Is an Object from a Class?

Description

Functions to test inheritance relationships between an object and a class (is) or between two classes (extends), and to establish such relationships (setIs, an explicit alternative to the contains= argument to setClass).

Usage

is(object, class2)

extends(class1, class2, maybe = TRUE, fullInfo = FALSE)

setIs(class1, class2, test=NULL, coerce=NULL, replace=NULL,
      by = character(), where = topenv(parent.frame()), classDef =,
      extensionObject = NULL, doComplete = TRUE)

Arguments

Summary of Functions

is:

With two arguments, tests whether object can be treated as from class2.

With one argument, returns all the super-classes of this object's class.

extends:

Does the first class extend the second class? The call returns maybe if the extension includes a test.

When called with one argument, the value is a vector of the superclasses of class1. If argument fullInfo is TRUE, the call returns a named list of objects of class SClassExtension; otherwise, just the names of the superclasses.

setIs:

Defines class1 to be an extension (subclass) of class2. If class2 is an existing virtual class, such as a class union, then only the two classes need to be supplied in the call, if the implied inherited methods work for class1. See the details section below.

Alternatively, arguments coerce and replace should be supplied, defining methods to coerce to the superclass and to replace the part corresponding to the superclass. As discussed in the details and other sections below, this form is often less recommended than the corresponding call to setAs, to which it is an alternative.

Argument test allows conditional inheritance, in which the is() result is tested for each object rather than being determined by the class definition. This form is discouraged when it can be avoided; in particular, note that conditional inheritance is not used to select methods for dispatch.

Details

Arranging for a class to inherit from another class is a key tool in programming. In R, there are three basic techniques, the first two providing what is called “simple” inheritance, the preferred form:

1. By the contains= argument in a call to setClass. This is and should be the most common mechanism. It arranges that the new class contains all the structure of the existing class, and in particular all the slots with the same class specified. The resulting class extension is defined to be simple, with important implications for method definition (see the section on this topic below).

2. Making class1 a subclass of a virtual class either by a call to setClassUnion to make the subclass a member of a new class union, or by a call to setIs to add a class to an existing class union or as a new subclass of an existing virtual class. In either case, the implication should be that methods defined for the class union or other superclass all work correctly for the subclass. This may depend on some similarity in the structure of the subclasses or simply indicate that the superclass methods are defined in terms of generic functions that apply to all the subclasses. These relationships are also generally simple.

3. Supplying coerce and replace arguments to setAs. R allows arbitrary inheritance relationships, using the same mechanism for defining coerce methods by a call to setAs. The difference between the two is simply that setAs will require a call to as for a conversion to take place, whereas after the call to setIs, objects will be automatically converted to the superclass.

   The automatic feature is the dangerous part, mainly because it results in the subclass potentially inheriting methods that do not work. See the section on inheritance below. If the two classes involved do not actually inherit a large collection of methods, as in the first example below, the danger may be relatively slight.

   If the superclass inherits methods where the subclass has only a default or remotely inherited method, problems are more likely. In this case, a general recommendation is to use the setAs mechanism instead, unless there is a strong counter reason. Otherwise, be prepared to override some of the methods inherited.

With this caution given, the rest of this section describes what happens when coerce= and replace= arguments are supplied to setIs.

The coerce and replace arguments are functions that define how to coerce a class1 object to class2, and how to replace the part of the subclass object that corresponds to class2. The first of these is a function of one argument which should be from, and the second of two arguments (from, value). For details, see the section on coerce functions below .

When by is specified, the coerce process first coerces to this class and then to class2. It's unlikely you would use the by argument directly, but it is used in defining cached information about classes.

The value returned (invisibly) by setIs is the revised class definition of class1.

Coerce, replace, and test functions

The coerce argument is a function that turns a class1 object into a class2 object. The replace argument is a function of two arguments that modifies a class1 object (the first argument) to replace the part of it that corresponds to class2 (supplied as value, the second argument). It then returns the modified object as the value of the call. In other words, it acts as a replacement method to implement the expression as(object, class2) <- value.

The easiest way to think of the coerce and replace functions is by thinking of the case that class1 contains class2 in the usual sense, by including the slots of the second class. (To repeat, in this situation you would not call setIs, but the analogy shows what happens when you do.)

The coerce function in this case would just make a class2 object by extracting the corresponding slots from the class1 object. The replace function would replace in the class1 object the slots corresponding to class2, and return the modified object as its value.

For additional discussion of these functions, see the documentation of the setAs function. (Unfortunately, argument def to that function corresponds to argument coerce here.)

The inheritance relationship can also be conditional, if a function is supplied as the test argument. This should be a function of one argument that returns TRUE or FALSE according to whether the object supplied satisfies the relation is(object, class2). Conditional relations between classes are discouraged in general because they require a per-object calculation to determine their validity. They cannot be applied as efficiently as ordinary relations and tend to make the code that uses them harder to interpret. NOTE: conditional inheritance is not used to dispatch methods. Methods for conditional superclasses will not be inherited. Instead, a method for the subclass should be defined that tests the conditional relationship.

Inherited methods

A method written for a particular signature (classes matched to one or more formal arguments to the function) naturally assumes that the objects corresponding to the arguments can be treated as coming from the corresponding classes. The objects will have all the slots and available methods for the classes.

The code that selects and dispatches the methods ensures that this assumption is correct. If the inheritance was “simple”, that is, defined by one or more uses of the contains= argument in a call to setClass, no extra work is generally needed. Classes are inherited from the superclass, with the same definition.

When inheritance is defined by a general call to setIs, extra computations are required. This form of inheritance implies that the subclass does not just contain the slots of the superclass, but instead requires the explicit call to the coerce and/or replace method. To ensure correct computation, the inherited method is supplemented by calls to as before the body of the method is evaluated.

The calls to as generated in this case have the argument strict = FALSE, meaning that extra information can be left in the converted object, so long as it has all the appropriate slots. (It's this option that allows simple subclass objects to be used without any change.) When you are writing your coerce method, you may want to take advantage of that option.

Methods inherited through non-simple extensions can result in ambiguities or unexpected selections. If class2 is a specialized class with just a few applicable methods, creating the inheritance relation may have little effect on the behavior of class1. But if class2 is a class with many methods, you may find that you now inherit some undesirable methods for class1, in some cases, fail to inherit expected methods. In the second example below, the non-simple inheritance from class "factor" might be assumed to inherit S3 methods via that class. But the S3 class is ambiguous, and in fact is "character" rather than "factor".

For some generic functions, methods inherited by non-simple extensions are either known to be invalid or sufficiently likely to be so that the generic function has been defined to exclude such inheritance. For example initialize methods must return an object of the target class; this is straightforward if the extension is simple, because no change is made to the argument object, but is essentially impossible. For this reason, the generic function insists on only simple extensions for inheritance. See the simpleInheritanceOnly argument to setGeneric for the mechanism. You can use this mechanism when defining new generic functions.

If you get into problems with functions that do allow non-simple inheritance, there are two basic choices. Either back off from the setIs call and settle for explicit coercing defined by a call to setAs; or, define explicit methods involving class1 to override the bad inherited methods. The first choice is the safer, when there are serious problems.

References

Chambers, John M. (2008) Software for Data Analysis: Programming with R Springer. (For the R version.)

Chambers, John M. (1998) Programming with Data Springer (For the original S4 version.)

See Also

inherits is nearly always equivalent to is, both for S4 and non-S4 objects, and is somewhat faster. The non-equivalence applies to classes that have conditional superclasses, with a non-trivial test= in the relation (not common and discouraged): for these, is tests for the relation but inherits by definition ignores conditional inheritance for S4 objects.

selectSuperClasses(cl) has similar semantics as extends(cl), typically returning subsets of the latter.

Examples

## Two examples of setIs() with coerce= and replace= arguments
## The first one works fairly well, because neither class has many
## inherited methods do be disturbed by the new inheritance

## The second example does NOT work well, because the new superclass,
## "factor", causes methods to be inherited that should not be.

## First example:
## a class definition (see \link{setClass} for class "track")
setClass("trackCurve", contains = "track",
         representation( 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 = structure(list(), x=numeric(), y=matrix(0,0,0),

                               smooth= matrix(0,0,0)))
## Automatically convert an object from class "trackCurve" into
## "trackMultiCurve", by making the y, smooth slots into 1-column matrices
setIs("trackCurve",
      "trackMultiCurve",
      coerce = function(obj) {
        new("trackMultiCurve",
            x = obj@x,
            y = as.matrix(obj@y),
            smooth = as.matrix(obj@smooth))
      },
      replace = function(obj, value) {
        obj@y <- as.matrix(value@y)
        obj@x <- value@x
        obj@smooth <- as.matrix(value@smooth)
        obj})




## Second Example:
## A class that adds a slot to "character"
setClass("stringsDated", contains = "character",
         representation(stamp="POSIXt"))

## Convert automatically to a factor by explicit coerce
setIs("stringsDated", "factor",
      coerce = function(from) factor(from@.Data),
      replace= function(from, value) {
                  from@.Data <- as.character(value); from })

ll <- sample(letters, 10, replace = TRUE)
ld <- new("stringsDated", ll, stamp = Sys.time())

levels(as(ld, "factor"))
levels(ld) # will be NULL--see comment in section on inheritance above.

## In contrast, a class that simply extends "factor"
## has no such ambiguities
setClass("factorDated", contains = "factor",
         representation(stamp="POSIXt"))
fd <- new("factorDated", factor(ll), stamp = Sys.time())
identical(levels(fd), levels(as(fd, "factor")))