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% File src/library/methods/man/setOldClass.Rd

% Part of the R package, http://www.R-project.org

% Copyright 1995-2010 R Core Team

% Distributed under GPL 2 or later

\name{setOldClass}

\alias{setOldClass}

\alias{.setOldIs}

\alias{POSIXct-class}

\alias{POSIXlt-class}

\alias{POSIXt-class}

\alias{aov-class}

\alias{maov-class}

\alias{anova-class}

\alias{anova.glm-class}

\alias{anova.glm.null-class}

\alias{Date-class}

\alias{data.frame-class}

\alias{data.frameRowLabels-class}

\alias{density-class}

\alias{dump.frames-class}

\alias{factor-class}

\alias{formula-class}

\alias{glm-class}

\alias{glm.null-class}

\alias{hsearch-class}

\alias{integrate-class}

\alias{libraryIQR-class}

\alias{lm-class}

\alias{logLik-class}

\alias{mlm-class}

\alias{mtable-class}

\alias{mts-class}

\alias{ordered-class}

\alias{packageIQR-class}

\alias{packageInfo-class}

\alias{recordedplot-class}

\alias{rle-class}

\alias{socket-class}

\alias{summaryDefault-class}

\alias{summary.table-class}

\alias{oldClass-class}

\alias{.OldClassesList}

\alias{table-class}

\alias{initialize,data.frame-method}

\alias{initialize,factor-method}

\alias{initialize,ordered-method}

\alias{initialize,table-method}

\alias{initialize,summary.table-method}

\title{Register Old-Style (S3) Classes and Inheritance}

\description{

  Register an old-style (a.k.a. \sQuote{S3}) class as a formally defined

  class. The \code{Classes} argument is the character vector used as the

  \code{class} attribute; in particular, if there is more than one

  string, old-style class inheritance is mimicked.  Registering via

  \code{setOldClass} allows S3 classes to appear in method signatures,

  as a slot in an S4 class, or as a superclass of an S4 class.

}

\usage{

setOldClass(Classes, prototype, where, test = FALSE, S4Class)

}

\arguments{

  \item{Classes}{

    A character vector, giving the names for S3

    classes, as they would appear on the right side of an assignment of

    the \code{class} attribute in S3 computations.

    In addition to S3 classes, an object type or other valid data part

    can be specified, if the S3 class is known to require its data to

    be of that form.

  }

\item{prototype}{

    An optional object to use as the prototype.  This should be provided

    as the default S3 object for the class.  If omitted, the S4 class

    created to register the S3 class is \code{VIRTUAL}.  See the

    details.

  }

  \item{where}{

    Where to store the class definitions, the global or top-level

    environment by default.  (When either function is called in the

    source for a package, the class definitions will be included in the

    package's environment by default.)

  }

  \item{test}{flag, if \code{TRUE}, arrange to test inheritance

    explicitly for each object, needed if the S3 class can have a

    different set of class strings, with the same first string.

    This is a different mechanism in implementation and should be

    specified separately for each pair of classes that have an

    optional inheritance.  See the \sQuote{Details}.

  }

  \item{S4Class}{ optionally, the class definition or the class name

    of an S4 class.  The new class will have all the slots and other

    properties of this class, plus its S3 inheritance as defined by

    the \code{Classses} argument.  Arguments \code{prototype} and

    \code{test} must not be supplied in this case.  See the section

    on \dQuote{S3 classes with known attributes} below.

  }

}

\details{

  Each of the names will be defined as an S4 class, extending the

  remaining classes in \code{Classes}, and the class \code{oldClass},

  which is the \sQuote{root} of all old-style classes. S3 classes have

  no formal definition, and therefore no formally defined slots. If a

  \code{prototype} argument is supplied in the call to

  \code{setOldClass()}, objects from the class can be generated, by a

  call to \code{\link{new}}; however, this usually not as relevant as

  generating objects from subclasses (see the section on extending S3

  classes below).   If  a prototype is not provided,

   the class will be created as a virtual S4 class.

  The main disadvantage is that the prototype object in an S4 class that

  uses this class as a slot will have a \code{NULL} object in that slot,

  which can sometimes lead to confusion.

  Beginning with version 2.8.0 of \R, support is provided for using a

  (registered) S3 class as a superclass of a new S4 class.  See the

  section on extending S3 classes below, and the examples.

  See \link{Methods} for the details of method dispatch and

  inheritance.

  Some S3 classes cannot be represented as an ordinary combination of S4

  classes and superclasses, because objects from the S3 class can have a

  variable set of strings in the class. It is still possible to register

  such classes as S4 classes, but now the inheritance has to be verified

  for each object, and you must call \code{setOldClass} with argument

  \code{test=TRUE} once for each superclass.

  For example, ordered factors \emph{always} have the S3

  class \code{c("ordered", "factor")}.  This is proper behavior, and

  maps simply into two S4 classes, with \code{"ordered"} extending

  \code{"factor"}.

  But objects whose class attribute has \code{"POSIXt"} as the first

  string may have either (or neither) of \code{"POSIXct"} or

  \code{"POSIXlt"} as the second string.  This behavior can be mapped

  into S4 classes but now to evaluate \code{is(x, "POSIXlt")}, for

  example, requires checking the S3 class attribute on each object.

  Supplying the \code{test=TRUE} argument to \code{setOldClass} causes

  an explicit test to be included in the class definitions.  It's

  never wrong to have this test, but since it adds significant

  overhead to methods defined for the inherited classes, you should

  only supply this argument if it's known that object-specific tests

  are needed.

  The list \code{.OldClassesList} contains the old-style classes that

  are defined by the methods package.  Each element of the list is a

  character vector, with multiple strings if inheritance is included.

  Each element of the list was passed to \code{setOldClass} when

  creating the \pkg{methods} package; therefore, these classes can be used

  in \code{\link{setMethod}} calls, with the inheritance as implied by

  the list.

}

\section{Extending S3 classes}{

  A call to \code{setOldClass} creates formal classes corresponding

  to S3 classes, allows these to be used as slots in other classes or in

  a signature in \code{\link{setMethod}}, and mimics the S3

  inheritance.

  In documentation for the initial implementation of S4 classes in \R,

  users were warned against defining S4 classes that contained S3

  classes, even if those had been registered.  The warning was based

  mainly on two points.  1: The S3 behavior of the objects would fail

  because the S3 class would not be visible, for example, when S3

  methods are dispatched.  2: Because S3 classes have no formal

  definition, nothing can be asserted in general about the S3 part of

  an object from such a class.  (The warning was repeated as recently

  as the first reference below.)

  Nevertheless, defining S4 classes to contain an S3 class and extend

  its behavior is attractive in many applications.  The alternative is

  to be stuck with S3 programming, without the flexibility and security of

  formal class and method definitions.

  Beginning with version 2.8.0, \R provides support for extending

  registered S3 classes; that is, for new classes defined by a call to

  \code{\link{setClass}} in which the \code{contains=} argument

  includes an S3 class.  See the examples below.  The support is aimed

  primarily at providing the S3 class information for all classes that

  extend class \linkS4class{oldClass}, in particular by ensuring that

  all objects from such classes contain the S3 class in a special

  slot.

  There are three different ways to indicate an extension to an existing

  S3 class:  \code{setOldClass()},  \code{setClass()} and

  \code{setIs()}.  In most cases, calling \code{setOldClass} is the

  best approach,  but the alternatives may be preferred in the special

  circumstances described below.

  Suppose \code{"A"} is any class extending \code{"oldClass"}. then

  \code{setOldClass(c("B", "A"))}

  creates a new class \code{"B"} whose S3 class

  concatenates \code{"B"}  with \code{S3Class("A")}.  The new class is a

  virtual class.  If \code{"A"} was defined with known attribute/slots,

  then \code{"B"} has these slots also; therefore, you must believe that

  the corresponding S3 objects from class \code{"B"} do indeed have the

  claimed attributes.  Notice that you can supply an S4 definition for the

  new class to specify additional attributes (as described in the next

  section.)

  The first alternative call produces a non-virtual class.

  \code{setClass("B", contains = "A")}

  This creates a non-virtual class with the same slots and superclasses

  as class \code{"A"}.  However, class \code{"B"} is not included in

  the S3 class slot of the new class, unless you provide it explicitly

  in the prototype.

  \code{setClass("B"); setIs("B", "A", .....)}

  This creates a virtual class that extends \code{"A"}, but does not

  contain the slots of \code{"A"}.  The additional arguments to

  \code{\link{setIs}} should provide a coerce and replacement method.

  In order for the new class to inherit S3 methods, the coerce method must

  ensure that the class \code{"A"} object produced has a suitable S3

  class.  The only likely reason to prefer this third approach is that

  class \code{"B"} is not consistent with known attributes in class

  \code{"A"}.

  Beginning with version 2.9.0 of \R, objects from a class extending an

  S3 class will be converted to the corresponding S3 class when being

  passed to an S3 method defined for that class (that is, for one of the

  strings in the S3 class attribute).  This is intended to ensure, as

  far as possible, that such methods will work if they work for ordinary

  S3 objects.  See \code{\link{Classes}} for details.

}

\section{S3 Classes with known attributes}{

  A further specification of an S3 class can be made \emph{if} the

  class is guaranteed to have some attributes of known class (where as

  with slots, \dQuote{known} means that the attribute is an object of

  a specified class, or a subclass of that class).

  In this case, the call to \code{setOldClass()} can supply an S4 class

  definition representing the known structure.  Since S4 slots are

  implemented as attributes (largely for just this reason), the know

  attributes can be specified in the representation of the S4 class.

  The usual technique will be to create an S4 class with the desired

  structure, and then supply the class name or definition as the

  argument \code{S4Class} to \code{setOldClass()}.

  See the definition of class \code{"ts"} in the examples below.  The

  call to \code{\link{setClass}} to create the S4 class can use the same

  class name, as here, so long as the class definition is not sealed.

  In the example, we define \code{"ts"} as a vector structure with a

  numeric slot for \code{"tsp"}.  The validity of this definition relies

  on an assertion that all the S3 code for this class is consistent with

  that definition; specifically, that all \code{"ts"} objects will

  behave as vector structures and will have a numeric \code{"tsp"}

  attribute. We believe this to be true of all the base code in \R, but

  as always with S3 classes, no guarantee is possible.

  The S4 class definition can  have virtual superclasses (as in

  the \code{"ts"} case) if the S3 class is asserted to behave

  consistently with these (in the example, time-series objects are

  asserted to be consistent with the \linkS4class{structure} class).

  For another example, look at the S4 class definition for \code{"data.frame"}.

  Be warned that failures of the S3 class to live up to its asserted

  behavior will usually go uncorrected, since S3 classes inherently

  have no definition, and the resulting invalid S4 objects can cause

  all sorts of grief.  Many S3 classes are not candidates for known

  slots, either because the presence or class of the attributes are

  not guaranteed  (e.g., \code{dimnames} in arrays, although these are

  not even S3 classes), or because the class uses named components of

  a list rather than attributes (e.g., \code{"lm"}).  An attribute

  that is sometimes missing cannot be represented as a slot, not even

  by pretending that it is present with class \code{"NULL"}, because

  attributes unlike slots can not have value \code{NULL}.

  One irregularity that is usually tolerated, however, is to optionally

  add other attributes to those guaranteed to exist (for example,

  \code{"terms"} in \code{"data.frame"} objects returned by

  \code{\link{model.frame}}).  As of version 2.8.0, validity checks by

  \code{\link{validObject}} ignore extra attributes; even if this check

  is tightened in the future, classes extending S3 classes would likely

  be exempted because extra attributes are so common.

}

\seealso{

  \code{\link{setClass}}, \code{\link{setMethod}}

}

\references{

  Chambers, John M. (2008)

  \emph{Software for Data Analysis: Programming with R}

  Springer.  (For the R version: see section 10.6 for method

  selection and section 13.4 for generic functions).

  Chambers, John M. (1998)

  \emph{Programming with Data}

  Springer (For the original S4 version.)

}

\examples{

require(stats)

setOldClass(c("mlm", "lm"))

setGeneric("dfResidual", function(model)standardGeneric("dfResidual"))

setMethod("dfResidual", "lm", function(model)model$df.residual)

## dfResidual will work on mlm objects as well as lm objects

myData <- data.frame(time = 1:10, y = (1:10)^.5)

myLm <- lm(cbind(y, y^3)  ~ time, myData)

showClass("data.frame")# to see the predefined S4 "oldClass"

## two examples extending S3 class "lm", class "xlm" directly

## and "ylm" indirectly

setClass("xlm", representation(eps = "numeric"), contains = "lm")

setClass("ylm", representation(header = "character"), contains = "xlm")

ym1 = new("ylm", myLm, header = "Example", eps = 0.)

## for more examples, see ?\link{S3Class}.

utils::str(.OldClassesList)

\dontshow{

stopifnot(identical(dfResidual(myLm), myLm$df.residual))

removeClass("ylm"); removeClass("xlm")

rm(myData, myLm)

removeGeneric("dfResidual")}

## Examples of S3 classes with guaranteed attributes

## an S3 class "stamped" with a vector and  a "date" attribute

## Here is a generator function and an S3 print method.

## NOTE:  it's essential that the generator checks the attribute classes

stamped <- function(x, date = Sys.time()) {

    if(!inherits(date, "POSIXt"))

      stop("bad date argument")

    if(!is.vector(x))

      stop("x must be a vector")

    attr(x, "date") <- date

    class(x) <- "stamped"

    x

}

print.stamped <- function(x, ...) {

    print(as.vector(x))

    cat("Date: ",  format(attr(x,"date")), "\n")

}

## Now, an S4 class with the same structure:

setClass("stamped4", contains = "vector", representation(date = "POSIXt"))

## We can use the S4 class to register "stamped", with its attributes:

setOldClass("stamped", S4Class = "stamped4")

selectMethod("show", "stamped")

## and then remove "stamped4" to clean up

removeClass("stamped4")

\dontshow{

set.seed(113)}

someLetters <- stamped(sample(letters, 10),

                       ISOdatetime(2008, 10, 15, 12, 0, 0))

st <- new("stamped", someLetters)

st

# show() method prints the object's class, then calls the S3 print method.

stopifnot(identical(S3Part(st, TRUE), someLetters))

# creating the S4 object directly from its data part and slots

new("stamped", 1:10, date = ISOdatetime(1976, 5, 5, 15, 10, 0))

\dontrun{

## The code in R that defines "ts" as an S4 class

setClass("ts", contains = "structure",

      representation(tsp = "numeric"),

      prototype(NA, tsp = rep(1,3)))

# prototype to be a legal S3 time-series

## and now registers it as an S3 class

    setOldClass("ts", S4Class = "ts", where = envir)

}

\dontshow{

  removeClass("stamped")

  rm(someLetters, st)

}

}

\keyword{ programming }

\keyword{ methods }