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% File src/library/stats/man/checkMFClasses.Rd
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% File src/library/stats/man/checkMFClasses.Rd
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% Part of the R package, https://www.R-project.org
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% Part of the R package, https://www.R-project.org
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% Copyright 1995-2007 R Core Team
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% Copyright 1995-2019 R Core Team
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% Distributed under GPL 2 or later
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% Distributed under GPL 2 or later
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\name{.checkMFClasses}
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\name{.checkMFClasses}
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\alias{.checkMFClasses}
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\alias{.checkMFClasses}
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\alias{.MFclass}
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\alias{.MFclass}
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\description{
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\description{
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  \code{.checkMFClasses} checks if the variables used in a predict
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  \code{.checkMFClasses} checks if the variables used in a predict
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  method agree in type with those used for fitting.
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  method agree in type with those used for fitting.
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  \code{.MFclass} categorizes variables for this purpose.
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  \code{.MFclass} categorizes variables for this purpose.
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  \code{.getXlevels()} extracts factor levels from \code{\link{factor}} or
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  \code{\link{character}} variables.
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}
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}
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\usage{
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\usage{
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.checkMFClasses(cl, m, ordNotOK = FALSE)
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.checkMFClasses(cl, m, ordNotOK = FALSE)
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.MFclass(x)
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.MFclass(x)
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.getXlevels(Terms, m)
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.getXlevels(Terms, m)
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}
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}
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\arguments{
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\arguments{
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  \item{cl}{a character vector of class descriptions to match.}
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  \item{cl}{a character vector of class descriptions to match.}
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  \item{m}{a model frame.}
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  \item{m}{a model frame (\code{\link{model.frame}()} result).}
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  \item{x}{any \R object.}
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  \item{x}{any \R object.}
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  \item{ordNotOK}{logical: are ordered factors different?}
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  \item{ordNotOK}{logical: are ordered factors different?}
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  \item{Terms}{a \code{terms} object.}
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  \item{Terms}{a \code{terms} object (\code{\link{terms.object}}).}
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}
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}
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\details{
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\details{
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  For applications involving \code{model.matrix} such as linear models
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  For applications involving \code{\link{model.matrix}()} such as linear models
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  we do not need to differentiate between ordered factors and factors as
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  we do not need to differentiate between \emph{ordered} factors and factors as
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  although these affect the coding, the coding used in the fit is
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  although these affect the coding, the coding used in the fit is
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  already recorded and imposed during prediction.  However, other
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  already recorded and imposed during prediction.  However, other
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  applications may treat ordered factors differently:
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  applications may treat ordered factors differently:
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  \code{\link[rpart]{rpart}} does, for example.
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  \code{\link[rpart]{rpart}} does, for example.
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}
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}
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\value{
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\value{
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  \code{.checkMFClasses()} checks and either signals an error calling
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  \code{\link{stop}()} or returns \code{\link{NULL}} invisibly.
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  \code{.MFclass} returns a character string, one of \code{"logical"},
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  \code{.MFclass()} returns a character string, one of \code{"logical"},
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  \code{"ordered"}, \code{"factor"}, \code{"numeric"}, \code{"nmatrix.*"}
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  \code{"ordered"}, \code{"factor"}, \code{"numeric"}, \code{"nmatrix.*"}
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  (a numeric matrix with a number of columns appended) or \code{"other"}.
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  (a numeric matrix with a number of columns appended) or \code{"other"}.
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  \code{.getXlevels} returns a named character vector, or \code{NULL}.
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  \code{.getXlevels} returns a named \code{\link{list}} of character
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  vectors, possibly empty, or \code{\link{NULL}}.
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}
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\examples{
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sapply(warpbreaks, .MFclass) # "numeric" plus 2 x "factor"
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sapply(iris,       .MFclass) # 4 x "numeric" plus "factor"
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mf <- model.frame(Sepal.Width ~ Species,      iris)
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mc <- model.frame(Sepal.Width ~ Sepal.Length, iris)
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.checkMFClasses("numeric", mc) # nothing else
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.checkMFClasses(c("numeric", "factor"), mf)
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## simple .getXlevels() cases :
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(xl <- .getXlevels(terms(mf), mf)) # a list with one entry " $ Species" with 3 levels:
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stopifnot(exprs = {
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  identical(xl$Species, levels(iris$Species))
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  identical(.getXlevels(terms(mc), mc), xl[0]) # a empty named list, as no factors
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  is.null(.getXlevels(terms(x~x), list(x=1)))
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})
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}
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}
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\keyword{utilities}
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\keyword{utilities}