R: S3-style Objects and S4-class Objects

S3Part {methods} | R Documentation

## S3-style Objects and S4-class Objects

### Description

Old-style (S3) classes may be registered as S4 classes (by calling `setOldClass`, and many have been. These classes can then be contained in (that is, superclasses of) regular S4 classes, allowing formal methods and slots to be added to the S3 behavior. The function `S3Part` extracts or replaces the S3 part of such an object and `S3Class` extracts or replaces the S3-style class. Most computations that need to deal with the S3 aspects can coerce the objects automatically, without direct calls to these functions. The functions also work for classes that extend basic vector or matrix object types. See the details below.

Also discussed are S3 <-> S4 coercion; see the section “S3 and S4 objects”

### Usage

    S3Part(object, strictS3 = FALSE, S3Class)

    S3Part(object, strictS3 = FALSE, needClass = ) <- value

    S3Class(object)

    S3Class(object) <-  value

    isXS3Class(classDef)

    slotsFromS3(object)

### Arguments

`object` | An object from some class that extends a registered S3 class, usually because the class has as one of its superclasses an S3 class registered by a call to `setOldClass`, or from a class that extends a basic vector, matrix or array object type. See the details. For most of the functions, an S3 object can also be supplied, with the interpretation that it is its own S3 part.
`strictS3` | If `TRUE`, the value returned by `S3Part` will be an S3 object, with all the S4 slots removed. Otherwise, an S4 object will always be returned; for example, from the S4 class created by `setOldClass` as a proxy for an S3 class, rather than the underlying S3 object.
`S3Class` | The character vector to be stored as the S3 class slot in the object returned. Usually, and by default, retains the slot from `object`.
`needClass` | Require that the replacement value be this class or a subclass of it.
`value` | For `S3Part<-`, the replacement value for the S3 part of the object. This does not need to be an S4 object; in fact, the usual way to create objects from these classes is by giving an S3 object of the right class as an argument to `new`. For `S3Class<-`, the character vector to assign as the S3 class.
`classDef` | A class definition object, as returned by `getClass`.

### Details

Classes that register S3 classes by a call to `setOldClass` have slot `".S3Class"` to hold the corresponding S3 vector of class strings. The prototype of such a class has the value for this slot determined by the argument to `setOldClass`.

As a result, new S4 classes that extend (contain) such registered S3 classes also have the same slot, and by default the prototype has the value determined by the `contains=` argument to `setClass`. Individual objects from the S4 class may have an S3 class corresponding to the value in the prototype or to an (S3) subclass of that value. See the examples below.

`S3Part()` with `strictS3 = TRUE` constructs the underlying S3 object by eliminating all the formally defined slots and turning off the S4 bit of the object. With `strictS3 = FALSE` the object returned is from the corresponding S4 class. For consistency and generality, `S3Part()` works also for classes that extend the basic vector, matrix and array classes. Since R is somewhat arbitrary about what it treats as an S3 class (`"ts"` is, but `"matrix"` is not), `S3Part()` tries to return an S3 (that is, non-S4) object whenever the S4 class has a suitable superclass, of either S3 or basic object type.

One general application that relies on this generality is to use `S3Part()` to get a superclass object that is guaranteed not to be an S4 object. If you are calling some function that checks for S4 objects, you need to be careful not to end up in a closed loop (`fooS4` calls `fooS3`, which checks for an S4 object and calls `fooS4` again, maybe indirectly). Using `S3Part()` with `strictS3 = TRUE` is a mechanism to avoid such loops.

Because the contents of S3 class objects have no definition or guarantee, the computations involving S3 parts do not| check for slot validity. Slots are implemented internally in R as attributes, which are copied when present in the S3 part. For this reason, grave problems can occur if an S4 class extending an S3 class uses the name of an S3 attribute as the name of an S4 slot. It's tempting to “promote” an attribute to a slot, but the resulting confusion between slot and attribute is hard to handle.

Frequently, `S3Part` can and should be avoided by simply coercing objects to the desired class; methods are automatically defined to deal correctly with the slots when `as` is called to extract or replace superclass objects.

The function `slotsFromS3()` is a generic function used internally to access the slots associated with the S3 part of the object. Methods for this function are created automatically when `setOldClass` is called with the `S4Class` argument. Usually, there is only one S3 slot, containing the S3 class, but the `S4Class` argument may provide additional slots, in the case that the S3 class has some guaranteed attributes that can be used as formal S4 slots. See the corresponding section in the documentation of `setOldClass`.

### Value

`S3Part`: Returns or sets the S3 information (and possibly some S4 slots as well, depending on arguments `S3Class` and `keepSlots`). See the discussion of argument `strict` above. If it is `TRUE` the value returned is an S3 object.
`S3Class`: For an object from a class extending S3 classes, returns or sets the character vector of class(es) stored in the object. Note that `S3Class` on any other object returns the value of `class`.
`isXS3Class`: Returns `TRUE` or `FALSE` according to whether the class defined by `ClassDef` extends S3 classes (specifically, whether it has the slot for holding the S3 class).
`slotsFromS3`: returns a list of the relevant slot classes, or an empty list for any other object.

### S3 and S4 Objects: Conversion Mechanisms

Objects in R have an internal bit that indicates whether or not to treat the object as coming from an S4 class. This bit is tested by `isS4` and can be set on or off by `asS4`. The latter function, however, does no checking or interpretation; you should only use it if you are very certain every detail has been handled correctly.

As a friendlier alternative, methods have been defined for coercing to the virtual classes `"S3"` and `"S4"`. The expressions `as(object, "S3")` and `as(object, "S4")` return S3 and S4 objects, respectively. In addition, they attempt to do conversions in a valid way, and also check validity when coercing to S4.

The expression `as(object, "S3")` can be used in two ways. For objects from one of the registered S3 classes, the expression will ensure that the class attribute is the full multi-string S3 class implied by `class(object)`. If the registered class has known attribute/slots, these will also be provided.

Another use of `as(object, "S3")` is to take an S4 object and turn it into an S3 object with corresponding attributes. This is only meaningful with S4 classes that have a data part. If you want to operate on the object without invoking S4 methods, this conversion is usually the safest way.

The expression `as(object, "S4")` will use the attributes in the object to create an object from the S4 definition of `class(object)`. This is a general mechanism to create partially defined version of S4 objects via S3 computations (not much different from invoking `new` with corresponding arguments, but usable in this form even if the S4 object has an initialize method with different arguments).

### 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

`setOldClass`

### Examples

    ## 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")

    ## lm.D9 is as computed in the example for stats::lm
    y1 = new("ylm", lm.D9, header = "test", eps = .1)
    xx = new("xlm", lm.D9, eps =.1)
    y2 = new("ylm", xx, header = "test")
    stopifnot(inherits(y2, "lm"))
    stopifnot(identical(y1, y2))
    stopifnot(identical(S3Part(y1, strict = TRUE), lm.D9))

    ## note the these classes can insert an S3 subclass of "lm" as the S3 part:
    myData <- data.frame(time = 1:10, y = (1:10)^.5)
    myLm <- lm(cbind(y, y^3)  ~ time, myData) # S3 class: c("mlm", "lm")
    ym1 = new("ylm", myLm, header = "Example", eps = 0.)

    ##similar classes to "xlm" and "ylm", but extending S3 class c("mlm", "lm")
    setClass("xmm", representation(eps = "numeric"), contains = "mlm")
    setClass("ymm", representation(header="character"), contains = "xmm")

    ym2 <- new("ymm", myLm, header = "Example2", eps = .001)

    # but for class "ymm", an S3 part of class "lm" is an error:
    try(new("ymm", lm.D9, header = "Example2", eps = .001))

    setClass("dataFrameD", representation(date = "Date"), contains = "data.frame")
    myDD <- new("dataFrameD", myData, date = Sys.Date())

    ## S3Part() applied to classes with a data part (.Data slot)

    setClass("NumX", contains="numeric", representation(id="character"))
    nn = new("NumX", 1:10, id="test")
    stopifnot(identical(1:10, S3Part(nn, strict = TRUE)))

    m1 = cbind(group, weight)
    setClass("MatX", contains = "matrix", representation(date = "Date"))
    mx1 = new("MatX", m1, date = Sys.Date())
    stopifnot(identical(m1, S3Part(mx1, strict = TRUE)))

[Package methods version 2.8.1 Index]