Nothing
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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