

  if (x$maxrows < x$levels) {
    cat("... etc.\n [list output truncated]\n\n")
  } else {
    cat("\n")
  }
}


print.Desc.character <- function(x, digits = NULL, ...) {
  print.Desc.factor(x, digits = digits, ...)
}


print.Desc.ordered <- function(x, digits = NULL, ...) {
  print.Desc.factor(x, digits = digits, ...)
}


print.Desc.integer <- function(x, digits = NULL, ...) {
  print.Desc.numeric(x, digits = digits, ...)
}


print.Desc.matrix <- function(x, digits = NULL, ...) {
  print.Desc.table(x, digits = digits, ...)
}


print.Desc.table <- function(x, digits = NULL, ...) {
  x[c(6, 8)] <- NULL

  # opt  <- options(scipen=4); on.exit(options(opt))

  if (x$ttype == "tndim") { # multdim table

    cat("Summary: \n",
      "n: ", Format(x$n, fmt = Fmt("abs")), ", ",
      length(x$dim), "-dim table: ", paste(x$dim, collapse = " x "),
      "\n\n",
      sep = ""
    )

    cat(gettextf(
      "%s\n  X-squared = %s, df = %s, p-value = %s",
      x[["chisq.test"]][["method"]],
      Format(x[["chisq.test"]][["statistic"]], digits = 3),
      x[["chisq.test"]][["parameter"]],
      Format(x[["chisq.test"]][["p.value"]], fmt = "p")
    ), "\n", sep = "")
    if (!x$approx.ok) {
      cat(cli::col_red("\nWarning message:\n  Exp. counts < 5: Chi-squared approx. may be incorrect!!\n"))
    }

    cat("\n")
    print(ftable(addmargins(x$tab, c(1, length(x$dim)))))
    cat("\n")
  } else { # <= 2-dimensional table


    if (x$ttype == "t1dim") { # 1-dim table ****
      cat("Summary: \n",
        "n: ", Format(x$n, fmt = Fmt("abs")),
        ", rows: ", x$dim[1],
        "\n\n",
        sep = ""
      )
      cat("Pearson's Chi-squared test (1-dim uniform):\n  ",
        .CaptOut(x$chisq.test)[5], "\n\n",
        sep = ""
      )

      if (!x$approx.ok) {
        ChisqWarning()
      }

      print(x$perctab)
    } else { # 2-dim tabl *****

      if (!is.null(attr(x, "missings"))) {
        missn <- paste(",", attr(x, "missings"), paste = "")
      } else {
        missn <- ""
      }

      cat("Summary: \n",
        "n: ", Format(x$n, fmt = Fmt("abs")),
        ", rows: ", Format(x$dim[1], fmt = Fmt("abs")),
        ", columns: ", Format(x$dim[2], fmt = Fmt("abs")),
        missn,
        "\n\n",
        sep = ""
      )

      if (x$ttype == "t2x2") {
        if (x$verbose == "3") {
          cat("Pearson's Chi-squared test:\n  ",
            .CaptOut(x$chisq.test)[5], "\n",
            sep = ""
          )
        }
        cat("Pearson's Chi-squared test (cont. adj):\n  ",
          .CaptOut(x$chisq.test.cont)[5], "\n",
          sep = ""
        )
        cat("Fisher's exact test ",
          .CaptOut(x$fisher.test)[5], "\n",
          sep = ""
        )

        if (x$verbose %in% c("2", "3")) { # print only with verbosity > 1
          cat("", .CaptOut(x$mcnemar.test)[5], "\n", sep = "")
        }

        if (!x$approx.ok) {
          ChisqWarning()
        }

        if (x$verbose %in% c("2", "3")) { # print only with verbosity > 1
          cat("\n")
          if (x$verbose == "2") {
            m <- ftable(format(rbind(
              "odds ratio    " = x$or,
              "rel. risk (col1)  " = x$relrisk1,
              "rel. risk (col2)  " = x$relrisk2,
              "prop. diff " = x$propdiff
            ), digits = 3, nsmall = 3))
          } else {
            m <- ftable(format(rbind(
              "odds ratio    " = x$or,
              "rel. risk (col1)  " = x$relrisk1,
              "rel. risk (col2)  " = x$relrisk2,
              "rel. risk (row1)  " = x$relrisk1r,
              "rel. risk (row2)  " = x$relrisk2r,
              "prop. diff        " = x$propdiff
            ), digits = 3, nsmall = 3))
          }
          attr(m, "col.vars")[[1]][1] <- "estimate"
          txt <- capture.output(print(m))
          txt[1] <- paste(txt[1], DescToolsOptions("footnote")[1], sep = "")
          cat(txt, sep = "\n")
          cat("\n")
        }
      } else {
        # we report chisquare without cont-corr for rxc and with cont-corr for 2x2 by default
        cat("Pearson's Chi-squared test:\n  ",
          .CaptOut(x$chisq.test)[5], "\n",
          sep = ""
        )

        if (x$verbose == "3") {
          cat("Pearson's Chi-squared test (cont. adj):\n  ",
            .CaptOut(x$chisq.test.cont)[5], "\n",
            sep = ""
          )
        }

        if (x$verbose > 1) { # print only with verbosity > 1

          # Log-likelihood chi-squared (G2) test of independence (homogeneity)
          cat("Log likelihood ratio (G-test) test of independence:\n  ",
            .CaptOut(x$loglik.chisq.test)[5], "\n",
            sep = ""
          )
          # Mantel-Haenszel ChiSquared (linear hypothesis)
          cat("Mantel-Haenszel Chi-squared:\n  ",
            .CaptOut(x$mh.test)[5], "\n",
            sep = ""
          )
        }

        if (!x$approx.ok) {
          ChisqWarning()
        }
      }

      switch(x$verbose,
        "1" = {
          cat("\n")
        },
        "2" = {
          cat(sprintf(
            "\nContingency Coeff.     %.3f\nCramer's V             %.3f\nKendall Tau-b          %.3f\n",
            x$assocs[1, 1],
            x$assocs[2, 1],
            x$assocs[3, 1]
          ))
          cat("\n")
        },
        "3" = {
          cat("\n")
          txt <- capture.output(x$assocs)
          txt[1] <- paste(txt[1], DescToolsOptions("footnote")[1], sep = "")
          cat(txt, sep = "\n")
          cat("\n")
        }
      )

      # print(PercTable(x$tab, rfrq=rfrq, margins=margins, ...))
      print(x$perctab)

      if ((x$verbose == "3") || (x$ttype == "t2x2")) {
        if (.has_color()) {
          cat(cli::col_silver(gettextf(
            "\n%s\n%s %s%s conf. level\n", strrep("\u2500", 20),
            DescToolsOptions("footnote")[1], x$conf.level * 100, "%"
          )))
        } else {
          cat(gettextf(
            "\n%s\n%s %s%s conf. level\n", strrep("\u2500", 20),
            DescToolsOptions("footnote")[1], x$conf.level * 100, "%"
          ))
        }
      }
    }

    cat("\n")
  }
}


print.Desc.xtabs <- function(x, digits = NULL, ...) {
  print.Desc.table(x, digits, ...)
}





print.Desc.Date <- function(x, digits = NULL, ...) {
  # time aggregation already in the definition of the variable:
  # example:     cut( x, breaks="quarter" )
  #              breaks: day, month, quarter, year

  m <- rbind(
    c("length", "n", "NAs", "unique"),
    c(Format(unlist(x[c("length", "n", "NAs", "unique")]), fmt = Fmt("abs"))),
    c(
      "",
      x["nperc"] <- Format(x[["n"]] / x[["length"]], fmt = "%", digits = 1),
      x["naperc"] <- Format(x[["NAs"]] / x[["length"]], fmt = "%", digits = 1),
      ""
    )
  )
  m[] <- StrAlign(m, sep = "\\r")
  cat(paste(" ", apply(m, 1, paste, collapse = " ")), sep = "\n")
  cat("\n")



  cat(x$highlow, "\n", sep = "")

  cat("\nWeekday:\n\n")
  cat("Pearson's Chi-squared test (1-dim uniform):\n  ",
    .CaptOut(x$d.chisq.test)[5], "\n\n",
    sep = ""
  )

  if (!x$d.approx.ok) {
    ChisqWarning()
  }


  print(x$dperctab)

  cat("\nMonths:\n\n")
  cat("Pearson's Chi-squared test (1-dim uniform):\n  ",
    .CaptOut(x$m.chisq.test)[5], "\n\n",
    sep = ""
  )

  print(x$mperctab)

  if (!x$m.approx.ok) {
    ChisqWarning()
  }


  if (!is.null(x$hbreaks)) {
    cat("\nBy", x$hbreaks, ":\n\n")
    print(x$freq)
  } else {
    # cat("Warning:\n  No plausible breaks for years found!\n")
    cat(cli::col_red("Warning:\n  No plausible breaks for years found!\n"))
  }
  cat("\n")
}


print.Desc.ts <- function(x, digits = NULL, ...) {
  x["nperc"] <- Format(x[["n"]] / x[["length"]], fmt = "%", digits = 1)
  x["naperc"] <- Format(x[["NAs"]] / x[["length"]], fmt = "%", digits = 1)
  x["zeroperc"] <- Format(x[["0s"]] / x[["length"]], fmt = "%", digits = 1)

  x[c("length", "n", "NAs", "unique", "0s")] <-
    lapply(x[c("length", "n", "NAs", "unique", "0s")],
      Format,
      fmt = Fmt("abs")
    )

  lst <- list(
    l1 = unlist(x[c("length", "n", "NAs", "unique", "0s")]),
    l2 = c("", x[["nperc"]], x[["naperc"]], "", x[["zeroperc"]]),
    l3 = c(
      start = paste(x$start, collapse = "-"),
      end = paste(x$end, collapse = "-"),
      frequency = x$frequency, "", ""
    )
  )

  width <- max(c(
    unlist(lapply(lst, nchar)),
    unlist(lapply(lapply(lst, names), nchar))
  ), na.rm = TRUE)
  if (x$unique == x$n) {
    lst$l1["unique"] <- "= n"
  }

  m <- rbind(lst$l1, lst$l2, "", names(lst$l3), lst$l3, "")
  .print.charmatrix(m)
}



print.Desc.factfact <- function(x, digits = NULL, ...) {
  # txt <- .CaptOut(Desc(x$tab, plotit=FALSE, digits=digits, rfrq=x$rfrq,
  #                      verbose=x$verbose, freq=x$freq, conf.level=x$conf.level,
  #                      ...))[-(1:3)]
  # cat(txt, sep="\n")

  print.Desc(Desc(x$tab,
    plotit = FALSE, rfrq = x$rfrq, digits = digits,
    verbose = x$verbose, freq = x$freq,
    conf.level = x$conf.level, ...
  ), nomain = TRUE)
}


print.Desc.numfact <- function(x, digits = NULL, ...) {
  cat("Summary: \n",
    "n pairs: ", Format(x$n, fmt = Fmt("abs")),
    ", valid: ", Format(x$nvalid, fmt = Fmt("abs")),
    " (", Format(x$nvalid / x$n, fmt = Fmt("per")), ")",
    ", missings: ", Format(x$n - x$nvalid, fmt = Fmt("abs")),
    " (", Format((x$n - x$nvalid) / x$n, fmt = Fmt("per")), "),",
    " groups: ", x$nlevel,
    sep = ""
  )
  cat("\n\n")

  # digits <- Coalesce(digits, x$digits, NULL)
  if (is.null(digits)) {
    digits <- DescToolsOptions("digits", default = 3)
  }

  digits <- rep(digits, length.out = 5 + (x$verbose == 3) * 7L)

  z <- rbind(
    Format(x$mean, fmt = Fmt("num", digits = digits[1])),
    Format(x$median, fmt = Fmt("num", digits = digits[2])),
    Format(x$sd, fmt = Fmt("num", digits = digits[3])),
    Format(x$IQR, fmt = Fmt("num", digits = digits[4])),
    Format(x$ns, fmt = Fmt("abs")),
    Format(x$np, fmt = Fmt("per", digits = digits[5])),
    Format(x$NAs, fmt = Fmt("abs")),
    Format(x$Zeros, fmt = Fmt("abs"))
  )
  # cannot use names as 0s is replaced by X.0s.... :
  rownames(z) <- c("mean", "median", "sd", "IQR", "n", "np", "NAs", "0s")
  colnames(z) <- rep("", ncol(z))

  if (x$verbose == 3) {
    z <- rbind(
      z,
      Format(x$min, fmt = Fmt("num", digits = digits[6])),
      Format(x$max, fmt = Fmt("num", digits = digits[7])),
      Format(x$Q1, fmt = Fmt("num", digits = digits[8])),
      Format(x$Q3, fmt = Fmt("num", digits = digits[9])),
      Format(x$mad, fmt = Fmt("num", digits = digits[10])),
      Format(x$skew, fmt = Fmt("num", digits = digits[11])),
      Format(x$kurt, fmt = Fmt("num", digits = digits[12]))
    )
    rownames(z)[9:15] <- c("min", "max", "Q1", "Q3", "mad", "skew", "kurt")
  }

  z <- rbind(names(x$mean), z)
  z[] <- StrAlign(z, sep = "\\r")
  print(z, quote = FALSE, print.gap = 2, ...)

  if (inherits(x$test, "simpleError")) {
    cat(gettextf("\nError in test(x) : %s\n\n", x$test$message))
  } else {
    cat(gettextf(
      "\n%s:\n  %s", x$test["method"],
      .CaptOut(x$test)[5]
    ), "\n\n", sep = "")
  }

  if ((x$NAgs > 0) & (length(grep("NA", x$xname)) == 0)) {
    cat(cli::col_red(gettextf(
      "\nWarning:\n  Grouping variable contains %s NAs (%s",
      x$NAgs, signif(x$NAgs / x$n, digits = 3) * 100
    ), "%).\n", sep = ""))
  } else {
    cat("\n")
  }

  cat("\n")
}


print.Desc.numnum <- function(x, digits = NULL, ...) {
  cat("Summary: \n",
    "n pairs: ", Format(x$n, fmt = Fmt("abs")),
    ", valid: ", Format(x$nvalid, fmt = Fmt("abs")),
    " (", Format(x$nvalid / x$n, fmt = Fmt("per")), ")",
    ", missings: ", Format(x$n - x$nvalid, fmt = Fmt("abs")),
    " (", Format((x$n - x$nvalid) / x$n, fmt = Fmt("per")), ")",
    sep = ""
  )
  cat("\n\n")

  cat(gettextf(
    "\nPearson corr. : %s\nSpearman corr.: %s\nKendall corr. : %s\n\n",
    Format(x$cor.p, fmt = Fmt("num")),
    Format(x$cor.s, fmt = Fmt("num")),
    if (x$nvalid < 5000) {
      Format(x$cor.k, fmt = Fmt("num"))
    } else {
      "(sample too large)"
    }
  ))
}


print.Desc.factnum <- function(x, digits = NULL, ...) {
  x$main <- paste(x$xname, x$gname, sep = " ~ ")
  x$NAgs <- x$NAxs
  print.Desc.numfact(x, digits = digits, ...)

  cat(gettextf(
    "\n\nProportions of %s in the quantiles of %s:\n",
    x$xname, x$gname
  ))
  ptab <- x$ptab
  ptab[] <- StrAlign(Format(x$ptab, fmt = Fmt("per")))
  print(ptab, quote = FALSE, print.gap = 3, right = TRUE)
  cat("\n")
}




#' @rdname Desc
#' @export
plot.Desc <- function(x, main = NULL, ...) {
  plot.Desc.z <- function(z, main = main, ...) {
    if (any(z$class %in% c(
      "numeric", "integer", "character", "factor", "ordered", "logical", "Date",
      "table", "matrix", "xtabs", "ts", "xts",
      "factfact", "numnum", "factnum", "numfact"
    ))) {
      eval(parse(text = gettextf("plot.Desc.%s(z, main=main, ...)", z$class)))
    } else if (z$class %in% c("header")) {
      # do nothing
    } else if (z$class %in% c("palette")) {
      # eval(parse(text=gettextf("plot.%s(z, ...)", z$class)))
    } else {
      plot.Desc.default(z, main = main, ...)
    }
  }

  # dispatch for classes
  lapply(x, plot.Desc.z, main = main, ...)

  invisible()
}


plot.Desc.default <- function(x, main = NULL, ...) {
  return(gettextf(
    "should plot %s \nbut might not be able to plot that stuff...",
    deparse(substitute(x))
  ))
}


plot.Desc.numeric <- function(x, main = NULL, args.hist = NULL, ...) {
  # return the first value not being null of main, x$main, deparse(substitute(x))
  # (remind to allow NA here, for choosing no main title)
  main <- Reduce(
    function(x, y) ifelse(!is.null(x), x, y),
    c(main, x$main, deparse(substitute(x)))
  )

  if (x$maxrows == Inf) {
    args.hist <- list(type = "mass")
  } else if (is.null(args.hist)) {
    args.hist <- list(type = if (x$unique > 12) "hist" else "mass")
  }

  PlotFdist(x = x$x, main = main, args.hist = args.hist, ...)
}


plot.Desc.character <- function(x, main = NULL, ...) {
  plot.Desc.factor(x, main = main, ...)
}


plot.Desc.factor <- function(x, main = NULL, maxlablen = 25,
                             type = c("bar", "dot"),
                             col = NULL, border = NULL, xlim = NULL, ecdf = TRUE, ...) {
  # if (nlevels(factor(x)) <= 2) {
  #   plot.Desc.logical(x, main = main, ..., wrd=wrd)
  # }
  # else {

  oldpar <- par(no.readonly = TRUE)
  on.exit(par(oldpar))

  # was cex in the dots-args? parse dots.arguments
  cex <- unlist(match.call(expand.dots = FALSE)$...["cex"])
  if (is.null(cex)) cex <- par("cex")

  tab <- as.table(x$freq$freq)
  names(tab) <- x$freq[[1]]
  ptab <- as.table(x$freq$perc)
  trunc_fg <- (nrow(tab) > x$maxrows)
  if (!is.na(x$maxrows) && x$maxrows < nrow(tab)) {
    tab <- tab[1:min(nrow(tab), x$maxrows)]
    ptab <- ptab[1:min(nrow(tab), x$maxrows)]
  }

  if (max(nchar(names(tab))) > maxlablen) {
    names(tab) <- StrTrunc(names(tab), maxlablen)
  }
  wtxt <- max(strwidth(names(tab), "inch"))
  wplot <- (par("pin")[1] - wtxt) / 2
  layout(matrix(c(1, 2), nrow = 1), widths = c(wtxt + wplot, wplot) * 2.54)
  par(mai = c(1.2, max(strwidth(rev(names(tab)), "inch")) + .5, 0.2, .3) + .02)
  if (!is.na(x$main)) par(oma = c(0, 0, 3, 0))


  switch(match.arg(arg = type, choices = c("bar", "dot")),
    dot = {
      if (is.null(xlim)) {
        xlim <- range(pretty(tab)) + c(-1, 1) * diff(range(pretty(tab))) * 0.04
      }

      if (is.null(col)) col <- Pal()[1]
      if (is.null(border)) border <- "black"
      b <- barplot(rev(tab),
        horiz = TRUE, border = NA, col = "white", las = 1,
        xlim = xlim,
        xpd = FALSE, xlab = "frequency",
        cex.names = cex, cex.axis = cex, cex.lab = cex, tck = -0.04
      )
      abline(h = b, v = 0, col = "grey", lty = "dotted")
      segments(0, b, as.vector(rev(tab)), b)
      points(
        x = as.vector(rev(tab)), y = b, yaxt = "n",
        col = border, pch = 21, bg = col, cex = 1.3
      )
      box()

      par(mai = c(1.2, 0.1, 0.2, .3) + .02)
      b <- barplot(rev(ptab),
        horiz = TRUE, border = NA, col = "white", las = 1, names = "",
        xlim = c(-0.04, 1.04),
        xlab = "percent", cex.names = cex, cex.axis = cex,
        cex.lab = cex, tck = -0.04
      )
      abline(h = b, v = 0, col = "grey", lty = "dotted")
      segments(0, b, as.vector(rev(ptab)), b)
      points(
        x = as.vector(rev(ptab)), y = b, col = border, pch = 21,
        bg = col, cex = 1.3
      )
      box()
    },
    bar = { # type = "bar"

      if (is.null(xlim)) {
        xlim <- range(pretty(c(0.96 * min(tab), 1.04 * max(tab))))
      }

      if (is.null(col)) {
        col <- c(
          rep("grey80", length.out = 2 * nrow(tab)),
          rep(SetAlpha("grey80", 0.4), length.out = nrow(tab))
        )
      } else {
        if (length(col) == 1) {
          col <- c(
            rep(col, length.out = 2 * nrow(tab)),
            rep(SetAlpha(col, 0.3), length.out = nrow(tab))
          )
        } else {
          col <- rep(col, length.out = 3 * nrow(tab))
        }
      }
      if (is.null(border)) border <- NA
      barplot(rev(tab),
        horiz = TRUE, col = col[1:nrow(tab)],
        border = border, las = 1, xlim = xlim,
        xpd = FALSE, xlab = "frequency",
        cex.names = cex, cex.axis = cex, cex.lab = cex, tck = -0.04
      )
      grid(ny = NA)

      par(mai = c(1.2, 0.15, 0.2, .3) + .02)
      if (ecdf) {
        barplot(rev(cumsum(ptab)),
          horiz = TRUE, col = col[(2 * nrow(tab) + 1):(3 * nrow(tab))],
          border = border, las = 1,
          names = "", xlim = c(0, 1), xlab = "percent",
          cex.names = cex, cex.axis = cex, cex.lab = cex, tck = -0.04
        )
        barplot(rev(ptab),
          horiz = TRUE, col = col[(nrow(tab) + 1):(2 * nrow(tab))],
          border = border, names = "", xlab = NA, ylab = NA,
          add = TRUE, axes = FALSE
        )
      } else {
        barplot(rev(ptab),
          horiz = TRUE, col = col[(nrow(tab) + 1):(2 * nrow(tab))],
          border = border, las = 1, names = "",
          xlim = c(0, 1), xlab = "percent", cex.names = cex,
          cex.axis = cex, cex.lab = cex, tck = -0.04
        )
      }
      grid(ny = NA)
    }
  )


  if (is.null(main)) main <- x$main
  if (!is.na(main)) {
    title(main = Coalesce(main, x$main), outer = TRUE)
  }

  if (trunc_fg) {
    text(
      x = par()$usr[2], y = 0.4, labels = " ...[list output truncated]  ",
      cex = 0.6, adj = c(1, 0.5)
    )
  }

  if (!is.null(DescToolsOptions("stamp"))) {
    Stamp()
  }

  invisible()
}


plot.Desc.integer <- function(x, main = NULL, ...) {
  # switch(as.character(cut(x$unique, breaks=c(0, 2, 12,Inf), labels=1:3))
  #        , "1" = { plot.Desc.logical(x, main=main, ...) }
  #        , "2" = { plot.Desc.factor(x, main=main, ..., type="dot")  }
  #        , "3" = { plot.Desc.numeric(x, main=main, ...) }
  # )

  if (x$unique %[]% c(0, 2)) {
    plot.Desc.logical(x, main = main, ...)
  } else if (x$unique %(]% c(2, 12) | (x$maxrows > 0)) {
    plot.Desc.numeric(x, main = main, args.hist = list(type = "mass"), ...)
  } else {
    plot.Desc.numeric(x, main = main, ...)
  }

  invisible()
}


plot.Desc.ordered <- function(x, main = NULL, ...) {
  plot.Desc.factor(x, main = main, ...)
}


plot.Desc.logical <- function(x, main = NULL, xlab = "", col = NULL,
                              legend = TRUE, xlim = c(0, 1), confint = TRUE, ...) {
  main <- Reduce(
    function(x, y) ifelse(!is.null(x), x, y),
    c(main, x$main, deparse(substitute(x)))
  )


  if (is.null(col)) {
    col <- c(Pal()[1:2], "grey80", "grey60", "grey40")
  } else {
    col <- rep(col, length.out = 5)
  }

  tab <- x$afrq
  ptab <- x$rfrq[, 1]
  if (nrow(x$rfrq) > 2) stop("!plot.Desc.logical! can only display 2 levels")
  oldpar <- par(no.readonly = TRUE)
  on.exit(par(oldpar))

  par(mar = c(4.1, 2.1, 0, 2.1))
  if (!is.na(main)) par(oma = c(0, 0, 3, 0))

  plot(
    x = ptab[1], y = 1, cex = 0.8, xlim = xlim, yaxt = "n", ylab = "",
    type = "n", bty = "n", xlab = xlab, main = NA
  )
  segments(x0 = 0, x1 = 1, y0 = 1, y1 = 1, col = "grey")
  segments(x0 = c(0, 1), x1 = c(0, 1), y0 = 0.8, y1 = 1.2, col = "grey")

  # insert grid
  segments(
    x0 = seq(0, 1, 0.1), x1 = seq(0, 1, 0.1), y0 = 0.8, y1 = 1.2,
    col = "grey", lty = "dotted"
  )
  rect(xleft = 0, ybottom = 0.95, xright = ptab[1], ytop = 1.05, col = col[1]) # greenyellow
  rect(xleft = ptab[1], ybottom = 0.95, xright = 1, ytop = 1.05, col = col[2]) # green4

  if (confint) {
    ci.99 <- BinomCI(tab[1], sum(tab), conf.level = 0.99)[2:3]
    ci.95 <- BinomCI(tab[1], sum(tab), conf.level = 0.95)[2:3]
    ci.90 <- BinomCI(tab[1], sum(tab), conf.level = 0.90)[2:3]
    rect(xleft = ci.99[1], ybottom = 0.9, xright = ci.99[2], ytop = 1.1, col = col[3]) # olivedrab1
    rect(xleft = ci.95[1], ybottom = 0.9, xright = ci.95[2], ytop = 1.1, col = col[4]) # olivedrab3
    rect(xleft = ci.90[1], ybottom = 0.9, xright = ci.90[2], ytop = 1.1, col = col[5]) # olivedrab4
    segments(x0 = ptab[1], x1 = ptab[1], y0 = 0.7, y1 = 1.3)
  }

  if (legend) {
    legend(
      x = 0, y = 0.75, legend = c("ci.99     ", "ci.95     ", "ci.90     "),
      box.col = "white",
      fill = col[3:5], bg = "white", cex = 1, ncol = 3,
      text.width = c(0.2, 0.2, 0.2)
    )
  }
  if (length(rownames(tab)) == 1) {
    text(rownames(tab), x = ptab[1] / 2, y = 1.2)
  } else {
    text(rownames(tab), x = c(ptab[1], ptab[1] + 1) / 2, y = 1.2)
  }

  if (!is.na(main)) title(main = main, outer = TRUE)

  if (!is.null(DescToolsOptions("stamp"))) Stamp()

  invisible()
}


plot.Desc.Date <- function(x, main = NULL, breaks = NULL,
                           type = c(1, 2, 3), ...) {
  hist.axis <- function(mids, val, breaks) {
    # define a more appropriate hist x-axis as Werner Stahel suggested

    if (identical(breaks, "days")) {
      mdate <- as.Date(val, origin = "1970-01-01")
      axis(side = 1, at = mids, labels = Day(mdate))

      idx <- c(TRUE, diff(Month(mdate)) == 1)
      axis(
        side = 1, at = mids[idx], labels = Month(mdate, "mm")[idx],
        line = 1, lwd = NA
      )

      idx <- c(TRUE, diff(Year(mdate)) == 1)
      axis(
        side = 1, at = mids[idx], labels = Year(mdate)[idx],
        line = 2, lwd = NA
      )
    } else if (identical(breaks, "weeks")) {
      mdate <- as.Date(val, origin = "1970-01-01")
      axis(side = 1, at = mids, labels = tolower(Month(mdate, "mm")))

      idx <- c(TRUE, diff(Month(mdate)) == 1)
      axis(
        side = 1, at = mids[idx], labels = Month(mdate, "mm")[idx],
        line = 1, lwd = NA
      )

      idx <- c(TRUE, diff(Year(mdate)) == 1)
      axis(
        side = 1, at = mids[idx], labels = Year(mdate)[idx],
        line = 2, lwd = NA
      )
    } else if (identical(breaks, "months")) {
      mdate <- as.Date(val, origin = "1970-01-01")
      axis(side = 1, at = mids, labels = tolower(Month(mdate, "mm")))

      idx <- c(TRUE, diff(Year(mdate)) == 1)
      axis(
        side = 1, at = mids[idx], labels = Year(mdate)[idx],
        line = 1, lwd = NA
      )
    } else if (identical(breaks, "quarters")) {
      mdate <- as.Date(val, origin = "1970-01-01")
      axis(side = 1, at = mids, labels = paste("Q", Quarter(mdate), sep = "-"))

      idx <- c(TRUE, diff(Year(mdate)) == 1)
      axis(
        side = 1, at = mids[idx], labels = Year(mdate)[idx],
        line = 1, lwd = NA
      )
    } else if (identical(breaks, "years")) {
      mdate <- as.Date(val, origin = "1970-01-01")
      axis(side = 1, at = mids, labels = Year(mdate))
    } else {
      axis(side = 1, at = mids, labels = x$freq$level)
    }
  }


  main <- Reduce(
    function(x, y) ifelse(!is.null(x), x, y),
    c(main, x$main, deparse(substitute(x)))
  )


  # plots exp-obs dotcharts of weekdays and months
  oldpar <- par(no.readonly = TRUE)
  on.exit(par(oldpar))

  # par(mar=c(10.1,3.1,4.1,1.1), oma=c(0,9,0,0), mfrow=c(1,1))
  par(oma = c(0, 9, 0, 0))

  # days plot type = 1
  if (any(type == 1)) {
    tab <- x$dperctab$freq
    r.chi <- x$d.chisq.test

    dotchart(as.numeric(r.chi$exp[]),
      xlim = range(pretty(range(c(r.chi$exp[], r.chi$obs[])))),
      color = "black", bg = "white", pch = 21, cex = 0.8, xpd = TRUE
    )
    mtext(side = 2, at = 7:1, line = 2, names(r.chi$exp), las = 1)
    points(
      x = as.vector(r.chi$obs), y = 7:1, col = "black", bg = "black",
      pch = 21, cex = 1.2
    )
    points(
      x = as.vector(r.chi$exp), y = 7:1, col = "black", bg = "white",
      pch = 21, cex = 1.2
    )

    if (!is.na(main)) title(main = gettextf("%s (a: weekday)", main))

    if (!is.null(DescToolsOptions("stamp"))) {
      Stamp()
    }
  }

  if (any(type == 2)) {
    r.chi <- x$m.chisq.test
    month_xlim <- range(pretty(range(c(r.chi$exp[], r.chi$obs[]))))
    dotchart(as.numeric(r.chi$exp[]),
      xlim = month_xlim,
      color = "black", bg = "white", pch = 21, cex = 0.8, xpd = TRUE
    )
    mtext(side = 2, at = 12:1, line = 2, names(r.chi$exp), las = 1)
    points(
      x = as.vector(r.chi$obs), y = 12:1, col = "black", bg = "black",
      pch = 21, cex = 1.2
    )
    points(
      x = as.vector(r.chi$exp), y = 12:1, col = "black", bg = "white",
      pch = 21, cex = 1.2
    )

    legend(
      x = "bottom", inset = -0.5, legend = c("expected", "observed"),
      xpd = TRUE, ncol = 2,
      pch = c(21), col = c("black", "black"), bg = "white",
      pt.bg = c("white", "black"), cex = 1,
      pt.cex = 1, xjust = 0.5, adj = c(0, 0.5), text.width = c(4, 4)
    )

    # if(!is.na(main) & is.null(wrd)) {
    #   title(main=gettextf("%s (b: month)", main))
    # }
    if (!is.na(main)) title(main = gettextf("%s (b: month)", main))

    if (!is.null(DescToolsOptions("stamp"))) {
      Stamp()
    }
  }

  if (any(type == 3)) {
    Mar(NULL, 0)
    b <- barplot(x$freq$freq,
      space = 0, main = NA,
      xaxt = "n", col = NA, xlab = "", las = 1
    )
    # breaks can be:  c("month","days","weeks","quarter","year")
    hist.axis(mids = b, val = x$freq$level, breaks = x$hbreaks)

    if (!is.na(main)) title(main = gettextf("%s (c: %s)", main, x$hbreaks))

    if (!is.null(DescToolsOptions("stamp"))) {
      Stamp()
    }
  }
}


plot.Desc.ts <- function(x, main = NULL, ...) {
  main <- Reduce(
    function(x, y) ifelse(!is.null(x), x, y),
    c(main, x$main, deparse(substitute(x)))
  )

  PlotACF(x$x, main = main, ...)
}


plot.Desc.xtabs <- function(x, main = NULL, col1 = NULL, col2 = NULL,
                            horiz = TRUE, ...) {
  plot.Desc.table(x, main, col1, col2, horiz, ...)
}


plot.Desc.table <- function(x, main = NULL, col1 = NULL, col2 = NULL,
                            horiz = TRUE, ..., xlab = NULL, ylab = NULL, which = c(1,2)) {
  opt <- DescToolsOptions(stamp = NULL)

  oldpar <- par(no.readonly = TRUE)
  on.exit(par(oldpar))

  if (is.null(main)) main <- x$main
  if (is.null(xlab)) xlab <- Coalesce(names(dimnames(x$tab))[2], "x")
  if (is.null(ylab)) ylab <- Coalesce(names(dimnames(x$tab))[1], "y")

  if (length(dim(x$tab)) == 1) {
    #    maxrows <- InDots(..., arg="maxrows", default = 12)
    #    plot.Desc.factor(Untable(x)[,], main=main, wrd=wrd, maxrows=maxrows, col=col1)
    #
    #   CHECK if maxrows necessary!! ***********

    #  This is baaaaaaaaaaaaaaaaaadddddddd   *******************
    plot(Desc(Untable(x$tab)[, 1]), main = main, col = col1)
    # width <- 6
    # height <- 4
  } else if (length(dim(x$tab)) > 2) {
    mosaicplot(x$tab, main = main, cex = 0.8, las = 1, col = col1, ...)

    # width <- 8
    # height <- 8  # dimension for 2 mosaicplots
    # par(mfrow=c(1,1))
    # par(mar=c(3.1,4.1,1.1,0.5), oma=c(0,0,ifelse(is.na(main), 0, 2),0))
  } else {
    if (is.null(col1)) {
      col1 <- colorRampPalette(c(Pal()[1], "white", Pal()[2]), space = "rgb")(
        ncol(x$tab)
      )
    }
    if (is.null(col2)) {
      col2 <- colorRampPalette(c(Pal()[2], "white", Pal()[1]), space = "rgb")(
        nrow(x$tab)
      )
    }

    if(length(which) == 2){
      if (horiz) {
        # width <- 16
        # height <- 6.5  # dimension for 2 mosaicplots
        par(mfrow = c(1, 2))
        par(oma = c(1.1, 2.1, ifelse(is.na(main), 0, 2.1), 0))
      } else {
        # width <- 7
        # height <- 14  # dimension for 2 mosaicplots
        par(mfrow = c(2, 1), xpd = TRUE)
        par(oma = c(3.1, 1.1, ifelse(is.na(main), 0, 2), 0))
      }
    }
    
    if(any(which==1))
      PlotMosaic(x$tab, main = NA, xlab = NA, ylab = NA, horiz = TRUE, cols = col1)
    
    if(any(which==2))
      PlotMosaic(x$tab, main = NA, xlab = NA, ylab = NA, horiz = FALSE, cols = col2)

    title(xlab = xlab, outer = TRUE, line = -1, font = 2)
    title(ylab = ylab, outer = TRUE, line = 0, font = 2)
  }

  if (!is.na(main) && (length(dim(x$tab)) == 2)) 
    title(main, outer = ifelse(length(which)==2, TRUE, FALSE))

  options(opt)
  if (!is.null(DescToolsOptions("stamp"))) Stamp()

  # invisible(list(width=width, height=height))
  invisible()
  
}




plot.Desc.matrix <- function(x, main = NULL, col1 = NULL, col2 = NULL,
                             horiz = TRUE, ...) {
  # treat matrix as table
  plot.Desc.table(x, main = main, col1 = col1, col2 = col2, horiz = horiz, ...)
}


plot.Desc.xtabs <- function(x, main = NULL, col1 = NULL, col2 = NULL,
                            horiz = TRUE, ...) {
  # treat matrix as table
  plot.Desc.table(x, main = main, col1 = col1, col2 = col2, horiz = horiz, ...)
}


plot.Desc.factfact <- function(x, main = NULL, col1 = NULL, col2 = NULL,
                               horiz = TRUE, ...) {
  plot.Desc.table(x, main = main, col1 = col1, col2 = col2, horiz = horiz, ...)
}

# plot.Desc.numfact <- function(x, main=NULL, notch=FALSE, add_ni = TRUE,
#                      ... ){
#
#   # PlotMultiDens() would maybe be nice as well
#   # or perhaps violinplot??
#
#   if(is.null(main))
#     main <- x$main
#
#   # create a new graphics window
#   par(mar=c(5, 4, 2*add_ni, 2) + .1, oma=c(0, 0, 4.1, 0))
#
#   layout(matrix(c(1,2), ncol=2, byrow=TRUE), widths=c(2,1), TRUE)
#   boxplot(x$x ~ x$g, notch=notch, type="n", xaxt="n", yaxt="n", ... )
#   grid(nx=NA, ny=NULL)
#   bx <- boxplot(x$x ~ x$g, col="white", notch=notch, add=TRUE, cex.axis=0.8,
#         ... )
#
#   if(add_ni)
#     mtext(paste("n=", bx$n, sep=""), side=3, line=1, at=1:length(bx$n),
#          cex=0.8)
#
#   plot.design(x$x ~ x$g, cex=0.8, xlab="", ylab="", cex.axis=0.8, main="",
#                ... )
#   mtext( "means", side=3, line=1, cex=0.8)
#
#   title(main=main, outer=TRUE)
#
#   if(!is.null(DescToolsOptions("stamp")))  Stamp()
#
#   # reset layout
#   layout(1)
#
#   invisible()
#
# }



plot.Desc.numfact <- function(x, main = NULL, add_ni = TRUE,
                              args.boxplot = NULL,
                              col = DescToolsOptions("col"),
                              xlim = NULL, args.legend = NULL,
                              type = c("design", "dens"), ...) {
  opt <- DescToolsOptions(stamp = NA)

  type <- match.arg(type)

  if (is.null(main)) {
    main <- x$main
  }

  z <- split(x$x, x$g)


  if (type == "dens") {
    # Alter-Geschlechtsplot
    layout(matrix(c(1, 2), nrow = 2, byrow = TRUE),
      heights = c(2, 1.5)[1:2], TRUE
    )
    par(mar = c(0, 6.1, 1.1, 2.1), oma = c(0, 0, 3, 0))

    b <- PlotMultiDens(z,
      xlim = xlim, col = col,
      args.legend = args.legend,
      xaxt = "n", panel.first = grid(col = "darkgrey"),
      ylab = "", main = "", las = 1, na.rm = TRUE, ...
    )

    par(mar = c(3.1, 6.1, 1.1, 2.1))

    # set defaults for the boxplot
    args.boxplot1 <- list(
      x = z,
      frame.plot = FALSE, main = "",
      boxwex = 0.5, horizontal = TRUE,
      ylim = b$xlim, yaxt = "n", xaxt = "n",
      outcex = 1.3, outcol = rgb(0, 0, 0, 0.5),
      col = SetAlpha(col, 0.6)
    )
    if (!is.null(args.boxplot)) {
      args.boxplot1[names(args.boxplot)] <- args.boxplot
    }
    DoCall("boxplot", args.boxplot1)

    axis(side = 1)
    axis(side = 2, labels = names(z), at = seq(length(z)), las = 1, lwd = 0)
  } else {
    # create a new graphics window
    par(mar = c(5, 4, 2 * add_ni, 2) + .1, oma = c(0, 0, 4.1, 0))

    layout(matrix(c(1, 2), ncol = 2, byrow = TRUE), widths = c(2, 1), TRUE)

    boxplot(z, col = par("bg"), border = par("bg"), xaxt = "n", yaxt = "n", ...)
    # set defaults for the boxplot
    args.boxplot1 <- list(
      x = z,
      frame.plot = FALSE, main = "",
      horizontal = FALSE,
      col = "white", add = TRUE, cex.axis = 0.8,
      panel.first = grid(nx = NA, ny = NULL)
    )
    if (!is.null(args.boxplot)) {
      args.boxplot1[names(args.boxplot)] <- args.boxplot
    }

    args.boxplot1["panel.first"]

    bx <- DoCall("boxplot", args.boxplot1)

    if (add_ni) {
      mtext(paste("n=", bx$n, sep = ""),
        side = 3, line = 1,
        at = 1:length(bx$n), cex = 0.8
      )
    }
    d.frm <- data.frame(x$x, factor(x$g))
    names(d.frm) <- c(x$xname, x$gname)
    plot.design(d.frm,
      cex = 0.8, xlab = "", ylab = "",
      cex.axis = 0.8, main = ""
    )

    mtext("means", side = 3, line = 1, cex = 0.8)
  }

  title(main = main, outer = TRUE)

  DescToolsOptions(opt)

  if (!is.null(DescToolsOptions("stamp"))) {
    Stamp()
  }

  # reset layout
  layout(1)

  invisible()
}




plot.Desc.numnum <- function(x, main = NULL, col = SetAlpha(1, 0.3),
                             pch = NULL, cex = par("cex"), bg = par("bg"),
                             xlab = NULL, ylab = NULL, smooth = NULL, smooth.front = TRUE,
                             conf.level = 0.95, ...) {
  if (is.null(main)) main <- x$main
  if (is.null(xlab)) xlab <- x$gname
  if (is.null(ylab)) ylab <- x$xname

  plot(x = x$g, y = x$x, type = "n", main = main, xlab = xlab, ylab = ylab, ...)
  grid()
  # smoother should be in front of the points, this is ok, if x is long:
  if (smooth.front) {
    points(x = x$g, y = x$x, col = col, pch = pch, cex = cex, bg = bg)
  }

  smoot <- match.arg(smooth, choices = c("none", "loess", "lm", "spline", "exp"))

  if (is.null(smooth)) {
    if (x$nvalid < 500) {
      smooth <- "loess"
    } else {
      smooth <- "spline"
    }
  }

  if (identical(smooth, NA) || smooth == "none") {
    # do nothing
  } else if (smooth == "loess") {
    # lines(loess(x=x$g, y=x$x, na.action = na.omit))
    lines(loess(x$x ~ x$g, na.action = na.omit), conf.level = conf.level)
  } else if (smooth == "spline") {
    with(na.omit(data.frame(y = x$x, x = x$g)),
      lines(smooth.spline(x = x, y = y)),
      conf.level = conf.level
    )
  } else if (smooth == "lm") {
    #    lines(lm(x$x ~ x$g, na.action = na.omit))
    lines(
      lm(y ~ x, data = data.frame(y = x$x, x = x$g)),
      conf.level = conf.level
    )
  } else if (smooth == "exp") {
    lines.lmlog(
      lm(log(y) ~ x, data = data.frame(y = x$x, x = x$g)),
      conf.level = conf.level
    )
  }

  if (!smooth.front) {
    points(x = x$g, y = x$x, col = col, pch = pch, cex = cex, bg = bg)
  }

  invisible()
}

# overwrite fixed coded arguments, pretty cool idea!!
#
# PlotIt <- function(x, y, ...) {
#
#   arguments <- list(
#     x = x,
#     y = y,
#     ...,
#     type = "l",
#     asp = 1
#   )
#
#   arguments <- arguments[!duplicated(names(arguments))]
#
#   do.call("plot", arguments)
# }


plot.Desc.factnum <- function(x, main = NULL, col = NULL,
                              add_ni = TRUE, smooth = NULL, ...) {
  if (is.null(main)) main <- x$main

  usr <- par("usr")
  on.exit(par(usr))
  mar <- c(5, 4, 2 * add_ni, 2) + .1

  par(mar = mar, oma = c(0, 0, 4.1, 0))

  boxargs <- list(
    # these sets will survive
    formula = x$g ~ x$x, type = "n", xaxt = "n", yaxt = "n", ...,
    xlab = "", ylab = "", col = Coalesce(col, "white"),
    cex.axis = par("cex"), las = 1
  ) # these will only be used if they're not in ...
  boxargs <- boxargs[!duplicated(names(boxargs))]

  layout(matrix(c(1, 2), ncol = 2, byrow = TRUE), widths = c(2, 3), TRUE)

  # omit axis labels here, as Vilmantas doesn't like them... ;-)
  do.call("boxplot", boxargs)
  grid(nx = NA, ny = NULL)
  boxargs$add <- TRUE
  boxargs$xaxt <- boxargs$yaxt <- NULL
  bx <- do.call("boxplot", boxargs)

  if (add_ni) {
    # mtext does not support string rotation:
    # https://stat.ethz.ch/pipermail/r-help/2006-February/087775.html
    mtext(paste("n=", bx$n, sep = ""),
      side = 3, line = 1,
      at = 1:length(bx$n), cex = 0.8,
      las = InDots(..., arg = "las", default = 1), xpd = NA
    )
  }

  if (nrow(x$ptab) < 3) {
    if (!is.null(x$binci)) ylim <- range(pretty(x$binci)) else ylim <- NULL

    plot(x$ptab[2, ],
      xaxt = "n", las = 1,
      ylab = "", xlab = "Quantiles of x", ylim = ylim
    )
    axis(side = 1, at = 1:10, labels = gettextf("Q%s", 1:10))
    grid()

    if (!is.null(x$binci)) {
      ErrBars(x$binci)
    }

    smooth <- Coalesce(smooth, x$smooth, TRUE)

    if (ncol(x$ptab) > 6 && smooth) {
      lines(loess(p ~ x, data.frame(p = x$ptab[2, ], x = 1:ncol(x$ptab))))
    }
    points(
      x = 1:ncol(x$atab), y = x$ptab[2, ],
      pch = 21, cex = 1.5, bg = "white", type = "b"
    )
  } else {
    if (is.null(col)) {
      col <- colorRampPalette(
        c(Pal()[1], "white", Pal()[2]),
        space = "rgb"
      )(nrow(x$ptab))
    }

    PlotMosaic(x$ptab,
      main = NA, xlab = NA, ylab = NA, horiz = FALSE, cols = col,
      cex = InDots(..., arg = "cex", default = par("cex")),
      las = InDots(..., arg = "las", default = 1), mar = mar
    )
  }

  title(main = main, outer = TRUE)

  if (!is.null(DescToolsOptions("stamp"))) {
    Stamp()
  }
  
  layout(matrix(1))           # reset layout on exit
  
  invisible()
}





printWrd <- function(x, main = NULL, plotit = NULL, ..., wrd = wrd) {
  # x is a Desc object, wrd the handle to a word instance

  WrdPlotDesc <- function(z, wrd) {
    .plotReset <- function() {
      layout(matrix(1))
      par(
        xlog = FALSE, ylog = FALSE, adj = 0.5, ann = TRUE,
        ask = FALSE, bg = "white", bty = "o", cex = 1, cex.axis = 1,
        cex.lab = 1, cex.main = 1.2, cex.sub = 1, col = "black",
        col.axis = "black", col.lab = "black", col.main = "black",
        col.sub = "black", crt = 0, err = 0L, family = "", fg = "black",
        fig = c(0, 1, 0, 1), fin = c(12.8333333333333, 8), font = 1L,
        font.axis = 1L, font.lab = 1L, font.main = 2L, font.sub = 1L,
        #      lab = c(5L, 5L, 7L), las = 0L, lend = "round", lheight = 1,
        lab = c(5L, 5L, 7L), lend = "round", lheight = 1,
        ljoin = "round", lmitre = 10, lty = "solid", lwd = 1,
        mai = c(1.36, 1.09333, 1.093333, 0.56), mar = c(5.1, 4.1, 4.1, 2.1),
        mex = 1, mfcol = c(1L, 1L), mfg = c(1L, 1L, 1L, 1L),
        mfrow = c(1L, 1L), mgp = c(3, 1, 0), mkh = 0.001, new = FALSE,
        oma = c(0, 0, 0, 0), omd = c(0, 1, 0, 1), omi = c(0, 0, 0, 0),
        pch = 1L, pin = c(11.18, 5.54666666666667),
        plt = c(0.0851948051948052, 0.956363636363636, 0.17, 0.863333333333333),
        ps = 16L, pty = "m", smo = 1, srt = 0, tck = NA_real_,
        tcl = -0.5, usr = c(0, 1, 0, 1), xaxp = c(0, 1, 5),
        xaxs = "r", xaxt = "s", xpd = FALSE,
        yaxp = c(0, 1, 5), yaxs = "r", yaxt = "s", ylbias = 0.2
      )
      #   par(
      #     xlog = FALSE, ylog = FALSE,
      #     mai = c(1.36, 1.09333, 1.093333, 0.56), mar = c(5.1, 4.1,4.1, 2.1),
      #     mex = 1, mfcol = c(1L, 1L), mfg = c(1L, 1L, 1L, 1L),
      #     mfrow = c(1L, 1L),
      #     oma = c(0, 0, 0, 0), omd = c(0, 1, 0, 1), omi = c(0, 0, 0, 0),
      #     usr = c(0, 1, 0, 1), xpd = FALSE
      #     )
    }


    .plotReset()

    if (identical(z[[1]]$noplot, TRUE)) {
      # identical as noplot will not be present in filled objects!!
      # there's nothing to plot, the variable might be empty, so just leave here
    } else {
      if (any(z[[1]]$class %in% c("factor", "ordered", "character") ||
        (z[[1]]$class == "integer" && !is.null(z[[1]]$freq)))) {
        plot.Desc(z, main = NA)
        WrdPlot(
          width = 8, height = pmin(2 + 3 / 6 * nrow(z[[1]]$freq), 10),
          dfact = 2.7, crop = c(0, 0, 0, 0), wrd = wrd, append.cr = FALSE
        )
      } else if (any(z[[1]]$class %in% c("numeric", "integer"))) {
        plot.Desc(z, main = NA)
        WrdPlot(
          width = 8, height = 5.0, dfact = 2.3,
          crop = c(-.2, 0, 0, 0), wrd = wrd, append.cr = FALSE
        )
      } else if (any(z[[1]]$class %in% "logical")) {
        plot.Desc(z, main = NA)
        WrdPlot(
          width = 6, height = 4, dfact = 2.6,
          crop = c(-.2, 0.2, 1, 0), wrd = wrd, append.cr = FALSE
        )
      } else if (z[[1]]$class == "Date") {
        plot.Desc(z, main = NA, type = 1)
        WrdPlot(
          width = 6.5, height = 5, dfact = 2.5, wrd = wrd,
          append.cr = TRUE
        )
        plot.Desc(z, main = NA, type = 2)
        WrdPlot(
          width = 6.5, height = 6.2, dfact = 2.5, wrd = wrd,
          append.cr = TRUE
        )
        plot.Desc(z, main = NA, type = 3)
        WrdPlot(
          width = 6.5, height = 4, dfact = 2.5, wrd = wrd,
          append.cr = TRUE
        )
      } else if (z[[1]]$class %in% c("table", "matrix", "factfact")) {
        plot.Desc(z, main = NA, horiz = z[[1]]$horiz)
        if (z[[1]]$horiz) {
          WrdPlot(
            width = 16, height = 6.5, dfact = 2.5, wrd = wrd,
            append.cr = TRUE
          )
        } else {
          WrdPlot(
            width = 7, height = 14, dfact = 2.5, wrd = wrd,
            append.cr = TRUE
          )
        }
      } else if (z[[1]]$class %in% c("numnum")) {
        plot.Desc(z, main = NA)
        WrdPlot(
          width = 6.5, height = 6.5 / gold_sec_c, dfact = 2.5,
          crop = c(0, 0, 0.2, 0), wrd = wrd, append.cr = TRUE
        )
      } else if (z[[1]]$class %in% c("numfact")) {
        plot.Desc(z, main = NA)
        WrdPlot(
          width = 15, height = 7, dfact = 2.2,
          crop = c(0, 0, 0.2, 0), wrd = wrd, append.cr = TRUE
        )
      } else if (z[[1]]$class %in% c("factnum")) {
        plot.Desc(z, main = NA)
        WrdPlot(
          width = 15, height = 7, dfact = 2.2,
          crop = c(0, 0, 0.2, 0), wrd = wrd, append.cr = TRUE
        )
      }
    }
    invisible()
  }


  # start main proc  ****************

  # get fixed font
  fixedfont <- getOption("fixedfont", list(name = "Consolas", size = 7))

  for (i in seq_along(x)) {
    # # skip object header entries
    # if(names(x[i]) == "_objheader")
    #   next

    if (x[[i]]$class == "header") {
      if (is.null(x[[i]][["abstract"]])) {
        txt <- .CaptOut(print.Desc(x[i]))[-(1:2)]
        WrdCaption(x[[i]]$main, wrd = wrd)
        ToWrd(txt = txt, wrd = wrd)
        # WrdText(txt=txt, wrd=wrd )
      } else {
        attr(x[[i]]$abstract, "main") <- x[[i]][["main"]]
        ToWrd(x[[i]]$abstract, wrd = wrd)
      }
    } else {
      WrdCaption(x[[i]]$main, wrd = wrd)

      if (!is.null(x[[i]]$label)) {
        lblfont <- InDots(..., arg = "font", default = list(size = 8))
        lblfont$size <- 8
        ToWrd.character(
          x = paste("\n", x[[i]]$label, "\n", sep = ""),
          font = lblfont, wrd = wrd
        )
      }


      txt <- .CaptOut(print.Desc(x[i], nolabel = TRUE))[-(1:2)]

      if (x[[i]]$class == "Date") {
        WrdTable(nrow = 4, ncol = 2, wrd = wrd)
        # merge cells in the first row
        wrd[["Selection"]]$MoveRight(
          Unit = wdConst$wdCharacter, Count = 2,
          Extend = wdConst$wdExtend
        )
        wrd[["Selection"]][["Cells"]]$Merge()

        ToWrd(x = txt[1:6], font = fixedfont, wrd = wrd)
        wrd[["Selection"]]$MoveRight(wdConst$wdCell, 1, 0)
        ToWrd(x = txt[-c(1:6)], font = fixedfont, wrd = wrd)
      } else {
        if (max(unlist(lapply(txt, nchar))) < 59) {
          # decide if two rows or 2 columns ist adequate
          WrdTable(nrow = 1, ncol = 2, wrd = wrd)
          x[[i]]$horiz <- FALSE
        } else {
          WrdTable(nrow = 2, ncol = 1, wrd = wrd)
          x[[i]]$horiz <- TRUE
        }

        ToWrd(x = txt, font = fixedfont, wrd = wrd)
      }

      wrd[["Selection"]]$MoveRight(wdConst$wdCell, 1, 0)

      plotit <- Coalesce(plotit, x$plotit, DescToolsOptions("plotit"), FALSE)
      if (plotit) {
        WrdPlotDesc(x[i], wrd = wrd)
      }


      wrd[["Selection"]]$EndOf(wdConst$wdTable)
      # get out of tablerange
      wrd[["Selection"]]$MoveRight(wdConst$wdCharacter, 2, 0)
      selborder <- wrd[["Selection"]]$Borders(wdConst$wdBorderTop)
      selborder[["LineStyle"]] <- wdConst$wdLineStyleSingle
      wrd[["Selection"]]$TypeParagraph()
    }
  }

  invisible()
}





#' @rdname Desc
#' @export
Desc.palette <- function(x, ...) {
  print(x, ...)
  if (DescToolsOptions("plotit")) {
    plot(x)
  }
}


.has_color <- function() {
  .rstudio_with_ansi_support <- function() {
    if (Sys.getenv("RSTUDIO", "") == "") {
      return(FALSE)
    }
    if ((cols <- Sys.getenv("RSTUDIO_CONSOLE_COLOR", "")) != "" &&
      !is.na(as.numeric(cols))) {
      return(TRUE)
    }
    requireNamespace("rstudioapi", quietly = TRUE) &&
      rstudioapi::isAvailable() &&
      rstudioapi::hasFun("getConsoleHasColor")
  }

  .inside_emacs <- function() {
    Sys.getenv("EMACS") != "" || Sys.getenv("INSIDE_EMACS") != ""
  }

  .emacs_version <- function() {
    ver <- Sys.getenv("INSIDE_EMACS")
    if (ver == "") {
      return(NA_integer_)
    }
    ver <- gsub("'", "", ver)
    ver <- strsplit(ver, ",", fixed = TRUE)[[1]]
    ver <- strsplit(ver, ".", fixed = TRUE)[[1]]
    as.numeric(ver)
  }


  ## this is verbatim from crayon
  ## but it's just this function we use, so don't import...

  enabled <- getOption("crayon.enabled")
  if (!is.null(enabled)) {
    return(isTRUE(enabled))
  }
  if (.rstudio_with_ansi_support() && sink.number() == 0) {
    return(TRUE)
  }
  if (!isatty(stdout())) {
    return(FALSE)
  }
  if (.Platform$OS.type == "windows") {
    if (Sys.getenv("ConEmuANSI") == "ON") {
      return(TRUE)
    }
    if (Sys.getenv("CMDER_ROOT") != "") {
      return(TRUE)
    }
    return(FALSE)
  }
  if (.inside_emacs() &&
    !is.na(.emacs_version()[1]) &&
    .emacs_version()[1] >= 23) {
    return(TRUE)
  }
  if ("COLORTERM" %in% names(Sys.getenv())) {
    return(TRUE)
  }
  if (Sys.getenv("TERM") == "dumb") {
    return(FALSE)
  }
  grepl("^screen|^xterm|^vt100|color|ansi|cygwin|linux",
    Sys.getenv("TERM"),
    ignore.case = TRUE, perl = TRUE
  )
}

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DescTools documentation built on Sept. 26, 2024, 1:07 a.m.