Create a Class Definition

Description

Functions to create (setClass) and manipulate class definitions.

Usage

setClass(Class, representation, prototype, contains=character(),
         validity, access, where, version, sealed, package)

removeClass(Class, where)

isClass(Class, formal=TRUE, where)

getClasses(where, inherits = missing(where))

findClass(Class, where, unique = "")

resetClass(Class, classDef, where)

sealClass(Class, where)

Arguments

Details

These are the functions that create and manipulate formal class definitions. Brief documentation is provided below. See the references for an introduction and for more details.

setClass:

Define Class to be an S-style class. The effect is to create an object, of class "classRepEnvironment", and store this (hidden) in the specified environment or database. Objects can be created from the class (e.g., by calling new), manipulated (e.g., by accessing the object's slots), and methods may be defined including the class name in the signature (see setMethod).

removeClass:

Remove the definition of this class, from the environment where if this argument is supplied; if not, removeClass will search for a definition, starting in the top-level environment of the call to removeClass, and remove the (first) definition found.

isClass:

Is this a the name of a formally defined class? (Argument formal is for compatibility and is ignored.)

getClasses:

The names of all the classes formally defined on where. If called with no argument, all the classes visible from the calling function (if called from the top-level, all the classes in any of the environments on the search list). The inherits argument can be used to search a particular environment and all its parents, but usually the default setting is what you want.

findClass:

The list of environments or positions on the search list in which a class definition of Class is found. If where is supplied, this is an environment (or namespace) from which the search takes place; otherwise the top-level environment of the caller is used. If unique is supplied as a character string, findClass returns a single environment or position. By default, it always returns a list. The calling function should select, say, the first element as a position or environment for functions such as get.

If unique is supplied as a character string, findClass will warn if there is more than one definition visible (using the string to identify the purpose of the call), and will generate an error if no definition can be found.

resetClass:

Reset the internal definition of a class. Causes the complete definition of the class to be re-computed, from the representation and superclasses specified in the original call to setClass.

This function is called when aspects of the class definition are changed. You would need to call it explicitly if you changed the definition of a class that this class extends (but doing that in the middle of a session is living dangerously, since it may invalidate existing objects).

sealClass:

Seal the current definition of the specified class, to prevent further changes. It is possible to seal a class in the call to setClass, but sometimes further changes have to be made (e.g., by calls to setIs). If so, call sealClass after all the relevant changes have been made.

Inheritance and Prototypes

Defining new classes that inherit from (“extend”) other classes is a powerful technique, but has to be used carefully and not over-used. Otherwise, you will often get unintended results when you start to compute with objects from the new class.

As shown in the examples below, the simplest and safest form of inheritance is to start with an explicit class, with some slots, that does not extend anything else. It only does what we say it does.

Then extensions will add some new slots and new behavior.

Another variety of extension starts with one of the built-in data types, perhaps with the intension of modifying R's standard behavior for that class. In this case, the new class inherits the built-in data type as its “data” part. See the “numWithId” example below.

When such a class definition is printed, the data part shows up as a pseudo-slot named “.Data”.

S3 Classes

Earlier, informal classes of objects (usually referred to as “S3” classes) are used by many R functions. It's natural to consider including them as the class for a slot in a formal class, or even as a class to be extended by the new class. This isn't prohibited but there are some disadvantages, and if you do want to include S3 classes, they should be declared by including them in a call to setOldClass. Here are some considerations:

• Using S3 classes somewhat defeats the purpose of defining a formal class: An important advantage to your users is that a formal class provides guarantees of what the object contains (minimally, the classes of the slots and therfore what data they contain; optionally, any other requirements imposed by a validity method).

  But there is no guarantee whatever about the data in an object from an S3 class. It's entirely up to the functions that create or modify such objects. If you want to provide guarantees to your users, you will need a valdity method that explicitly checks the contents of S3-class objects.

• To get the minimal guarantee (that the object in a slot has, or extends, the class for the slot) you should ensure that the S3 classes are known to be S3 classes, with the possible inheritance. To do this, include a call to setOldClass for the S3 classes used.

  Otherwise, the S3 class is undefined (and the code used by setClass will issue a warning). Slot assignments, for example, will not then check for possible errors.

• These caveats apply to S3 classes; that is, objects with a class assigned by some R function but without a formal class definition. In contrast, the built-in data types (numeric, list, etc.) are generally fine as slots or for contains= classes (see the previous section). These data types don't have formal slots, but the base code in the system essentially forces them to contain the type of data they claim to have.

  The data types matrix and array are somewhat in between. They do not have an explicit S3 class, but do have one or two attributes. There is no general problem in having these as slots, but because there is no guarantee of a dimnames slot, they don't work as formal classes. The ts class is treated as a formal class, extending class vector.

References

The R package methods implements, with a few exceptions, the programming interface for classes and methods in the book Programming with Data (John M. Chambers, Springer, 1998), in particular sections 1.6, 2.7, 2.8, and chapters 7 and 8.

While the programming interface for the methods package follows the reference, the R software is an original implementation, so details in the reference that reflect the S4 implementation may appear differently in R. Also, there are extensions to the programming interface developed more recently than the reference. For a discussion of details and ongoing development, see the web page http://developer.r-project.org/methodsPackage.html and the pointers from that page.

See Also

setClassUnion, Methods, makeClassRepresentation

Examples

## A simple class with two slots
setClass("track",
         representation(x="numeric", y="numeric"))
## A class extending the previous, adding one more slot
setClass("trackCurve",
         representation("track", smooth = "numeric"))
## A class similar to "trackCurve", but with different structure
## allowing matrices for the "y" and "smooth" slots
setClass("trackMultiCurve",
         representation(x="numeric", y="matrix", smooth="matrix"),
         prototype = list(x=numeric(), y=matrix(0,0,0),
                          smooth= matrix(0,0,0)))
##
## Suppose we want trackMultiCurve to be like trackCurve when there's
## only one column.
## First, the wrong way.
try(setIs("trackMultiCurve", "trackCurve",
  test = function(obj) {ncol(slot(obj, "y")) == 1}))

## Why didn't that work?  You can only override the slots "x", "y",
## and "smooth" if you provide an explicit coerce function to correct
## any inconsistencies:

setIs("trackMultiCurve", "trackCurve",
  test = function(obj) {ncol(slot(obj, "y")) == 1},
  coerce = function(obj) {
     new("trackCurve",
         x = slot(obj, "x"),
         y = as.numeric(slot(obj,"y")),
         smooth = as.numeric(slot(obj, "smooth")))
  })

## A class that extends the built-in data type "numeric"

setClass("numWithId", representation(id = "character"),
    contains = "numeric")

new("numWithId", 1:3, id = "An Example")